Publications

@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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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},

tppubtype = {article}

}

@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}

}

@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}

}

@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},

tppubtype = {article}

}

@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 = {},

pubstate = {published},

tppubtype = {article}

}

@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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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 = {},

pubstate = {published},

tppubtype = {article}

}

@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 = {},

pubstate = {published},

tppubtype = {article}

}

@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 = {},

pubstate = {published},

tppubtype = {article}

}

@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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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},

tppubtype = {article}

}

@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}

}

@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}

}

@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}

}

@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.},

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pubstate = {published},

tppubtype = {article}

}

@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 = {},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@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}

}

@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}

}