Collaborative Capabilities in Physical Human-Robot Interaction Scenarios
The aim of PhRoCiety is to advance cognitive understanding and the current control about cooperative and robust multi-contact physical interaction between multiple agents, where agents are humans or robots. PhRoCiety will go beyond traditional approaches by: (1) proposing novel control methodologies for performing cooperative tasks with multiple agents in physical human-robot or robot-robot interaction scenarios; (2) combining cognitive learning and physical interaction with predictable and unpredictable events; (3) validating theoretical advances in real-world physical interactive scenarios.
Firstly, PhRoCiety will advance state-of-the-art in the way robots learn and perform cooperative tasks, by developing new tools for learning predictive models of human dynamic behavior in collaborative scenarios. Here the aim is to study neuromechanical parameters of human-human collaborative behaviors.
Secondly, PhRoCiety will propose a novel control framework that will innovate the robotic technology for assisting humans performing physical collaborative tasks. By measuring and modeling human dynamics in human-human collaborative setups, PhRoCiety will advance the state-of-the art in autonomous robot companions that interact with humans to provide assistance, work alongside with humans as peers, learn from humans as apprentices, and foster more engaging physical interaction between them.
Thirdly, another achievement of PhRoCiety will be the validation of methods in real-world scenarios. The evaluations will show robots exploiting cooperative partnership with humans for cognitive learning and utilizing assistive physical interaction.
Gener al control structure and project’s research objectives in a physical human robot interaction scenario.
Publications
2020
Petrič, Tadej; Žlajpah, Leon
Combining Virtual and Physical Guides for Autonomous In-Contact Path Adaptation Inproceedings
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},
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}
}
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.
Dyadic Human-Human Interactions in Reaching Tasks: Fitts' Law for Two Inproceedings
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},
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},
tppubtype = {inproceedings}
}
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.
