PhRoCiety

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

Journal Articles

End-effector Cartesian stiffness shaping - sequential least squares programming approach

Knezevic, Nikola; Lukic, Branko; Jovanovic, Kosta; Zlajpah, Leon; Petric, Tadej

End-effector Cartesian stiffness shaping - sequential least squares programming approach Journal Article

Serbian Journal of Electrical Engineering, 18 (1), pp. 1–14, 2021, ISSN: 1451-4869.

Abstract | Links | BibTeX

Phase-Synchronized Learning of Periodic Compliant Movement Primitives (P-CMPs)

Petrič, Tadej

Phase-Synchronized Learning of Periodic Compliant Movement Primitives (P-CMPs) Journal Article

Frontiers in Neurorobotics, 14 , pp. 90, 2020, ISSN: 1662-5218.

Abstract | Links | BibTeX

Inproceedings

Turing test of motor ability perception in physical collaboration between a human and an intelligent robot agent

Rebeka, Kropivšek Leskovar ; Petrič, Tadej

Turing test of motor ability perception in physical collaboration between a human and an intelligent robot agent Inproceedings

Žemva Andrej, Trost Andrej (Ed.): Proceedings of the Twenty-ninth International Electrotechnical and Computer Science Conference ERK 2020, 2020, ISBN: 2591-0442, 29.

Abstract | Links | BibTeX

Combining Virtual and Physical Guides for Autonomous In-Contact Path Adaptation

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.

Abstract | Links | BibTeX

Dyadic Human-Human Interactions in Reaching Tasks: Fitts' Law for Two

Leskovar, Rebeka Kropivšek; Čamernik, Jernej; Petrič, Tadej

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.

Abstract | Links | BibTeX

Partners

JSI Team

MembersCOBISS IDRolePeriod
Petrič Tadej30885PI2019- 2021
Nemec Bojan118Researcher2019- 2021
Brecelj Tilen37467Researcher2020- 2021
Simonič Mihael51693Researcher2019- 2021
Kropivšek Leskovar Rebeka53766Technician2019- 2021

Founding source


ARRS grant no.: N2-0130