Publications
2024
Knežević, Nikola; Lukić, Branko; Petrič, Tadej; Jovanovič, Kosta
A Geometric Approach to Task-Specific Cartesian Stiffness Shaping Journal Article
In: Journal of Intelligent and Robotic Systems: Theory and Applications, vol. 110, no. 1, 2024, ISSN: 15730409.
@article{Knezevic2024,
title = {A Geometric Approach to Task-Specific Cartesian Stiffness Shaping},
author = {Nikola Knežević and Branko Lukić and Tadej Petrič and Kosta Jovanovič},
doi = {10.1007/s10846-023-02035-6},
issn = {15730409},
year = {2024},
date = {2024-01-01},
journal = {Journal of Intelligent and Robotic Systems: Theory and Applications},
volume = {110},
number = {1},
abstract = {Controlling the exact Cartesian stiffness values of a robot end-effector (EE) is troublesome because of difficulties associated with estimating the stiffness and controllability of a full Cartesian stiffness matrix. However, most practical applications require only quantitative (high/low) stiffness values in the EE motion direction (or perpendicular direction). Full control of the stiffness matrix requiring too many control inputs which is hardly possible in practical applications. To ensure the efficiency of execution for a range of redundant robots, we present an algorithm for shaping a robot's Cartesian stiffness ellipsoid, a more intuitive and visual stiffness representation, using a nonlinear sequential least square programming optimization. The algorithm is designed to optimize the joint stiffness values and the trajectory of the robot's joints, using null-space exploration, for a given task. Using eigenvalue decomposition of the stiffness matrix, the algorithm minimizes the orientation difference between the major axis of the current and the desired stiffness ellipsoid and specify a scaling factor between the major and the minor axis. The presented approach allows the user to better understand and control of a robot, regardless of the user's knowledge of the achievable stiffness range and the interdependencies of the Cartesian stiffness matrix elements.},
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Controlling the exact Cartesian stiffness values of a robot end-effector (EE) is troublesome because of difficulties associated with estimating the stiffness and controllability of a full Cartesian stiffness matrix. However, most practical applications require only quantitative (high/low) stiffness values in the EE motion direction (or perpendicular direction). Full control of the stiffness matrix requiring too many control inputs which is hardly possible in practical applications. To ensure the efficiency of execution for a range of redundant robots, we present an algorithm for shaping a robot's Cartesian stiffness ellipsoid, a more intuitive and visual stiffness representation, using a nonlinear sequential least square programming optimization. The algorithm is designed to optimize the joint stiffness values and the trajectory of the robot's joints, using null-space exploration, for a given task. Using eigenvalue decomposition of the stiffness matrix, the algorithm minimizes the orientation difference between the major axis of the current and the desired stiffness ellipsoid and specify a scaling factor between the major and the minor axis. The presented approach allows the user to better understand and control of a robot, regardless of the user's knowledge of the achievable stiffness range and the interdependencies of the Cartesian stiffness matrix elements.
Misković, Luka; Dežman, Miha; Petrič, Tadej
Pneumatic Exoskeleton Joint With a Self-Supporting Air Tank and Stiffness Modulation: Design, Modeling, and Experimental Evaluation Journal Article
In: IEEE/ASME Transactions on Mechatronics, vol. PP, pp. 1–12, 2024, ISSN: 1941014X.
@article{Miskovic2024,
title = {Pneumatic Exoskeleton Joint With a Self-Supporting Air Tank and Stiffness Modulation: Design, Modeling, and Experimental Evaluation},
author = {Luka Misković and Miha Dežman and Tadej Petrič},
doi = {10.1109/TMECH.2023.3344998},
issn = {1941014X},
year = {2024},
date = {2024-01-01},
journal = {IEEE/ASME Transactions on Mechatronics},
volume = {PP},
pages = {1--12},
publisher = {IEEE},
abstract = {Electromechanical variable stiffness actuators (VSA) can store and reuse different amounts of energy in the elastic element by varying the stiffness, but they are typically heavy for use in exoskeletons because they require more than one motor. At the same time, the use of pneumatic actuators in exoskeletons is suitable due to their high power-to-weight ratio and inherent compliance, where stiffness varies with applied pressure. However, the required air supply often compromises the portability of such systems. In this article, a novel pneumatic exoskeleton joint mechanism is proposed that uses a pneumatic artificial muscle (PAM) as an air tank and a pneumatic cylinder to store and reuse energy and thus generate torque. The main innovation is that the PAM is independent of an external air supply; instead, compressed air from a cylinder is used to inflate the PAM. This is achieved by timely control of three air solenoid valves and air accumulation. Variable stiffness is achieved in two ways: by changing the pressure in the pneumatic cylinder and by contracting the PAM's length. The mechanism and method of stiffness modulation are first described analytically and then evaluated experimentally on an experimental platform, where various functions, temperature effects, and leakage tests are investigated. The results show satisfactory performance and validate the theoretical concepts.},
keywords = {},
pubstate = {published},
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Electromechanical variable stiffness actuators (VSA) can store and reuse different amounts of energy in the elastic element by varying the stiffness, but they are typically heavy for use in exoskeletons because they require more than one motor. At the same time, the use of pneumatic actuators in exoskeletons is suitable due to their high power-to-weight ratio and inherent compliance, where stiffness varies with applied pressure. However, the required air supply often compromises the portability of such systems. In this article, a novel pneumatic exoskeleton joint mechanism is proposed that uses a pneumatic artificial muscle (PAM) as an air tank and a pneumatic cylinder to store and reuse energy and thus generate torque. The main innovation is that the PAM is independent of an external air supply; instead, compressed air from a cylinder is used to inflate the PAM. This is achieved by timely control of three air solenoid valves and air accumulation. Variable stiffness is achieved in two ways: by changing the pressure in the pneumatic cylinder and by contracting the PAM's length. The mechanism and method of stiffness modulation are first described analytically and then evaluated experimentally on an experimental platform, where various functions, temperature effects, and leakage tests are investigated. The results show satisfactory performance and validate the theoretical concepts.
Mišković, Luka; Tricomi, Enrica; Zhang, Xiaohui; Missiroli, Francesco; Krstanović, Kristina; Petrič, Tadej; Masia, Lorenzo
Hybrid Rigid-Soft and Pneumatic-Electromechanical Exoskeleton for Multi-Joint Lower Limb Assistance Journal Article
In: IEEE Transactions on Medical Robotics and Bionics, vol. 6, no. 3, pp. 1180-1189, 2024.
@article{Miskovic2024,
title = {Hybrid Rigid-Soft and Pneumatic-Electromechanical Exoskeleton for Multi-Joint Lower Limb Assistance},
author = {Luka Mišković and Enrica Tricomi and Xiaohui Zhang and Francesco Missiroli and Kristina Krstanović and Tadej Petrič and Lorenzo Masia},
doi = {10.1109/TMRB.2024.3421547},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {IEEE Transactions on Medical Robotics and Bionics},
volume = {6},
number = {3},
pages = {1180-1189},
keywords = {},
pubstate = {published},
tppubtype = {article}
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Žlajpah, Leon; Petrič, Tadej
RobotBlockSet (RBS)—A Comprehensive Robotics Framework Proceedings Article
In: Pisla, Doina; Carbone, Giuseppe; Condurache, Daniel; Vaida, Calin (Ed.): Advances in Service and Industrial Robotics, pp. 439–450, Springer Nature Switzerland, Cham, 2024, ISBN: 978-3-031-59257-7.
@inproceedings{10.1007/978-3-031-59257-7_44,
title = {RobotBlockSet (RBS)—A Comprehensive Robotics Framework},
author = {Leon Žlajpah and Tadej Petrič},
editor = {Doina Pisla and Giuseppe Carbone and Daniel Condurache and Calin Vaida},
isbn = {978-3-031-59257-7},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
booktitle = {Advances in Service and Industrial Robotics},
pages = {439–450},
publisher = {Springer Nature Switzerland},
address = {Cham},
abstract = {In this paper, we present the comprehensive robotics framework RBS, which addresses the critical need for seamless integration between simulation and real-world execution in robotics. The proposed framework provides a unified solution for designing, testing, and executing robotic applications, bridging the gap between virtual and physical environments. By providing interfaces for various simulators and real robots, along with tools for robot modeling, motion planning, and execution, RBS streamlines the development process. It removes the complexity associated with the transition from simulation to real systems, shortens development times and enables fast and efficient design iterations. This innovative framework holds great promise for advancing robotics research and development. It enables researchers and engineers to realise the full potential of simulation and real-world testing in the development of state-of-the-art robotic systems.},
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In this paper, we present the comprehensive robotics framework RBS, which addresses the critical need for seamless integration between simulation and real-world execution in robotics. The proposed framework provides a unified solution for designing, testing, and executing robotic applications, bridging the gap between virtual and physical environments. By providing interfaces for various simulators and real robots, along with tools for robot modeling, motion planning, and execution, RBS streamlines the development process. It removes the complexity associated with the transition from simulation to real systems, shortens development times and enables fast and efficient design iterations. This innovative framework holds great promise for advancing robotics research and development. It enables researchers and engineers to realise the full potential of simulation and real-world testing in the development of state-of-the-art robotic systems.
Šifrer, Jan; Petrič, Tadej
A Novel Approach Exploiting Contact Points on Robot Structures for Enhanced End-Effector Accuracy Proceedings Article
In: Pisla, Doina; Carbone, Giuseppe; Condurache, Daniel; Vaida, Calin (Ed.): Advances in Service and Industrial Robotics, pp. 329–336, Springer Nature Switzerland, Cham, 2024, ISBN: 978-3-031-59257-7.
@inproceedings{10.1007/978-3-031-59257-7_33,
title = {A Novel Approach Exploiting Contact Points on Robot Structures for Enhanced End-Effector Accuracy},
author = {Jan Šifrer and Tadej Petrič},
editor = {Doina Pisla and Giuseppe Carbone and Daniel Condurache and Calin Vaida},
isbn = {978-3-031-59257-7},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
booktitle = {Advances in Service and Industrial Robotics},
pages = {329–336},
publisher = {Springer Nature Switzerland},
address = {Cham},
abstract = {In this paper, we propose a novel approach that leverages contact points on the robot's structure to significantly enhance the precision of robotic mechanisms. This method involves a detailed analysis of how strategic contact utilization can lead to improved accuracy in robotic operations. Through experimental validation and comparative studies, we demonstrate the efficacy of this technique in refining the performance of robotic systems. Our findings highlight the potential of this approach in optimizing robotic functionality, opening new avenues for advanced robotic applications in various fields.},
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In this paper, we propose a novel approach that leverages contact points on the robot's structure to significantly enhance the precision of robotic mechanisms. This method involves a detailed analysis of how strategic contact utilization can lead to improved accuracy in robotic operations. Through experimental validation and comparative studies, we demonstrate the efficacy of this technique in refining the performance of robotic systems. Our findings highlight the potential of this approach in optimizing robotic functionality, opening new avenues for advanced robotic applications in various fields.
2023
Escarabajal, Rafael J; París, Elena; Petrič, Tadej; Valera, Ángel; Mata, Vicente; Babič, Jan
Assistive Upper-Limb Control using a Novel Measure of Human Muscular Manipulability based on Force Envelopes Proceedings Article
In: 2023 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 1–8, IEEE, 2023, ISBN: 979-8-3503-2570-6.
@inproceedings{Escarabajal2023,
title = {Assistive Upper-Limb Control using a Novel Measure of Human Muscular Manipulability based on Force Envelopes},
author = {Rafael J Escarabajal and Elena París and Tadej Petrič and Ángel Valera and Vicente Mata and Jan Babič},
url = {https://ieeexplore.ieee.org/document/10354618/},
doi = {10.1109/ROBIO58561.2023.10354618},
isbn = {979-8-3503-2570-6},
year = {2023},
date = {2023-12-01},
booktitle = {2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)},
pages = {1--8},
publisher = {IEEE},
abstract = {This paper presents a novel approach to measuring upper limb muscular manipulability considering human biomechanics. We address the limitations of classical manipulability measures in robotics when applied to the human body. Our method introduces the concept of a force envelope to estimate the capability of the human arm to exert forces in different directions, considering the contributions of the muscles. To achieve this, we employed a biomechanical model based on Hill's muscle model, calibrated using both geometric (segmental lengths) and strength-based (muscle activation) approaches to adapt to individual users. Furthermore, we designed a control algorithm that enables a robotic device to assist the user in unfavorable directions, guided by the manipulability measure. By providing a more isotropic response, the robotic device compensates for low manipulability in certain regions of the workspace. We conducted experiments using a haptic robot in admittance mode along the sagittal plane, where a viscous environment acted as a load to hinder human movement throughout the workspace. Our results demonstrate the effectiveness of the proposed method in reducing human effort by assisting in less manipulable directions while leaving high manipulability directions unassisted. Additionally, we successfully verified the superiority in performance of our novel approach against existing methods.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper presents a novel approach to measuring upper limb muscular manipulability considering human biomechanics. We address the limitations of classical manipulability measures in robotics when applied to the human body. Our method introduces the concept of a force envelope to estimate the capability of the human arm to exert forces in different directions, considering the contributions of the muscles. To achieve this, we employed a biomechanical model based on Hill's muscle model, calibrated using both geometric (segmental lengths) and strength-based (muscle activation) approaches to adapt to individual users. Furthermore, we designed a control algorithm that enables a robotic device to assist the user in unfavorable directions, guided by the manipulability measure. By providing a more isotropic response, the robotic device compensates for low manipulability in certain regions of the workspace. We conducted experiments using a haptic robot in admittance mode along the sagittal plane, where a viscous environment acted as a load to hinder human movement throughout the workspace. Our results demonstrate the effectiveness of the proposed method in reducing human effort by assisting in less manipulable directions while leaving high manipulability directions unassisted. Additionally, we successfully verified the superiority in performance of our novel approach against existing methods.
Razmjoo, Amirreza; Brecelj, Tilen; Savevska, Kristina; Ude, Aleš; Petrič, Tadej; Calinon, Sylvain
Learning Joint Space Reference Manifold for Reliable Physical Assistance Proceedings Article
In: 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 10412–10417, IEEE, 2023, ISSN: 21530866.
@inproceedings{Razmjoo2023,
title = {Learning Joint Space Reference Manifold for Reliable Physical Assistance},
author = {Amirreza Razmjoo and Tilen Brecelj and Kristina Savevska and Aleš Ude and Tadej Petrič and Sylvain Calinon},
url = {https://ieeexplore.ieee.org/document/10342173/},
doi = {10.1109/IROS55552.2023.10342173},
issn = {21530866},
year = {2023},
date = {2023-10-01},
booktitle = {2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages = {10412--10417},
publisher = {IEEE},
abstract = {This paper presents a study on the use of the Talos humanoid robot for performing assistive sit-to-stand or stand-to-sit tasks. In such tasks, the human exerts a large amount of force (100-200 N) within a very short time (2-8 s), posing significant challenges in terms of human unpredictability and robot stability control. To address these challenges, we propose an approach for finding a spatial reference for the robot, which allows the robot to move according to the force exerted by the human and control its stability during the task. Specifically, we focus on the problem of finding a 1D manifold for the robot, while assuming a simple controller to guide its movement on this manifold. To achieve this, we use a functional representation to parameterize the manifold and solve an optimization problem that takes into account the robot's stability and the unpredictability of human behavior. We demonstrate the effectiveness of our approach through simulations and experiments with the Talos robot, showing robustness and adaptability.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
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This paper presents a study on the use of the Talos humanoid robot for performing assistive sit-to-stand or stand-to-sit tasks. In such tasks, the human exerts a large amount of force (100-200 N) within a very short time (2-8 s), posing significant challenges in terms of human unpredictability and robot stability control. To address these challenges, we propose an approach for finding a spatial reference for the robot, which allows the robot to move according to the force exerted by the human and control its stability during the task. Specifically, we focus on the problem of finding a 1D manifold for the robot, while assuming a simple controller to guide its movement on this manifold. To achieve this, we use a functional representation to parameterize the manifold and solve an optimization problem that takes into account the robot's stability and the unpredictability of human behavior. We demonstrate the effectiveness of our approach through simulations and experiments with the Talos robot, showing robustness and adaptability.
Petrič, Tadej; Žlajpah, Leon
Kinematic model calibration of a collaborative redundant robot using a closed kinematic chain Journal Article
In: Scientific Reports, vol. 13, no. 1, pp. 1–12, 2023, ISSN: 20452322.
@article{Petric2023,
title = {Kinematic model calibration of a collaborative redundant robot using a closed kinematic chain},
author = {Tadej Petrič and Leon Žlajpah},
url = {https://doi.org/10.1038/s41598-023-45156-6},
doi = {10.1038/s41598-023-45156-6},
issn = {20452322},
year = {2023},
date = {2023-01-01},
journal = {Scientific Reports},
volume = {13},
number = {1},
pages = {1--12},
publisher = {Nature Publishing Group UK},
abstract = {In this paper, we propose a novel approach for the kinematic calibration of collaborative redundat robots, focusing on improving their precision using a cost-effective and efficient method. We exploit the redundancy of the closed-loop kinematic chain by utilizing a spherical joint, enabling precise definition of the robot end-effector position while maintaining free joint motion in the null space. Leveraging the availability of joint torque sensors in most collaborative robots, we employ a kinesthetic approach to obtain constrained joint motion for calibration. An optimization approach is utilized to determine the optimal kinematic parameters based on measured joint positions and a constrained end-effector position defined by the spherical joint. The effectiveness of the proposed method is demonstrated and validated on the Franka Emika Panda robot, a 7-DoF robot. Results indicate a significant enhancement in absolute accuracy, with comparable performance to more expensive sensor systems such as optical measurement systems. Our approach offers a practical and cost-effective solution for improving the precision of collaborative robots.},
keywords = {},
pubstate = {published},
tppubtype = {article}
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In this paper, we propose a novel approach for the kinematic calibration of collaborative redundat robots, focusing on improving their precision using a cost-effective and efficient method. We exploit the redundancy of the closed-loop kinematic chain by utilizing a spherical joint, enabling precise definition of the robot end-effector position while maintaining free joint motion in the null space. Leveraging the availability of joint torque sensors in most collaborative robots, we employ a kinesthetic approach to obtain constrained joint motion for calibration. An optimization approach is utilized to determine the optimal kinematic parameters based on measured joint positions and a constrained end-effector position defined by the spherical joint. The effectiveness of the proposed method is demonstrated and validated on the Franka Emika Panda robot, a 7-DoF robot. Results indicate a significant enhancement in absolute accuracy, with comparable performance to more expensive sensor systems such as optical measurement systems. Our approach offers a practical and cost-effective solution for improving the precision of collaborative robots.
Brecelj, Tilen; Petrič, Tadej
Stable Heteroclinic Channel Networks for Physical Human–Humanoid Robot Collaboration Journal Article
In: Sensors, vol. 23, no. 3, 2023, ISSN: 14248220.
@article{Brecelj2023,
title = {Stable Heteroclinic Channel Networks for Physical Human–Humanoid Robot Collaboration},
author = {Tilen Brecelj and Tadej Petrič},
doi = {10.3390/s23031396},
issn = {14248220},
year = {2023},
date = {2023-01-01},
journal = {Sensors},
volume = {23},
number = {3},
abstract = {Human–robot collaboration is one of the most challenging fields in robotics, as robots must understand human intentions and suitably cooperate with them in the given circumstances. But although this is one of the most investigated research areas in robotics, it is still in its infancy. In this paper, human–robot collaboration is addressed by applying a phase state system, guided by stable heteroclinic channel networks, to a humanoid robot. The base mathematical model is first defined and illustrated on a simple three-state system. Further on, an eight-state system is applied to a humanoid robot to guide it and make it perform different movements according to the forces exerted on its grippers. The movements presented in this paper are squatting, standing up, and walking forwards and backward, while the motion velocity depends on the magnitude of the applied forces. The method presented in this paper proves to be a suitable way of controlling robots by means of physical human-robot interaction. As the phase state system and the robot movements can both be further extended to make the robot execute many other tasks, the proposed method seems to provide a promising way for further investigation and realization of physical human–robot interaction.},
keywords = {},
pubstate = {published},
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Human–robot collaboration is one of the most challenging fields in robotics, as robots must understand human intentions and suitably cooperate with them in the given circumstances. But although this is one of the most investigated research areas in robotics, it is still in its infancy. In this paper, human–robot collaboration is addressed by applying a phase state system, guided by stable heteroclinic channel networks, to a humanoid robot. The base mathematical model is first defined and illustrated on a simple three-state system. Further on, an eight-state system is applied to a humanoid robot to guide it and make it perform different movements according to the forces exerted on its grippers. The movements presented in this paper are squatting, standing up, and walking forwards and backward, while the motion velocity depends on the magnitude of the applied forces. The method presented in this paper proves to be a suitable way of controlling robots by means of physical human-robot interaction. As the phase state system and the robot movements can both be further extended to make the robot execute many other tasks, the proposed method seems to provide a promising way for further investigation and realization of physical human–robot interaction.
Baumgartner, Jakob; Petrič, Tadej; Klančar, Gregor
Potential Field Control of a Redundant Nonholonomic Mobile Manipulator with Corridor-Constrained Base Motion Journal Article
In: Machines, vol. 11, no. 2, pp. 1–18, 2023, ISSN: 20751702.
@article{Baumgartner2023,
title = {Potential Field Control of a Redundant Nonholonomic Mobile Manipulator with Corridor-Constrained Base Motion},
author = {Jakob Baumgartner and Tadej Petrič and Gregor Klančar},
doi = {10.3390/machines11020293},
issn = {20751702},
year = {2023},
date = {2023-01-01},
journal = {Machines},
volume = {11},
number = {2},
pages = {1--18},
abstract = {This work proposes a solution for redundant nonholonomic mobile manipulator control with corridor constraints on base motion. The proposed control strategy applies an artificial potential field for base navigation to achieve joint control with desired trajectory tracking of the end effector. The overall kinematic model is created by describing the nonholonomic mobile platform and the kinematics of the manipulator. The objective function used consists of a primary control task that optimizes the joint variables to achieve the desired pose or trajectory of the end effector and a secondary control task that optimizes the joint variables for the base to support the arm and stay within the corridor. As a last priority, an additional optimization is introduced to optimize the maneuverability index. The proposed baseline navigation has global convergence without local minima and is computationally efficient. This is achieved by an optimal grid-based search on a coarse discrete grid and a bilinear interpolation to obtain a continuous potential function and its gradient. The performance of the proposed control algorithm is illustrated by several simulations of a mobile manipulator model derived for a Pal Tiago mobile base and an Emiko Franka Panda robotic manipulator.},
keywords = {},
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This work proposes a solution for redundant nonholonomic mobile manipulator control with corridor constraints on base motion. The proposed control strategy applies an artificial potential field for base navigation to achieve joint control with desired trajectory tracking of the end effector. The overall kinematic model is created by describing the nonholonomic mobile platform and the kinematics of the manipulator. The objective function used consists of a primary control task that optimizes the joint variables to achieve the desired pose or trajectory of the end effector and a secondary control task that optimizes the joint variables for the base to support the arm and stay within the corridor. As a last priority, an additional optimization is introduced to optimize the maneuverability index. The proposed baseline navigation has global convergence without local minima and is computationally efficient. This is achieved by an optimal grid-based search on a coarse discrete grid and a bilinear interpolation to obtain a continuous potential function and its gradient. The performance of the proposed control algorithm is illustrated by several simulations of a mobile manipulator model derived for a Pal Tiago mobile base and an Emiko Franka Panda robotic manipulator.
Lukić, Branko; Jovanović, Kosta; Žlajpah, Leon; Petrič, Tadej
Online Cartesian Compliance Shaping of Redundant Robots in Assembly Tasks Journal Article
In: Machines, vol. 11, no. 1, 2023, ISSN: 20751702.
@article{Lukic2023,
title = {Online Cartesian Compliance Shaping of Redundant Robots in Assembly Tasks},
author = {Branko Lukić and Kosta Jovanović and Leon Žlajpah and Tadej Petrič},
doi = {10.3390/machines11010035},
issn = {20751702},
year = {2023},
date = {2023-01-01},
journal = {Machines},
volume = {11},
number = {1},
abstract = {This paper presents a universal approach to shaping the mechanical properties of the interaction between a collaborative robot and its environment through an end-effector Cartesian compliance shaping. More specifically, the focus is on the class of kinematically redundant robots, for which a novel redundancy reconfiguration scheme for online optimization of the Cartesian compliance of the end-effector is presented. The null-space reconfiguration aims to enable the more efficient and versatile use of collaborative robots, including robots with passive compliant joints. The proposed approach is model-based and gradient-based to enable real-time computation and reconfiguration of the robot for Cartesian compliance while ensuring accurate position tracking. The optimization algorithm combines two coordinate frames: the global (world) coordinate frame commonly used for end-effector trajectory tracking; and the coordinate frame fixed to the end-effector in which optimization is computed. Another attractive feature of the approach is the bound on the magnitude of the interaction force in contact tasks. The results are validated on a torque-controlled 7-DOF KUKA LWR robot emulating joint compliance in a quasi-static experiment (the robot exerts a force on an external object) and a peg-in-hole experiment emulating an assembly task.},
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This paper presents a universal approach to shaping the mechanical properties of the interaction between a collaborative robot and its environment through an end-effector Cartesian compliance shaping. More specifically, the focus is on the class of kinematically redundant robots, for which a novel redundancy reconfiguration scheme for online optimization of the Cartesian compliance of the end-effector is presented. The null-space reconfiguration aims to enable the more efficient and versatile use of collaborative robots, including robots with passive compliant joints. The proposed approach is model-based and gradient-based to enable real-time computation and reconfiguration of the robot for Cartesian compliance while ensuring accurate position tracking. The optimization algorithm combines two coordinate frames: the global (world) coordinate frame commonly used for end-effector trajectory tracking; and the coordinate frame fixed to the end-effector in which optimization is computed. Another attractive feature of the approach is the bound on the magnitude of the interaction force in contact tasks. The results are validated on a torque-controlled 7-DOF KUKA LWR robot emulating joint compliance in a quasi-static experiment (the robot exerts a force on an external object) and a peg-in-hole experiment emulating an assembly task.
Čamernik, Jernej; Leskovar, Rebeka Kropivšek; Petrič, Tadej
Leader–Follower Dynamics in Complex Obstacle Avoidance Task Journal Article
In: International Journal of Social Robotics, vol. 15, no. 1, pp. 59–70, 2023, ISSN: 1875-4791.
@article{Camernik2023,
title = {Leader–Follower Dynamics in Complex Obstacle Avoidance Task},
author = {Jernej Čamernik and Rebeka Kropivšek Leskovar and Tadej Petrič},
url = {https://link.springer.com/10.1007/s12369-022-00945-3},
doi = {10.1007/s12369-022-00945-3},
issn = {1875-4791},
year = {2023},
date = {2023-01-01},
journal = {International Journal of Social Robotics},
volume = {15},
number = {1},
pages = {59--70},
abstract = {A question that many researchers in social robotics are addressing is how to create more human-like behaviour in robots to make the collaboration between a human and a robot more intuitive to the human partner. In order to develop a human-like collaborative robotic system, however, human collaboration must first be better understood. Human collaboration is something we are all familiar with, however not that much is known about it from a kinematic standpoint. One dynamic that hasn't been researched thoroughly, yet naturally occurs in human collaboration, is for instance leader–follower dynamics. In our previous study, we tackled the question of leader–follower role allocation in human dyads during a collaborative reaching task, where the results implied that the subjects who performed higher in the individual experiment would naturally assume the role of a leader when in physical collaboration. In this study, we build upon the leader–follower role allocation study in human dyads by observing how the leader–follower dynamics change when the collaborative task becomes more complex. Here, the study was performed on a reaching task, where one subject in a dyad was faced with an additional task of obstacle avoidance when performing a 2D reaching task, while their partner was not aware of the obstacle. We have found that subjects change their roles throughout the task in order to complete it successfully, however looking at the overall task leader the higher-performing individual will always dominate over the lower-performing one, regardless of whether they are aware of the additional task of obstacle avoidance or not.},
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A question that many researchers in social robotics are addressing is how to create more human-like behaviour in robots to make the collaboration between a human and a robot more intuitive to the human partner. In order to develop a human-like collaborative robotic system, however, human collaboration must first be better understood. Human collaboration is something we are all familiar with, however not that much is known about it from a kinematic standpoint. One dynamic that hasn't been researched thoroughly, yet naturally occurs in human collaboration, is for instance leader–follower dynamics. In our previous study, we tackled the question of leader–follower role allocation in human dyads during a collaborative reaching task, where the results implied that the subjects who performed higher in the individual experiment would naturally assume the role of a leader when in physical collaboration. In this study, we build upon the leader–follower role allocation study in human dyads by observing how the leader–follower dynamics change when the collaborative task becomes more complex. Here, the study was performed on a reaching task, where one subject in a dyad was faced with an additional task of obstacle avoidance when performing a 2D reaching task, while their partner was not aware of the obstacle. We have found that subjects change their roles throughout the task in order to complete it successfully, however looking at the overall task leader the higher-performing individual will always dominate over the lower-performing one, regardless of whether they are aware of the additional task of obstacle avoidance or not.
Žlajpah, Leon; Petrič, Tadej
Optimizing Robot Positioning Accuracy with Kinematic Calibration and Deflection Estimation Proceedings Article
In: Petrič, Tadej; Ude, Aleš; Žlajpah, Leon (Ed.): Advances in Service and Industrial Robotics, pp. 255–263, Springer Nature Switzerland, Cham, 2023, ISBN: 978-3-031-32606-6.
@inproceedings{10.1007/978-3-031-32606-6_30,
title = {Optimizing Robot Positioning Accuracy with Kinematic Calibration and Deflection Estimation},
author = {Leon Žlajpah and Tadej Petrič},
editor = {Tadej Petrič and Aleš Ude and Leon Žlajpah},
url = {https://link.springer.com/10.1007/978-3-031-32606-6_30},
doi = {10.1007/978-3-031-32606-6_30},
isbn = {978-3-031-32606-6},
year = {2023},
date = {2023-01-01},
booktitle = {Advances in Service and Industrial Robotics},
pages = {255--263},
publisher = {Springer Nature Switzerland},
address = {Cham},
abstract = {To achieve higher positioning accuracy, it is common practice to calibrate the robot. An essential part of the calibration is the estimation of the kinematic parameters. Due to various nonlinear influences on the end-effector position accuracy, such as joint and link flexibility, standard methods of identifying kinematic parameters do not always give a satisfactory result. In this paper, we propose a strategy that considers deflection-dependent errors to improve the overall positioning accuracy of the robot. As joint/link deflections mainly depend on gravity, we include the compensation of gravity-induced errors in the estimation procedure. In the first step of the proposed strategy, we compute the joint position errors caused by gravity. In the next step, we apply an existing optimization method to estimate the kinematic parameters. We propose to use an optimization based on random configurations. Such an approach allows good calibration even when we want to calibrate a robot in a bounded workspace. Since calibration is generally time consuming, we investigated how the number of measured configurations influences the calibration. To evaluate the proposed method, we used a simulation of the collaborative robot Franka Emika Panda in MuJoCo.},
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To achieve higher positioning accuracy, it is common practice to calibrate the robot. An essential part of the calibration is the estimation of the kinematic parameters. Due to various nonlinear influences on the end-effector position accuracy, such as joint and link flexibility, standard methods of identifying kinematic parameters do not always give a satisfactory result. In this paper, we propose a strategy that considers deflection-dependent errors to improve the overall positioning accuracy of the robot. As joint/link deflections mainly depend on gravity, we include the compensation of gravity-induced errors in the estimation procedure. In the first step of the proposed strategy, we compute the joint position errors caused by gravity. In the next step, we apply an existing optimization method to estimate the kinematic parameters. We propose to use an optimization based on random configurations. Such an approach allows good calibration even when we want to calibrate a robot in a bounded workspace. Since calibration is generally time consuming, we investigated how the number of measured configurations influences the calibration. To evaluate the proposed method, we used a simulation of the collaborative robot Franka Emika Panda in MuJoCo.
Brecelj, Tilen; Petrič, Tadej
Application of a Phase State System for Physical Human-Humanoid Robot Collaboration Proceedings Article
In: Petrič, Tadej; Ude, Aleš; Žlajpah, Leon (Ed.): Advances in Service and Industrial Robotics, pp. 89–96, Springer Nature Switzerland, Cham, 2023, ISBN: 978-3-031-32606-6.
@inproceedings{10.1007/978-3-031-32606-6_11,
title = {Application of a Phase State System for Physical Human-Humanoid Robot Collaboration},
author = {Tilen Brecelj and Tadej Petrič},
editor = {Tadej Petrič and Aleš Ude and Leon Žlajpah},
url = {https://link.springer.com/10.1007/978-3-031-32606-6_11},
doi = {10.1007/978-3-031-32606-6_11},
isbn = {978-3-031-32606-6},
year = {2023},
date = {2023-01-01},
booktitle = {Advances in Service and Industrial Robotics},
pages = {89--96},
publisher = {Springer Nature Switzerland},
address = {Cham},
abstract = {Collaborative robotics is one of the fastest developing but at the same time one of the most challenging fields in robotics. The reason for the latter is that a good robot collaborator should precisely understand the intentions of the human coworker. In this paper, human-robot collaboration is addressed by the application of a dynamical phase state system guided by stable heteroclinic channel networks to the motion of a humanoid robot. With this approach, a person can control the underlying dynamical system by applying forces to the grippers of the humanoid robot and this way guide the robot. The robot motions presented in this paper are lifting up the forearms and squatting, but the dynamical model can be further extended to incorporate an arbitrary amount of motions. The presented approach, therefore, provides a suitable way for the realization of efficient human-robot collaboration and should be further explored and developed.},
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Collaborative robotics is one of the fastest developing but at the same time one of the most challenging fields in robotics. The reason for the latter is that a good robot collaborator should precisely understand the intentions of the human coworker. In this paper, human-robot collaboration is addressed by the application of a dynamical phase state system guided by stable heteroclinic channel networks to the motion of a humanoid robot. With this approach, a person can control the underlying dynamical system by applying forces to the grippers of the humanoid robot and this way guide the robot. The robot motions presented in this paper are lifting up the forearms and squatting, but the dynamical model can be further extended to incorporate an arbitrary amount of motions. The presented approach, therefore, provides a suitable way for the realization of efficient human-robot collaboration and should be further explored and developed.
2022
Žlajpah, Leon; Petrič, Tadej
Kinematic calibration for collaborative robots on a mobile platform using motion capture system Journal Article
In: Robotics and Computer-Integrated Manufacturing, vol. 79, pp. 102446, 2022, ISSN: 0736-5845.
@article{zlajpah2022,
title = {Kinematic calibration for collaborative robots on a mobile platform using motion capture system},
author = {Leon Žlajpah and Tadej Petrič},
url = {https://www.sciencedirect.com/science/article/pii/S0736584522001296},
doi = {https://doi.org/10.1016/j.rcim.2022.102446},
issn = {0736-5845},
year = {2022},
date = {2022-09-01},
journal = {Robotics and Computer-Integrated Manufacturing},
volume = {79},
pages = {102446},
abstract = {For modern robotic applications that go beyond the typical industrial environment, absolute accuracy is one of the key properties that make this possible. There are several approaches in the literature to improve robot accuracy for a typical industrial robot mounted on a fixed frame. In contrast, there is no method to improve robot accuracy when the robot is mounted on a mobile base, which is typical for collaborative robots. Therefore, in this work, we proposed and analyzed two approaches to improve the absolute accuracy of the robot mounted on a mobile platform using an optical measurement system. The first approach is based on geometric operations used to calculate the rotation axes of each joint. This approach identifies all rotational axes, which allows the calculation of the Denavit–Hartenberg (DH) parameters and thus the complete kinematic model, including the position and orientation errors of the robot end-effector and the robot base. The second approach to parameter estimation is based on optimization using a set of joint positions and end-effector poses to find the optimal DH parameters. Since the robot is mounted on a mobile base that is not fixed, an optical measurement system was used to dynamically and simultaneously measure the position of the robot base and the end-effector. The performance of the two proposed methods was analyzed and validated on a 7-DoF Franka Emika Panda robot mounted on a mobile platform PAL Tiago-base. The results show a significant improvement in absolute accuracy for both proposed approaches. By using the proposed approach with the optical measurement system, we can easily automate the estimation of robot kinematic parameters with the aim of improving absolute accuracy, especially in applications that require high positioning accuracy.},
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For modern robotic applications that go beyond the typical industrial environment, absolute accuracy is one of the key properties that make this possible. There are several approaches in the literature to improve robot accuracy for a typical industrial robot mounted on a fixed frame. In contrast, there is no method to improve robot accuracy when the robot is mounted on a mobile base, which is typical for collaborative robots. Therefore, in this work, we proposed and analyzed two approaches to improve the absolute accuracy of the robot mounted on a mobile platform using an optical measurement system. The first approach is based on geometric operations used to calculate the rotation axes of each joint. This approach identifies all rotational axes, which allows the calculation of the Denavit–Hartenberg (DH) parameters and thus the complete kinematic model, including the position and orientation errors of the robot end-effector and the robot base. The second approach to parameter estimation is based on optimization using a set of joint positions and end-effector poses to find the optimal DH parameters. Since the robot is mounted on a mobile base that is not fixed, an optical measurement system was used to dynamically and simultaneously measure the position of the robot base and the end-effector. The performance of the two proposed methods was analyzed and validated on a 7-DoF Franka Emika Panda robot mounted on a mobile platform PAL Tiago-base. The results show a significant improvement in absolute accuracy for both proposed approaches. By using the proposed approach with the optical measurement system, we can easily automate the estimation of robot kinematic parameters with the aim of improving absolute accuracy, especially in applications that require high positioning accuracy.
Gams, Andrej; Petrič, Tadej; Nemec, Bojan; Ude, Aleš
Manipulation Learning on Humanoid Robots Journal Article
In: Current Robotics Reports, vol. 3, no. 3, pp. 97-109, 2022, ISSN: 2662-4087.
@article{Gams2022,
title = {Manipulation Learning on Humanoid Robots},
author = {Andrej Gams and Tadej Petri{č} and Bojan Nemec and Aleš Ude},
url = {https://doi.org/10.1007/s43154-022-00082-9},
doi = {10.1007/s43154-022-00082-9},
issn = {2662-4087},
year = {2022},
date = {2022-09-01},
journal = {Current Robotics Reports},
volume = {3},
number = {3},
pages = {97-109},
abstract = {The ability to autonomously manipulate the physical world is the key capability needed to fulfill the potential of cognitive robots. Humanoid robots, which offer very rich sensorimotor capabilities, have made giant leaps in their manipulation capabilities in recent years. Due to their similarity to humans, the progress can be partially attributed to the learning by demonstration paradigm. Supplemented by the autonomous learning methods to refine the demonstrated manipulation actions, humanoid robots can effectively learn new manipulation skills. In this paper we present continuous effort by our research group to advance the manipulation capabilities of humanoid robots and bring them to autonomously act in an unstructured world.},
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The ability to autonomously manipulate the physical world is the key capability needed to fulfill the potential of cognitive robots. Humanoid robots, which offer very rich sensorimotor capabilities, have made giant leaps in their manipulation capabilities in recent years. Due to their similarity to humans, the progress can be partially attributed to the learning by demonstration paradigm. Supplemented by the autonomous learning methods to refine the demonstrated manipulation actions, humanoid robots can effectively learn new manipulation skills. In this paper we present continuous effort by our research group to advance the manipulation capabilities of humanoid robots and bring them to autonomously act in an unstructured world.
Miskovic, Luka; Deman, Miha; Petric, Tadej
Pneumatic quasi-passive variable stiffness mechanism for energy storage applications Journal Article
In: IEEE Robotics and Automation Letters, pp. 1-1, 2022.
@article{9674781,
title = {Pneumatic quasi-passive variable stiffness mechanism for energy storage applications},
author = {Luka Miskovic and Miha Deman and Tadej Petric},
doi = {10.1109/LRA.2022.3141211},
year = {2022},
date = {2022-01-01},
journal = {IEEE Robotics and Automation Letters},
pages = {1-1},
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Leskovar, Rebeka Kropivšek; Čamernik, Jernej; Petrič, Tadej
Leader-Follower Dynamics in Complex Obstacle Avoidance Task Journal Article
In: arXiv preprint arXiv:2207.04791, 2022.
@article{leskovar2022leader,
title = {Leader-Follower Dynamics in Complex Obstacle Avoidance Task},
author = {Rebeka Kropivšek Leskovar and Jernej Čamernik and Tadej Petrič},
url = {https://arxiv.org/abs/2207.04791},
doi = {https://doi.org/10.48550/arXiv.2207.04791},
year = {2022},
date = {2022-01-01},
journal = {arXiv preprint arXiv:2207.04791},
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Leskovar, Rebeka Kropivšek; Petrič;, Tadej
Increased Complexity of a Human-Robot Collaborative Task May Increase the Need for a Socially Competent Robot Proceedings Article
In: 2022 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO), pp. 1-6, 2022.
@inproceedings{9802968,
title = {Increased Complexity of a Human-Robot Collaborative Task May Increase the Need for a Socially Competent Robot},
author = {Rebeka Kropivšek Leskovar and Tadej Petrič;},
doi = {10.1109/ARSO54254.2022.9802968},
year = {2022},
date = {2022-01-01},
booktitle = {2022 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO)},
pages = {1-6},
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Brecelj, Tilen; Petrič, Tadej
Zero Moment Line—Universal Stability Parameter for Multi-Contact Systems in Three Dimensions Journal Article
In: Sensors, vol. 22, no. 15, 2022, ISSN: 1424-8220.
@article{Brecelj2022,
title = {Zero Moment Line—Universal Stability Parameter for Multi-Contact Systems in Three Dimensions},
author = {Tilen Brecelj and Tadej Petrič},
url = {https://www.mdpi.com/1424-8220/22/15/5656},
doi = {10.3390/s22155656},
issn = {1424-8220},
year = {2022},
date = {2022-01-01},
journal = {Sensors},
volume = {22},
number = {15},
abstract = {The widely used stability parameter, the zero moment point (ZMP), which is usually defined on the ground, is redefined, in this paper, in two different ways to acquire a more general form that allows its application to systems that are not supported only on the ground, and therefore, their support polygon does not extend only on the floor. This way it allows to determine the stability of humanoid and other floating-based robots that are interacting with the environment at arbitrary heights. In the first redefinition, the ZMP is represented as a line containing all possible ZMPs, called the zero moment line (ZML), while in the second redefinition, the ZMP is represented as the ZMP angle, i.e., the angle between the ZML and the vertical line, passing through the center of mass (COM) of the investigated system. The first redefinition is useful in situations when the external forces and their acting locations are known, while the second redefinition can be applied in situations when the COM of the system under study is known and can be tracked. The first redefinition of the ZMP is also applied to two different measurements performed with two force plates, two force sensors, and the Optitrack system. In the first measurement, a subject stands up from a bench and sits down while being pulled by its hands, while in the second measurement, two subjects stand still, hold on to two double handles, and lean backward. In both cases, the stability of the subjects involved in the measurements is investigated and discussed.},
keywords = {},
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The widely used stability parameter, the zero moment point (ZMP), which is usually defined on the ground, is redefined, in this paper, in two different ways to acquire a more general form that allows its application to systems that are not supported only on the ground, and therefore, their support polygon does not extend only on the floor. This way it allows to determine the stability of humanoid and other floating-based robots that are interacting with the environment at arbitrary heights. In the first redefinition, the ZMP is represented as a line containing all possible ZMPs, called the zero moment line (ZML), while in the second redefinition, the ZMP is represented as the ZMP angle, i.e., the angle between the ZML and the vertical line, passing through the center of mass (COM) of the investigated system. The first redefinition is useful in situations when the external forces and their acting locations are known, while the second redefinition can be applied in situations when the COM of the system under study is known and can be tracked. The first redefinition of the ZMP is also applied to two different measurements performed with two force plates, two force sensors, and the Optitrack system. In the first measurement, a subject stands up from a bench and sits down while being pulled by its hands, while in the second measurement, two subjects stand still, hold on to two double handles, and lean backward. In both cases, the stability of the subjects involved in the measurements is investigated and discussed.
2021
Leskovar, Rebeka Kropivšek; Čamernik, Jernej; Petrič, Tadej
Leader–Follower Role Allocation for Physical Collaboration in Human Dyads Journal Article
In: Applied Sciences, vol. 11, no. 19, 2021, ISSN: 2076-3417.
@article{Leskovar2021,
title = {Leader–Follower Role Allocation for Physical Collaboration in Human Dyads},
author = {Rebeka Kropivšek Leskovar and Jernej Čamernik and Tadej Petrič},
url = {https://www.mdpi.com/2076-3417/11/19/8928},
doi = {10.3390/app11198928},
issn = {2076-3417},
year = {2021},
date = {2021-09-25},
journal = {Applied Sciences},
volume = {11},
number = {19},
abstract = {People often find themselves in situations where collaboration with others is necessary to accomplish a particular task. In such cases, a leader–follower relationship is established to coordinate a plan to achieve a common goal. This is usually accomplished through verbal communication. However, what happens when verbal communication is not possible? In this study, we observe the dynamics of a leader–follower relationship in human dyads during collaborative tasks where there is no verbal communication between partners. Using two robotic arms, we designed a collaborative experimental task in which subjects perform the task individually or coupled together through a virtual model. The results show that human partners fall into the leader–follower dynamics even when they cannot communicate verbally. We demonstrate this in two steps. First, we study how each subject in a collaboration influences task performance, and second, we evaluate whether both partners influence it equally or not using our proposed sorting method to objectively identify a leader. We also study the leader–follower dynamics by analysing the task performance of partners during their individual sessions to predict the role distribution in a dyad. Based on the results of our prediction method, we conclude that the higher-performing individual performance will assume the role of a leader in collaboration.},
keywords = {},
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People often find themselves in situations where collaboration with others is necessary to accomplish a particular task. In such cases, a leader–follower relationship is established to coordinate a plan to achieve a common goal. This is usually accomplished through verbal communication. However, what happens when verbal communication is not possible? In this study, we observe the dynamics of a leader–follower relationship in human dyads during collaborative tasks where there is no verbal communication between partners. Using two robotic arms, we designed a collaborative experimental task in which subjects perform the task individually or coupled together through a virtual model. The results show that human partners fall into the leader–follower dynamics even when they cannot communicate verbally. We demonstrate this in two steps. First, we study how each subject in a collaboration influences task performance, and second, we evaluate whether both partners influence it equally or not using our proposed sorting method to objectively identify a leader. We also study the leader–follower dynamics by analysing the task performance of partners during their individual sessions to predict the role distribution in a dyad. Based on the results of our prediction method, we conclude that the higher-performing individual performance will assume the role of a leader in collaboration.
Simonič, Mihael; Petrič, Tadej; Ude, Aleš; Nemec, Bojan
Analysis of Methods for Incremental Policy Refinement by Kinesthetic Guidance Journal Article
In: Journal of Intelligent & Robotic Systems, vol. 102, no. 1, pp. 5, 2021, ISSN: 0921-0296.
@article{Simonic2021,
title = {Analysis of Methods for Incremental Policy Refinement by Kinesthetic Guidance},
author = {Mihael Simonič and Tadej Petrič and Aleš Ude and Bojan Nemec},
url = {https://link.springer.com/10.1007/s10846-021-01328-y},
doi = {10.1007/s10846-021-01328-y},
issn = {0921-0296},
year = {2021},
date = {2021-05-01},
journal = {Journal of Intelligent & Robotic Systems},
volume = {102},
number = {1},
pages = {5},
abstract = {Traditional robot programming is often not feasible in small-batch production, as it is time-consuming, inefficient, and expensive. To shorten the time necessary to deploy robot tasks, we need appropriate tools to enable efficient reuse of existing robot control policies. Incremental Learning from Demonstration (iLfD) and reversible Dynamic Movement Primitives (DMP) provide a framework for efficient policy demonstration and adaptation. In this paper, we extend our previously proposed framework with improvements that provide better performance and lower the algorithm's computational burden. Further, we analyse the learning stability and evaluate the proposed framework with a comprehensive user study. The proposed methods have been evaluated on two popular collaborative robots, Franka Emika Panda and Universal Robot UR10.},
keywords = {},
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Traditional robot programming is often not feasible in small-batch production, as it is time-consuming, inefficient, and expensive. To shorten the time necessary to deploy robot tasks, we need appropriate tools to enable efficient reuse of existing robot control policies. Incremental Learning from Demonstration (iLfD) and reversible Dynamic Movement Primitives (DMP) provide a framework for efficient policy demonstration and adaptation. In this paper, we extend our previously proposed framework with improvements that provide better performance and lower the algorithm's computational burden. Further, we analyse the learning stability and evaluate the proposed framework with a comprehensive user study. The proposed methods have been evaluated on two popular collaborative robots, Franka Emika Panda and Universal Robot UR10.
Knezevic, Nikola; Lukic, Branko; Jovanovic, Kosta; Zlajpah, Leon; Petric, Tadej
End-effector Cartesian stiffness shaping - sequential least squares programming approach Journal Article
In: Serbian Journal of Electrical Engineering, vol. 18, no. 1, pp. 1–14, 2021, ISSN: 1451-4869.
@article{Knezevic2021,
title = {End-effector Cartesian stiffness shaping - sequential least squares programming approach},
author = {Nikola Knezevic and Branko Lukic and Kosta Jovanovic and Leon Zlajpah and Tadej Petric},
url = {http://www.doiserbia.nb.rs/Article.aspx?ID=1451-48692101001K
http://cobotat.ijs.si/wp-content/uploads/2021/04/Knezevic-et-al._2021_End-effector-Cartesian-stiffness-shaping-sequential-least-squares-programming-approach_Serbian-Journal-of-Electri.pdf},
doi = {10.2298/SJEE2101001K},
issn = {1451-4869},
year = {2021},
date = {2021-01-01},
journal = {Serbian Journal of Electrical Engineering},
volume = {18},
number = {1},
pages = {1--14},
abstract = {Control of robot end-effector (EE) Cartesian stiffness matrix (or the whole mechanical impedance) is still a challenging open issue in physical humanrobot interaction (pHRI). This paper presents an optimization approach for shaping the robot EE Cartesian stiffness. This research targets collaborative robots with intrinsic compliance – serial elastic actuators (SEAs). Although robots with SEAs have constant joint stiffness, task redundancy (null-space) for a specific task could be used for robot reconfiguration and shaping the stiffness matrix while still keeping the EE position unchanged. The method proposed in this paper to investigate null-space reconfiguration's influence on Cartesian robot stiffness is based on the Sequential Least Squares Programming (SLSQP) algorithm, which presents an expansion of the quadratic programming algorithm for nonlinear functions with constraints. The method is tested in simulations for 4 DOF planar robot. Results are presented for control of the EE Cartesian stiffness initially along one axis, and then control of stiffness along both planar axis – shaping the main diagonal of the EE stiffness matrix.},
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Control of robot end-effector (EE) Cartesian stiffness matrix (or the whole mechanical impedance) is still a challenging open issue in physical humanrobot interaction (pHRI). This paper presents an optimization approach for shaping the robot EE Cartesian stiffness. This research targets collaborative robots with intrinsic compliance – serial elastic actuators (SEAs). Although robots with SEAs have constant joint stiffness, task redundancy (null-space) for a specific task could be used for robot reconfiguration and shaping the stiffness matrix while still keeping the EE position unchanged. The method proposed in this paper to investigate null-space reconfiguration's influence on Cartesian robot stiffness is based on the Sequential Least Squares Programming (SLSQP) algorithm, which presents an expansion of the quadratic programming algorithm for nonlinear functions with constraints. The method is tested in simulations for 4 DOF planar robot. Results are presented for control of the EE Cartesian stiffness initially along one axis, and then control of stiffness along both planar axis – shaping the main diagonal of the EE stiffness matrix.
Brecelj, Tilen; Petric, Tadej
Angular Dependency of the Zero Moment Point Proceedings Article
In: Zeghloul, Said; Laribi, Med Amine; Sandoval, Juan (Ed.): Advances in Service and Industrial Robotics. RAAD 2021, pp. 135–144, Springer International Publishing, Cham, 2021, ISBN: 978-3-030-75259-0.
@inproceedings{10.1007/978-3-030-75259-0_15,
title = {Angular Dependency of the Zero Moment Point},
author = {Tilen Brecelj and Tadej Petric},
editor = {Said Zeghloul and Med Amine Laribi and Juan Sandoval},
doi = {https://doi.org/10.1007/978-3-030-75259-0_15},
isbn = {978-3-030-75259-0},
year = {2021},
date = {2021-01-01},
booktitle = {Advances in Service and Industrial Robotics. RAAD 2021},
pages = {135--144},
publisher = {Springer International Publishing},
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series = {Mechanisms and Machine Science},
abstract = {In this paper, the standard definition of the zero moment point as a location on the ground is extended to its angular definition around the center of mass of a humanoid robot. This new definition provides a more general way of expressing this stability parameter and enables its wider use, as this way it can be located anywhere on a specific line passing through the system's center of mass. The angular expression of the zero moment point is examined and compared with the zero moment point of the linear inverted pendulum model, which can be obtained with some simplifications of its angular definition. For a better understanding of the angular dependence of the zero moment point with respect to the accelerations of the humanoid's center of mass in the horizontal and vertical directions, some computer simulations are presented. Finally, a real scenario of humanoid postural stability is presented and discussed, in which the advantages of the angular definition of the zero moment point can be seen.},
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In this paper, the standard definition of the zero moment point as a location on the ground is extended to its angular definition around the center of mass of a humanoid robot. This new definition provides a more general way of expressing this stability parameter and enables its wider use, as this way it can be located anywhere on a specific line passing through the system's center of mass. The angular expression of the zero moment point is examined and compared with the zero moment point of the linear inverted pendulum model, which can be obtained with some simplifications of its angular definition. For a better understanding of the angular dependence of the zero moment point with respect to the accelerations of the humanoid's center of mass in the horizontal and vertical directions, some computer simulations are presented. Finally, a real scenario of humanoid postural stability is presented and discussed, in which the advantages of the angular definition of the zero moment point can be seen.
Leskovar, Rebeka Kropivšek; Petrič, Tadej
Humans Prefer Collaborating with a Robot Who Leads in a Physical Human-Robot Collaboration Scenario Proceedings Article
In: 2021 20th International Conference on Advanced Robotics (ICAR), pp. 935-941, 2021.
@inproceedings{9659365,
title = {Humans Prefer Collaborating with a Robot Who Leads in a Physical Human-Robot Collaboration Scenario},
author = {Rebeka Kropivšek Leskovar and Tadej Petrič},
doi = {10.1109/ICAR53236.2021.9659365},
year = {2021},
date = {2021-01-01},
booktitle = {2021 20th International Conference on Advanced Robotics (ICAR)},
pages = {935-941},
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Mišković, Luka; Dežman, Miha; Petrić, Tadej
Modular quasi-passive mechanism for energy storage applications: towards lightweight high-performance exoskeleton Proceedings Article
In: 2021 20th International Conference on Advanced Robotics (ICAR), pp. 588-593, 2021.
@inproceedings{9659353,
title = {Modular quasi-passive mechanism for energy storage applications: towards lightweight high-performance exoskeleton},
author = {Luka Mišković and Miha Dežman and Tadej Petrić},
doi = {10.1109/ICAR53236.2021.9659353},
year = {2021},
date = {2021-01-01},
booktitle = {2021 20th International Conference on Advanced Robotics (ICAR)},
pages = {588-593},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2020
Rebeka, Kropivšek Leskovar; Petrič, Tadej
Turing test of motor ability perception in physical collaboration between a human and an intelligent robot agent Proceedings Article
In: Andrej Žemva, Trost (Ed.): Proceedings of the Twenty-ninth International Electrotechnical and Computer Science Conference ERK 2020, 2020, ISBN: 2591-0442, 29.
@inproceedings{kropivsek2020,
title = {Turing test of motor ability perception in physical collaboration between a human and an intelligent robot agent},
author = {Rebeka, Kropivšek Leskovar and Tadej Petrič},
editor = {Žemva, Andrej, Trost, Andrej},
url = {http://cobotat.ijs.si/wp-content/uploads/2021/04/ERK2020.pdf},
isbn = {2591-0442, 29},
year = {2020},
date = {2020-09-21},
booktitle = {Proceedings of the Twenty-ninth International Electrotechnical and Computer Science Conference ERK 2020},
volume = {ERK 2020},
abstract = {In this paper we propose a novel robot control method for human-robot collaboration tasks that takes into account the leader-follower relationship found in human interactions. Taking into account the leader-follower dynamics, learnt during a study on human-human collaboration, the control method replicates human behaviour when performing collaborative tasks. The performance of the proposed control method was evaluated using a 2D reaching task where we compared task performance between individual tasks, tasks in collaboration with a human and tasks in collaboration with a robot. The subjects in the evaluation were asked to grade their perceived task load for each experiment as well as specify if they thought they performed the task alone, with a robot or with a human partner as a Turing test to determine whether the subjects were able to distinct between a robot and a human partner. The results of the evaluation showed, that the robot control method is capable of replicating human behavior to benefit overall task performance of the subject in collaboration, however it is not capable of replicating this behaviour to the degree that the subject in collaboration would not be able distinct whether they were collaborating with a robot or a human partner. },
keywords = {},
pubstate = {published},
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In this paper we propose a novel robot control method for human-robot collaboration tasks that takes into account the leader-follower relationship found in human interactions. Taking into account the leader-follower dynamics, learnt during a study on human-human collaboration, the control method replicates human behaviour when performing collaborative tasks. The performance of the proposed control method was evaluated using a 2D reaching task where we compared task performance between individual tasks, tasks in collaboration with a human and tasks in collaboration with a robot. The subjects in the evaluation were asked to grade their perceived task load for each experiment as well as specify if they thought they performed the task alone, with a robot or with a human partner as a Turing test to determine whether the subjects were able to distinct between a robot and a human partner. The results of the evaluation showed, that the robot control method is capable of replicating human behavior to benefit overall task performance of the subject in collaboration, however it is not capable of replicating this behaviour to the degree that the subject in collaboration would not be able distinct whether they were collaborating with a robot or a human partner.
Petrič, Tadej; Jamšek, Marko; Babič, Jan
Exoskeleton Control Based on Network of Stable Heteroclinic Channels (SHC) Combined with Gaussian Mixture Models (GMM) Proceedings Article
In: Lenarčič, Jadran; Siciliano, Bruno (Ed.): pp. 341–348, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-50975-0.
@inproceedings{petric2020,
title = {Exoskeleton Control Based on Network of Stable Heteroclinic Channels (SHC) Combined with Gaussian Mixture Models (GMM)},
author = {Tadej Petrič and Marko Jamšek and Jan Babič},
editor = {Jadran Lenarčič and Bruno Siciliano},
url = {https://doi.org/10.1007/978-3-030-50975-0_42},
isbn = {978-3-030-50975-0},
year = {2020},
date = {2020-07-18},
pages = {341--348},
publisher = {Springer International Publishing},
address = {Cham},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Jamšek, Marko; Petrič, Tadej; Babič, Jan
Gaussian Mixture Models for Control of Quasi-Passive Spinal Exoskeletons Journal Article
In: Sensors, vol. 20, no. 9, 2020, ISSN: 1424-8220.
@article{Jamsek2020,
title = {Gaussian Mixture Models for Control of Quasi-Passive Spinal Exoskeletons},
author = {Marko Jamšek and Tadej Petrič and Jan Babič},
url = {https://www.mdpi.com/1424-8220/20/9/2705},
doi = {10.3390/s20092705},
issn = {1424-8220},
year = {2020},
date = {2020-01-01},
journal = {Sensors},
volume = {20},
number = {9},
keywords = {},
pubstate = {published},
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Žlajpah, Leon; Petrič, Tadej
Generation of Smooth Cartesian Paths Using Radial Basis Functions Proceedings Article
In: Zeghloul, Said; Laribi, Med Amine; Arevalo, Juan Sebastian Sandoval (Ed.): Advances in Service and Industrial Robotics, pp. 171–180, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-48989-2.
@inproceedings{10.1007/978-3-030-48989-2_19,
title = {Generation of Smooth Cartesian Paths Using Radial Basis Functions},
author = {Leon Žlajpah and Tadej Petrič},
editor = {Said Zeghloul and Med Amine Laribi and Juan Sebastian Sandoval Arevalo},
isbn = {978-3-030-48989-2},
year = {2020},
date = {2020-01-01},
booktitle = {Advances in Service and Industrial Robotics},
pages = {171--180},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {In this paper, we consider the problem of generating smooth Cartesian paths for robots passing through a sequence of waypoints. For interpolation between waypoints we propose to use radial basis functions (RBF). First, we describe RBF based on Gaussian kernel functions and how the weights are calculated. The path generation considers also boundary conditions for velocity and accelerations. Then we present how RBF parameters influence the shape of the generated path. The proposed RBF method is compared with paths generated by a spline and linear interpolation. The results demonstrate the advantages of the proposed method, which is offering a good alternative to generate smooth Cartesian paths.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
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In this paper, we consider the problem of generating smooth Cartesian paths for robots passing through a sequence of waypoints. For interpolation between waypoints we propose to use radial basis functions (RBF). First, we describe RBF based on Gaussian kernel functions and how the weights are calculated. The path generation considers also boundary conditions for velocity and accelerations. Then we present how RBF parameters influence the shape of the generated path. The proposed RBF method is compared with paths generated by a spline and linear interpolation. The results demonstrate the advantages of the proposed method, which is offering a good alternative to generate smooth Cartesian paths.
Petrič, Tadej; Žlajpah, Leon
Combining Virtual and Physical Guides for Autonomous In-Contact Path Adaptation Proceedings Article
In: Zeghloul, Said; Laribi, Med Amine; Arevalo, Juan Sebastian Sandoval (Ed.): Advances in Service and Industrial Robotics, pp. 181–189, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-48989-2.
@inproceedings{10.1007/978-3-030-48989-2_20,
title = {Combining Virtual and Physical Guides for Autonomous In-Contact Path Adaptation},
author = {Tadej Petrič and Leon Žlajpah},
editor = {Said Zeghloul and Med Amine Laribi and Juan Sebastian Sandoval Arevalo},
url = {http://cobotat.ijs.si/wp-content/uploads/2021/04/Raad2020.pdf},
isbn = {978-3-030-48989-2},
year = {2020},
date = {2020-01-01},
booktitle = {Advances in Service and Industrial Robotics},
pages = {181--189},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {Several approaches exist for learning and control of robot behaviors in physical human-robot interaction (PHRI) scenarios. One of these is the approach based on virtual guides which actively helps to guide the user. Such a system enables guiding users towards preferred movement directions or prevents them to enter into a prohibited zone. Despite being shown that such a framework works well in physical contact with humans, the efficient interaction with the environment is still limited. Within the virtual guide framework, the environment is considered as a physical guide, for example, a table is a plane that prevents the robot to penetrate through. To mitigate these limits we introduce and evaluate the means of autonomous path adaptation through interaction with physical guides, which essentially means merging virtual and physical guides. The virtual guide framework was extended by introducing an algorithm which partially modifies the virtual guides online. The path updates are now based on the interactive force measurements and essentially improves the virtual guides to match them with the actual physical guides.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
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Several approaches exist for learning and control of robot behaviors in physical human-robot interaction (PHRI) scenarios. One of these is the approach based on virtual guides which actively helps to guide the user. Such a system enables guiding users towards preferred movement directions or prevents them to enter into a prohibited zone. Despite being shown that such a framework works well in physical contact with humans, the efficient interaction with the environment is still limited. Within the virtual guide framework, the environment is considered as a physical guide, for example, a table is a plane that prevents the robot to penetrate through. To mitigate these limits we introduce and evaluate the means of autonomous path adaptation through interaction with physical guides, which essentially means merging virtual and physical guides. The virtual guide framework was extended by introducing an algorithm which partially modifies the virtual guides online. The path updates are now based on the interactive force measurements and essentially improves the virtual guides to match them with the actual physical guides.
Leskovar, Rebeka Kropivšek; Čamernik, Jernej; Petrič, Tadej
Dyadic Human-Human Interactions in Reaching Tasks: Fitts' Law for Two Proceedings Article
In: Zeghloul, Said; Laribi, Med Amine; Arevalo, Juan Sebastian Sandoval (Ed.): Advances in Service and Industrial Robotics, pp. 199–207, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-48989-2.
@inproceedings{10.1007/978-3-030-48989-2_22,
title = {Dyadic Human-Human Interactions in Reaching Tasks: Fitts' Law for Two},
author = {Rebeka Kropivšek Leskovar and Jernej Čamernik and Tadej Petrič},
editor = {Said Zeghloul and Med Amine Laribi and Juan Sebastian Sandoval Arevalo},
url = {http://cobotat.ijs.si/wp-content/uploads/2021/04/RAAD2020_Rkl_Final.pdf},
isbn = {978-3-030-48989-2},
year = {2020},
date = {2020-01-01},
booktitle = {Advances in Service and Industrial Robotics},
pages = {199--207},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {In this paper we examine physical collaboration between two individuals using a dual-arm robot as a haptic interface. First, we design a haptic controller based on a virtual dynamic model of the robot arms. Then, we analyse dyadic human-human collaboration with a reaching task on a 2D plane, where the distance and size of the target changed randomly from a pool of nine reachable positions and sizes. Each subject performed the task individually and linked through the guided robot arms with a virtual model to perform the same task in collaboration. We evaluated both, individual and collaborative performances, based on Fitts' law, which describes the relation between the speed of motion and its accuracy. The results show that the Fitts' law applies to both, individual and collaborative tasks, with their performance improving when in collaboration.},
keywords = {},
pubstate = {published},
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In this paper we examine physical collaboration between two individuals using a dual-arm robot as a haptic interface. First, we design a haptic controller based on a virtual dynamic model of the robot arms. Then, we analyse dyadic human-human collaboration with a reaching task on a 2D plane, where the distance and size of the target changed randomly from a pool of nine reachable positions and sizes. Each subject performed the task individually and linked through the guided robot arms with a virtual model to perform the same task in collaboration. We evaluated both, individual and collaborative performances, based on Fitts' law, which describes the relation between the speed of motion and its accuracy. The results show that the Fitts' law applies to both, individual and collaborative tasks, with their performance improving when in collaboration.
Lukić, Branko; Jovanović, Kosta; Knežević, Nikola; Žlajpah, Leon; Petrič, Tadej
Maximizing the End-Effector Cartesian Stiffness Range for Kinematic Redundant Robot with Compliance Proceedings Article
In: Zeghloul, Said; Laribi, Med Amine; Arevalo, Juan Sebastian Sandoval (Ed.): Advances in Service and Industrial Robotics, pp. 208–217, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-48989-2.
@inproceedings{10.1007/978-3-030-48989-2_23,
title = {Maximizing the End-Effector Cartesian Stiffness Range for Kinematic Redundant Robot with Compliance},
author = {Branko Lukić and Kosta Jovanović and Nikola Knežević and Leon Žlajpah and Tadej Petrič},
editor = {Said Zeghloul and Med Amine Laribi and Juan Sebastian Sandoval Arevalo},
isbn = {978-3-030-48989-2},
year = {2020},
date = {2020-01-01},
booktitle = {Advances in Service and Industrial Robotics},
pages = {208--217},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {Compliant robots with constant joint stiffness (Serial Elastic Actuators - SEA), on the contrary to ones with variable joint stiffness (Variable Stiffness Actuators -- VSA), have limited capabilities for modulating robot mechanical impedance in the interaction task. However, in the case of kinematic redundancy in specific tasks, robots can exploit the null space to adjust End-Effector (EE) Cartesian stiffness. Thus, prior knowledge of the task path or the operational workspace can be used to pre-compute joint stiffness that can enable maximal ratio between maximal and minimal stiffness of the robot's EE during the task execution, and therefore shape achievable EE stiffness to best fit the task execution. In that light, this paper elaborates on the preselection of joint stiffnesses which influences the achievable robot's Cartesian stiffness in a specific task. Besides optimizing the available operational EE stiffness, by pre-computed joint stiffness values, the robot will be able to adapt better to specific tasks and provide a better framework for safe and efficient physical human-robot interaction. The paper presents an approach to the selection of predefined joint stiffness values of the 7-DOFs KUKA LWR, where joint stiffness is achieved/emulated with torque feedback. In the simulation experiments, the approach is depicted in the preselection of two joint stiffness values within the prescribed range, while other joint stiffness is set constant.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Compliant robots with constant joint stiffness (Serial Elastic Actuators - SEA), on the contrary to ones with variable joint stiffness (Variable Stiffness Actuators -- VSA), have limited capabilities for modulating robot mechanical impedance in the interaction task. However, in the case of kinematic redundancy in specific tasks, robots can exploit the null space to adjust End-Effector (EE) Cartesian stiffness. Thus, prior knowledge of the task path or the operational workspace can be used to pre-compute joint stiffness that can enable maximal ratio between maximal and minimal stiffness of the robot's EE during the task execution, and therefore shape achievable EE stiffness to best fit the task execution. In that light, this paper elaborates on the preselection of joint stiffnesses which influences the achievable robot's Cartesian stiffness in a specific task. Besides optimizing the available operational EE stiffness, by pre-computed joint stiffness values, the robot will be able to adapt better to specific tasks and provide a better framework for safe and efficient physical human-robot interaction. The paper presents an approach to the selection of predefined joint stiffness values of the 7-DOFs KUKA LWR, where joint stiffness is achieved/emulated with torque feedback. In the simulation experiments, the approach is depicted in the preselection of two joint stiffness values within the prescribed range, while other joint stiffness is set constant.
Petrič, Tadej
Phase-Synchronized Learning of Periodic Compliant Movement Primitives (P-CMPs) Journal Article
In: Frontiers in Neurorobotics, vol. 14, pp. 90, 2020, ISSN: 1662-5218.
@article{10.3389/fnbot.2020.599889,
title = {Phase-Synchronized Learning of Periodic Compliant Movement Primitives (P-CMPs)},
author = {Tadej Petrič},
url = {https://www.frontiersin.org/article/10.3389/fnbot.2020.599889
http://cobotat.ijs.si/wp-content/uploads/2021/04/Petric_2020_Phase-Synchronized-Learning-of-Periodic-Compliant-Movement-Primitives-P-CMPs_Frontiers-in-Neurorobotics.pdf},
doi = {10.3389/fnbot.2020.599889},
issn = {1662-5218},
year = {2020},
date = {2020-01-01},
journal = {Frontiers in Neurorobotics},
volume = {14},
pages = {90},
abstract = {Autonomous trajectory and torque profile synthesis through modulation and generalization require a database of motion with accompanying dynamics, which is typically difficult and time-consuming to obtain. Inspired by adaptive control strategies, this paper presents a novel method for learning and synthesizing Periodic Compliant Movement Primitives (P-CMPs). P-CMPs combine periodic trajectories encoded as Periodic Dynamic Movement Primitives (P-DMPs) with accompanying task-specific Periodic Torque Primitives (P-TPs). The state-of-the-art approach requires to learn TPs for each variation of the task, e.g., modulation of frequency. Comparatively, in this paper, we propose a novel P-TPs framework, which is both frequency and phase-dependent. Thereby, the executed P-CMPs can be easily modulated, and consequently, the learning rate can be improved. Moreover, both the kinematic and the dynamic profiles are parameterized, thus enabling the representation of skills using corresponding parameters. The proposed framework was evaluated on two robot systems, i.e., Kuka LWR-4 and Franka Emika Panda. The evaluation of the proposed approach on a Kuka LWR-4 robot performing a swinging motion and on Franka Emika Panda performing an exercise for elbow rehabilitation shows fast P-CTPs acquisition and accurate and compliant motion in real-world scenarios.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Autonomous trajectory and torque profile synthesis through modulation and generalization require a database of motion with accompanying dynamics, which is typically difficult and time-consuming to obtain. Inspired by adaptive control strategies, this paper presents a novel method for learning and synthesizing Periodic Compliant Movement Primitives (P-CMPs). P-CMPs combine periodic trajectories encoded as Periodic Dynamic Movement Primitives (P-DMPs) with accompanying task-specific Periodic Torque Primitives (P-TPs). The state-of-the-art approach requires to learn TPs for each variation of the task, e.g., modulation of frequency. Comparatively, in this paper, we propose a novel P-TPs framework, which is both frequency and phase-dependent. Thereby, the executed P-CMPs can be easily modulated, and consequently, the learning rate can be improved. Moreover, both the kinematic and the dynamic profiles are parameterized, thus enabling the representation of skills using corresponding parameters. The proposed framework was evaluated on two robot systems, i.e., Kuka LWR-4 and Franka Emika Panda. The evaluation of the proposed approach on a Kuka LWR-4 robot performing a swinging motion and on Franka Emika Panda performing an exercise for elbow rehabilitation shows fast P-CTPs acquisition and accurate and compliant motion in real-world scenarios.
2019
Žlajpah, L.; Petrič, T.
Unified Virtual Guides Framework for Path Tracking Tasks Journal Article
In: Robotica, pp. 1–17, 2019.
@article{zlajpah2019_robotica,
title = {Unified Virtual Guides Framework for Path Tracking Tasks},
author = {L. Žlajpah and T. Petrič},
doi = {10.1017/S0263574719000973},
year = {2019},
date = {2019-08-13},
urldate = {2019-08-13},
journal = {Robotica},
pages = {1–17},
publisher = {Cambridge University Press},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Babič, J.; Petrič, T.; Mombaur, K.; Kingma, I.; Bornmann, J.; González-Vargas, J.; Baltrusch, S.; Šarabon, N.; Houdijk, H.
SPEXOR: Design and development of passive spinal exoskeletal robot for low back pain prevention and vocational reintegration Journal Article
In: SN Applied Sciences, vol. 1, no. 3, pp. 262, 2019, ISSN: 2523-3971.
@article{Babic2019,
title = {SPEXOR: Design and development of passive spinal exoskeletal robot for low back pain prevention and vocational reintegration},
author = {J. Babič and T. Petrič and K. Mombaur and I. Kingma and J. Bornmann and J. González-Vargas and S. Baltrusch and N. Šarabon and H. Houdijk},
doi = {10.1007/s42452-019-0266-1},
issn = {2523-3971},
year = {2019},
date = {2019-02-23},
journal = {SN Applied Sciences},
volume = {1},
number = {3},
pages = {262},
abstract = {The objective of SPEXOR project is to address low back pain as one of the most appealing health problems of the modern society by creating a body of scientific and technological knowledge in the multidisciplinary areas of biomechanics, robotics, and computer science that will lead to technologies for low back pain prevention. In this paper we provide an overview of the current state-of-art of SPEXOR that the consortium achieved in the first twenty-four months of the project. After introducing the rationale, we describe the biomechanics of low back pain intervention, development of the musculoskeletal stress monitoring for assessment of neuromuscular trunk functions, modeling and optimization of the interaction of spinal exoskeleton with the human body, electromechanical design and development of the passive spinal exoskeleton and its control, and finally the end-user evaluation of the functional effects, usability and satisfaction.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The objective of SPEXOR project is to address low back pain as one of the most appealing health problems of the modern society by creating a body of scientific and technological knowledge in the multidisciplinary areas of biomechanics, robotics, and computer science that will lead to technologies for low back pain prevention. In this paper we provide an overview of the current state-of-art of SPEXOR that the consortium achieved in the first twenty-four months of the project. After introducing the rationale, we describe the biomechanics of low back pain intervention, development of the musculoskeletal stress monitoring for assessment of neuromuscular trunk functions, modeling and optimization of the interaction of spinal exoskeleton with the human body, electromechanical design and development of the passive spinal exoskeleton and its control, and finally the end-user evaluation of the functional effects, usability and satisfaction.
Petrič, T.; Gams, A.
Task Space Torque Profile Adaptations for Dynamical Human-Robot Motion Transfer Proceedings Article
In: pp. 44–52, Springer International Publishing, Cham, 2019, ISBN: 978-3-030-00232-9.
@inproceedings{Petric2019,
title = {Task Space Torque Profile Adaptations for Dynamical Human-Robot Motion Transfer},
author = {T. Petrič and A. Gams},
isbn = {978-3-030-00232-9},
year = {2019},
date = {2019-01-01},
pages = {44--52},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {Motion transfer from a human to a robot implies accurate tracking of desired, demonstrated trajectories. However, direct imitation of joint position trajectories might not result in similar behavior of the robot and the human, because they have different kinematic and dynamic properties, i.e., different embodiment. To avoid the correspondence problem, the demonstrated trajectories need to be somehow adapted. In this paper we go beyond simple imitation, but we show how the torque profiles that should execute the demonstrated position trajectories are being learned in a manner that preserves the correspondence. Thus, position trajectories are modified from the demonstration and, furthermore, the robot executes the motion that preserves correspondence in a compliant manner. Because it is compliant, the robot is safer for the nearby person or environment, as potential unforeseen collisions will result in lower impact forces. We show the results of motion transfer of squatting from a human to a simulated CoMaN humanoid robot.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Motion transfer from a human to a robot implies accurate tracking of desired, demonstrated trajectories. However, direct imitation of joint position trajectories might not result in similar behavior of the robot and the human, because they have different kinematic and dynamic properties, i.e., different embodiment. To avoid the correspondence problem, the demonstrated trajectories need to be somehow adapted. In this paper we go beyond simple imitation, but we show how the torque profiles that should execute the demonstrated position trajectories are being learned in a manner that preserves the correspondence. Thus, position trajectories are modified from the demonstration and, furthermore, the robot executes the motion that preserves correspondence in a compliant manner. Because it is compliant, the robot is safer for the nearby person or environment, as potential unforeseen collisions will result in lower impact forces. We show the results of motion transfer of squatting from a human to a simulated CoMaN humanoid robot.
Žlajpah, L.; Petrič, T.
Virtual Guides for Redundant Robots Using Admittance Control for Path Tracking Tasks Proceedings Article
In: pp. 13–23, Springer International Publishing, Cham, 2019, ISBN: 978-3-030-00232-9.
@inproceedings{10.1007/978-3-030-00232-9_2,
title = {Virtual Guides for Redundant Robots Using Admittance Control for Path Tracking Tasks},
author = {L. Žlajpah and T. Petrič},
isbn = {978-3-030-00232-9},
year = {2019},
date = {2019-01-01},
pages = {13--23},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {Virtual guides are used in human-robot cooperation to support a human performing manipulation tasks. They can act as guidance constrains to assist the user to move in the preferred direction or along desired path, or as forbidden-region constraint which prevent him to move into restricted region of the robot workspace. In this paper we proposed a novel framework that unifies virtual guides using virtual robot approach, which is represented with the admittance control, where a broad class of virtual guides and constraints can be implemented. The dynamic properties and the constraints of the virtual robot can be defined using three sets of parameters and variables: desired motion variables, dynamic parameters (stiffness, damping and inertia) and dead-zones. To validate the approach we implemented it on a KUKA LWR robot for the Buzz-Wire tasks, where the goal is to move a ring along a curved wire.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Virtual guides are used in human-robot cooperation to support a human performing manipulation tasks. They can act as guidance constrains to assist the user to move in the preferred direction or along desired path, or as forbidden-region constraint which prevent him to move into restricted region of the robot workspace. In this paper we proposed a novel framework that unifies virtual guides using virtual robot approach, which is represented with the admittance control, where a broad class of virtual guides and constraints can be implemented. The dynamic properties and the constraints of the virtual robot can be defined using three sets of parameters and variables: desired motion variables, dynamic parameters (stiffness, damping and inertia) and dead-zones. To validate the approach we implemented it on a KUKA LWR robot for the Buzz-Wire tasks, where the goal is to move a ring along a curved wire.
Petrič, T.; Peternel, L.; Morimoto, J.; Babič, J.
Assistive Arm-Exoskeleton Control Based on Human Muscular Manipulability Journal Article
In: Frontiers in Neurorobotics, vol. 13, pp. 30, 2019, ISSN: 1662-5218.
@article{10.3389/fnbot.2019.00030,
title = {Assistive Arm-Exoskeleton Control Based on Human Muscular Manipulability},
author = {T. Petrič and L. Peternel and J. Morimoto and J. Babič},
doi = {10.3389/fnbot.2019.00030},
issn = {1662-5218},
year = {2019},
date = {2019-01-01},
journal = {Frontiers in Neurorobotics},
volume = {13},
pages = {30},
abstract = {This paper introduces a novel control framework for an arm exoskeleton that takes into account force of the human arm. In contrast to the conventional exoskeleton controllers where the assistance is provided without considering the human arm biomechanical force manipulability properties, we propose a control approach based on the arm muscular manipulability. The proposed control framework essentially reshapes the anisotropic force manipulability into the endpoint force manipulability that is invariant with respect to the direction in the entire workspace of the arm. This allows users of the exoskeleton to perform tasks effectively in the whole range of the workspace, even in areas that are normally unsuitable due to the low force manipulability of the human arm. We evaluated the proposed control framework with real robot experiments where subjects wearing an arm exoskeleton were asked to move a weight between several locations. The results show that the proposed control framework does not affect the normal movement behavior of the users while effectively reduces user effort in the area of low manipulability. Particularly, the proposed approach augments the human arm force manipulability to execute tasks equally well in the entire workspace of the arm.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper introduces a novel control framework for an arm exoskeleton that takes into account force of the human arm. In contrast to the conventional exoskeleton controllers where the assistance is provided without considering the human arm biomechanical force manipulability properties, we propose a control approach based on the arm muscular manipulability. The proposed control framework essentially reshapes the anisotropic force manipulability into the endpoint force manipulability that is invariant with respect to the direction in the entire workspace of the arm. This allows users of the exoskeleton to perform tasks effectively in the whole range of the workspace, even in areas that are normally unsuitable due to the low force manipulability of the human arm. We evaluated the proposed control framework with real robot experiments where subjects wearing an arm exoskeleton were asked to move a weight between several locations. The results show that the proposed control framework does not affect the normal movement behavior of the users while effectively reduces user effort in the area of low manipulability. Particularly, the proposed approach augments the human arm force manipulability to execute tasks equally well in the entire workspace of the arm.
Petrič, T.; Žlajpah, L.
On-line Adaption of Virtual Guides Through Physical Interaction Proceedings Article
In: Berns, Karsten; Görges, Daniel (Ed.): Advances in Service and Industrial Robotics, pp. 293–300, Springer International Publishing, Cham, 2019, ISBN: 978-3-030-19648-6.
@inproceedings{10.1007/978-3-030-19648-6_34,
title = {On-line Adaption of Virtual Guides Through Physical Interaction},
author = {T. Petrič and L. Žlajpah},
editor = {Karsten Berns and Daniel Görges},
isbn = {978-3-030-19648-6},
year = {2019},
date = {2019-01-01},
booktitle = {Advances in Service and Industrial Robotics},
pages = {293--300},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {Virtual guide framework allows efficient learning and control of complex robot behaviors in human-robot interaction scenarios. The framework can help to guide users to move in a predefined direction or prevent them to enter a forbidden-region. As such, the framework also allows efficient modulation of regions by changing of parameters. In this paper, we introduce and evaluate the means of adapting path parameters through physical interaction. The main goal was to introduce an algorithm into a virtual guide framework which can partially modify the path trajectories. The path updates are based on physical interaction and allow human intervention to improve the task performance. This enables to update the path trajectory only where needed and hence, to bypass the need to re-learn the whole trajectory from scratch. Since virtual guides are also active while learning, the required effort from the user is lower compared to the required effort when the user is teaching the robot with kinesthetic guidance. The effectiveness of the proposed algorithm has been demonstrated with simulation results and experiments on a KUKA LWR robot.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
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Virtual guide framework allows efficient learning and control of complex robot behaviors in human-robot interaction scenarios. The framework can help to guide users to move in a predefined direction or prevent them to enter a forbidden-region. As such, the framework also allows efficient modulation of regions by changing of parameters. In this paper, we introduce and evaluate the means of adapting path parameters through physical interaction. The main goal was to introduce an algorithm into a virtual guide framework which can partially modify the path trajectories. The path updates are based on physical interaction and allow human intervention to improve the task performance. This enables to update the path trajectory only where needed and hence, to bypass the need to re-learn the whole trajectory from scratch. Since virtual guides are also active while learning, the required effort from the user is lower compared to the required effort when the user is teaching the robot with kinesthetic guidance. The effectiveness of the proposed algorithm has been demonstrated with simulation results and experiments on a KUKA LWR robot.
Lukić, B; Petrič, T; Žlajpah, L; Jovanović, K
KUKA LWR Robot Cartesian Stiffness Control Based on Kinematic Redundancy Proceedings Article
In: Berns, Karsten; Görges, Daniel (Ed.): Advances in Service and Industrial Robotics, pp. 310–318, Springer International Publishing, Cham, 2019, ISBN: 978-3-030-19648-6.
@inproceedings{10.1007/978-3-030-19648-6_34b,
title = {KUKA LWR Robot Cartesian Stiffness Control Based on Kinematic Redundancy},
author = {B Lukić and T Petrič and L Žlajpah and K Jovanović},
editor = {Karsten Berns and Daniel Görges},
isbn = {978-3-030-19648-6},
year = {2019},
date = {2019-01-01},
booktitle = {Advances in Service and Industrial Robotics},
pages = {310--318},
publisher = {Springer International Publishing},
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Žlajpah, L; Petrič, T
Bounded Self-motion of Functional Redundant Robots Proceedings Article
In: Berns, Karsten; Görges, Daniel (Ed.): Advances in Service and Industrial Robotics, pp. 285–292, Springer International Publishing, Cham, 2019, ISBN: 978-3-030-19648-6.
@inproceedings{Zlajpah2019_raad,
title = {Bounded Self-motion of Functional Redundant Robots},
author = {L Žlajpah and T Petrič},
editor = {Karsten Berns and Daniel Görges},
isbn = {978-3-030-19648-6},
year = {2019},
date = {2019-01-01},
booktitle = {Advances in Service and Industrial Robotics},
pages = {285--292},
publisher = {Springer International Publishing},
address = {Cham},
keywords = {},
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Jovanović, Kosta; Petrič, Tadej; Tsuji, Toshiaki; Oddo, Calogero Maria
Editorial: Human-Like Advances in Robotics: Motion, Actuation, Sensing, Cognition and Control Journal Article
In: Frontiers in Neurorobotics, vol. 13, pp. 85, 2019, ISSN: 1662-5218.
@article{10.3389/fnbot.2019.00085,
title = {Editorial: Human-Like Advances in Robotics: Motion, Actuation, Sensing, Cognition and Control},
author = {Kosta Jovanović and Tadej Petrič and Toshiaki Tsuji and Calogero Maria Oddo},
url = {https://www.frontiersin.org/article/10.3389/fnbot.2019.00085},
doi = {10.3389/fnbot.2019.00085},
issn = {1662-5218},
year = {2019},
date = {2019-01-01},
journal = {Frontiers in Neurorobotics},
volume = {13},
pages = {85},
keywords = {},
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}
2018
Petrič, T.; Gams, A.; Colasanto, L.; Ijspeert, A. J.; Ude, A.
Accelerated Sensorimotor Learning of Compliant Movement Primitives Journal Article
In: IEEE Transactions on Robotics, vol. 34, no. 6, pp. 1636-1642, 2018, ISSN: 1552-3098.
@article{8437179,
title = {Accelerated Sensorimotor Learning of Compliant Movement Primitives},
author = {T. Petrič and A. Gams and L. Colasanto and A. J. Ijspeert and A. Ude},
doi = {10.1109/TRO.2018.2861921},
issn = {1552-3098},
year = {2018},
date = {2018-12-01},
journal = {IEEE Transactions on Robotics},
volume = {34},
number = {6},
pages = {1636-1642},
abstract = {Autonomous trajectory generation through generalization requires a database of motion, which can be difficult and time consuming to obtain. In this paper, we propose a method for autonomous expansion of a database for the generation of compliant and accurate motion, achieved through the framework of compliant movement primitives (CMPs). These combine task-specific kinematic and corresponding feed-forward dynamic trajectories. The framework allows for generalization and modulation of dynamic behavior. Inspired by human sensorimotor learning abilities, we propose a novel method that can autonomously learn task-specific torque primitives (TPs) associated to given kinematic trajectories, encoded as dynamic movement primitives. The proposed algorithm is completely autonomous, and can be used to rapidly generate and expand the CMP database. Since CMPs are parameterized, statistical generalization can be used to obtain an initial TP estimate of a new CMP. Thereby, the learning rate of new CMPs can be significantly improved. The evaluation of the proposed approach on a Kuka LWR-4 robot performing a peg-in-hole task shows fast TP acquisition and accurate generalization estimates in real-world scenarios.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Autonomous trajectory generation through generalization requires a database of motion, which can be difficult and time consuming to obtain. In this paper, we propose a method for autonomous expansion of a database for the generation of compliant and accurate motion, achieved through the framework of compliant movement primitives (CMPs). These combine task-specific kinematic and corresponding feed-forward dynamic trajectories. The framework allows for generalization and modulation of dynamic behavior. Inspired by human sensorimotor learning abilities, we propose a novel method that can autonomously learn task-specific torque primitives (TPs) associated to given kinematic trajectories, encoded as dynamic movement primitives. The proposed algorithm is completely autonomous, and can be used to rapidly generate and expand the CMP database. Since CMPs are parameterized, statistical generalization can be used to obtain an initial TP estimate of a new CMP. Thereby, the learning rate of new CMPs can be significantly improved. The evaluation of the proposed approach on a Kuka LWR-4 robot performing a peg-in-hole task shows fast TP acquisition and accurate generalization estimates in real-world scenarios.
Peternel, L.; Petrič, T.; Babič, J.
Robotic assembly solution by human-in-the-loop teaching method based on real-time stiffness modulation Journal Article
In: Autonomous Robots, vol. 42, no. 1, pp. 1–17, 2018, ISSN: 1573-7527.
@article{Peternel2018,
title = {Robotic assembly solution by human-in-the-loop teaching method based on real-time stiffness modulation},
author = {L. Peternel and T. Petrič and J. Babič},
doi = {10.1007/s10514-017-9635-z},
issn = {1573-7527},
year = {2018},
date = {2018-01-01},
journal = {Autonomous Robots},
volume = {42},
number = {1},
pages = {1--17},
abstract = {We propose a novel human-in-the-loop approach for teaching robots how to solve assembly tasks in unpredictable and unstructured environments. In the proposed method the human sensorimotor system is integrated into the robot control loop though a teleoperation setup. The approach combines a 3-DoF end-effector force feedback with an interface for modulation of the robot end-effector stiffness. When operating in unpredictable and unstructured environments, modulation of limb impedance is essential in terms of successful task execution, stability and safety. We developed a novel hand-held stiffness control interface that is controlled by the motion of the human finger. A teaching approach was then used to achieve autonomous robot operation. In the experiments, we analysed and solved two part-assembly tasks: sliding a bolt fitting inside a groove and driving a self-tapping screw into a material of unknown properties. We experimentally compared the proposed method to complementary robot learning methods and analysed the potential benefits of direct stiffness modulation in the force-feedback teleoperation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We propose a novel human-in-the-loop approach for teaching robots how to solve assembly tasks in unpredictable and unstructured environments. In the proposed method the human sensorimotor system is integrated into the robot control loop though a teleoperation setup. The approach combines a 3-DoF end-effector force feedback with an interface for modulation of the robot end-effector stiffness. When operating in unpredictable and unstructured environments, modulation of limb impedance is essential in terms of successful task execution, stability and safety. We developed a novel hand-held stiffness control interface that is controlled by the motion of the human finger. A teaching approach was then used to achieve autonomous robot operation. In the experiments, we analysed and solved two part-assembly tasks: sliding a bolt fitting inside a groove and driving a self-tapping screw into a material of unknown properties. We experimentally compared the proposed method to complementary robot learning methods and analysed the potential benefits of direct stiffness modulation in the force-feedback teleoperation.
Petrič, T.; Cevzar, M.; Babič, J.
Shared Control for Human-Robot Cooperative Manipulation Tasks Proceedings Article
In: Ferraresi, Carlo; Quaglia, Giuseppe (Ed.): pp. 787–796, Springer International Publishing, Cham, 2018, ISBN: 978-3-319-61276-8.
@inproceedings{Petrič2018,
title = {Shared Control for Human-Robot Cooperative Manipulation Tasks},
author = {T. Petrič and M. Cevzar and J. Babič},
editor = {Carlo Ferraresi and Giuseppe Quaglia},
isbn = {978-3-319-61276-8},
year = {2018},
date = {2018-01-01},
pages = {787--796},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {In the past decade many studies on human motor control have investigated how humans are moving their arms. In robotics, these studies were usually used as a foundation for human-robot cooperation tasks. Nonetheless, the gap between human motor control and robot control remains challenging. In this paper we investigated, how human proprioceptive abilities could enhance performance of cooperative manipulative tasks, where humans and robots are autonomous agents coupled through physical interaction. In such setups, the robot movements are usually accurate but without the proprioceptive capabilities observed in humans. On the contrary, humans have well developed proprioceptive capabilities, but their movement accuracy is highly dependent on the speed of movement. In this paper we proposed an approach where we exploited the speed-accuracy trade-off model of a human together with the robotic partner. In this way the performance can be improved in a human-robot cooperative setup. The performance was analyzed on a task where a long object, i.e. a pipe, needs to be manipulated into a groove with different tolerances. We tested the accuracy and efficiency of performing the task. The results show that the proposed approach can successfully estimate human behavior and successfully perform the task.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In the past decade many studies on human motor control have investigated how humans are moving their arms. In robotics, these studies were usually used as a foundation for human-robot cooperation tasks. Nonetheless, the gap between human motor control and robot control remains challenging. In this paper we investigated, how human proprioceptive abilities could enhance performance of cooperative manipulative tasks, where humans and robots are autonomous agents coupled through physical interaction. In such setups, the robot movements are usually accurate but without the proprioceptive capabilities observed in humans. On the contrary, humans have well developed proprioceptive capabilities, but their movement accuracy is highly dependent on the speed of movement. In this paper we proposed an approach where we exploited the speed-accuracy trade-off model of a human together with the robotic partner. In this way the performance can be improved in a human-robot cooperative setup. The performance was analyzed on a task where a long object, i.e. a pipe, needs to be manipulated into a groove with different tolerances. We tested the accuracy and efficiency of performing the task. The results show that the proposed approach can successfully estimate human behavior and successfully perform the task.
2017
Petrič, T.; Cevzar, M.; Babič, J.
Utilizing speed-accuracy trade-off models for human-robot coadaptation during cooperative groove fitting task Proceedings Article
In: 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids), pp. 107-112, 2017, ISSN: 2164-0580.
@inproceedings{Petrič2017,
title = {Utilizing speed-accuracy trade-off models for human-robot coadaptation during cooperative groove fitting task},
author = {T. Petrič and M. Cevzar and J. Babič},
doi = {10.1109/HUMANOIDS.2017.8239544},
issn = {2164-0580},
year = {2017},
date = {2017-11-01},
booktitle = {2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)},
pages = {107-112},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Goljat, R.; Babič, J.; Petrič, T.; Peternel, L.; Morimoto, J.
Power-augmentation control approach for arm exoskeleton based on human muscular manipulability Proceedings Article
In: 2017 IEEE International Conference on Robotics and Automation (ICRA), pp. 5929-5934, 2017.
@inproceedings{Goljat2017,
title = {Power-augmentation control approach for arm exoskeleton based on human muscular manipulability},
author = {R. Goljat and J. Babič and T. Petrič and L. Peternel and J. Morimoto},
doi = {10.1109/ICRA.2017.7989698},
year = {2017},
date = {2017-05-01},
booktitle = {2017 IEEE International Conference on Robotics and Automation (ICRA)},
pages = {5929-5934},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Petrič, T.; Simpson, C. S.; Ude, A.; Ijspeert, A. J.
Hammering Does Not Fit Fitts' Law Journal Article
In: Frontiers in Computational Neuroscience, vol. 11, pp. 45, 2017, ISSN: 1662-5188.
@article{10.3389/fncom.2017.00045,
title = {Hammering Does Not Fit Fitts' Law},
author = {T. Petrič and C. S. Simpson and A. Ude and A. J. Ijspeert},
doi = {10.3389/fncom.2017.00045},
issn = {1662-5188},
year = {2017},
date = {2017-01-01},
journal = {Frontiers in Computational Neuroscience},
volume = {11},
pages = {45},
abstract = {While movement is essential to human wellbeing, we are still unable to reproduce the deftness and robustness of human movement in automatons or completely restore function to individuals with many types of motor impairment. To better understand how the human nervous system plans and controls movements, neuromechanists employ simple tasks such as upper extremity reaches and isometric force tasks. However, these simple tasks rarely consider impacts and may not capture aspects of motor control that arise from real-world complexity. Here we compared existing models of motor control with the results of a periodic targeted impact task extended from Bernstein's seminal work: hammering a nail into wood. We recorded impact forces and kinematics from 10 subjects hammering at different frequencies and with hammers with different physical properties (mass and face area). We found few statistical differences in most measures between different types of hammer, demonstrating human robustness to minor changes in dynamics. Because human motor control is thought to obey optimality principles, we also developed a feedforward optimal simulation with a neuromechanically inspired cost function that reproduces the experimental data. However, Fitts' Law, which relates movement time to distance traveled and target size, did not match our experimental data. We therefore propose a new model in which the distance moved is a logarithmic function of the time to move that yields better results (R^2 > 0.99 compared to R^2 > 0.88). These results support the argument that humans control movement in an optimal way, but suggest that Fitts' Law may not generalize to periodic impact tasks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
While movement is essential to human wellbeing, we are still unable to reproduce the deftness and robustness of human movement in automatons or completely restore function to individuals with many types of motor impairment. To better understand how the human nervous system plans and controls movements, neuromechanists employ simple tasks such as upper extremity reaches and isometric force tasks. However, these simple tasks rarely consider impacts and may not capture aspects of motor control that arise from real-world complexity. Here we compared existing models of motor control with the results of a periodic targeted impact task extended from Bernstein's seminal work: hammering a nail into wood. We recorded impact forces and kinematics from 10 subjects hammering at different frequencies and with hammers with different physical properties (mass and face area). We found few statistical differences in most measures between different types of hammer, demonstrating human robustness to minor changes in dynamics. Because human motor control is thought to obey optimality principles, we also developed a feedforward optimal simulation with a neuromechanically inspired cost function that reproduces the experimental data. However, Fitts' Law, which relates movement time to distance traveled and target size, did not match our experimental data. We therefore propose a new model in which the distance moved is a logarithmic function of the time to move that yields better results (R^2 > 0.99 compared to R^2 > 0.88). These results support the argument that humans control movement in an optimal way, but suggest that Fitts' Law may not generalize to periodic impact tasks.
2016
Petrič, T.; Goljat, R.; Babič, J.
Cooperative human-robot control based on Fitts' law Proceedings Article
In: 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), pp. 345-350, 2016, ISSN: 2164-0580.
@inproceedings{Petrič2016,
title = {Cooperative human-robot control based on Fitts' law},
author = {T. Petrič and R. Goljat and J. Babič},
doi = {10.1109/HUMANOIDS.2016.7803299},
issn = {2164-0580},
year = {2016},
date = {2016-11-01},
booktitle = {2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)},
pages = {345-350},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}