Enhancing Robot-Environment Physical Interaction via Optimal Impedance Profiles
Name
paper_impedance_learning1.pdf
Description
Accepted version
Size
4.01 MB
Format
Unknown
Checksum (MD5)
46cc586b342a6065a1e6a1c2bebd7d23
Author(s)
Averta, Giuseppe
Hogan, Neville
Date Issued
2020
Journal
Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
Publisher
IEEE
Citation
Averta, Giuseppe and Hogan, Neville. 2020. "Enhancing Robot-Environment Physical Interaction via Optimal Impedance Profiles." Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, 2020-November.
Version
Author's final manuscript
Abstract
© 2020 IEEE. Physical interaction of robots with their environment is a challenging problem because of the exchanged forces. Hybrid position/force control schemes often exhibit problems during the contact phase, whereas impedance control appears to be more simple and reliable, especially when impedance is shaped to be energetically passive. Even if recent technologies enable shaping the impedance of a robot, how best to plan impedance parameters for task execution remains an open question. In this paper we present an optimization-based approach to plan not only the robot motion but also its desired end-effector mechanical impedance. We show how our methodology is able to take into account the transition from free motion to a contact condition, typical of physical interaction tasks. Results are presented for planar and three-dimensional open-chain manipulator arms. The compositionality of mechanical impedance is exploited to deal with kinematic redundancy and multi-arm manipulation.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/BIOROB49111.2020.9224382
