University of Oulu

M. Suomalainen, S. Calinon, E. Pignat and V. Kyrki, "Improving dual-arm assembly by master-slave compliance," 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 8676-8682. doi: 10.1109/ICRA.2019.8793977

Improving dual-arm assembly by master-slave compliance

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Author: Suomalainen, Markku1,2; Calinon, Sylvain3; Pignat, Emmanuel3;
Organizations: 1University of Oulu, Finland
2School of Electrical Engineering, Aalto University, Finland
3Idiap Research Institute, Switzerland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019081924646
Language: English
Published: Institute of Electrical and Electronics Engineers, 2019
Publish Date: 2019-08-19
Description:

Abstract

In this paper we show how different choices regarding compliance affect a dual-arm assembly task. In addition, we present how the compliance parameters can be learned from a human demonstration. Compliant motions can be used in assembly tasks to mitigate pose errors originating from, for example, inaccurate grasping. We present analytical background and accompanying experimental results on how to choose the center of compliance to enhance the convergence region of an alignment task. Then we present the possible ways of choosing the compliant axes for accomplishing alignment in a scenario where orientation error is present. We show that an earlier presented Learning from Demonstration method can be used to learn motion and compliance parameters of an impedance controller for both manipulators. The learning requires a human demonstration with a single teleoperated manipulator only, easing the execution of demonstration and enabling usage of manipulators at difficult locations as well. Finally, we experimentally verify our claim that having both manipulators compliant in both rotation and translation can accomplish the alignment task with less total joint motions and in shorter time than moving one manipulator only. In addition, we show that the learning method produces the parameters that achieve the best results in our experiments.

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Series: IEEE International Conference on Robotics and Automation
ISSN: 2152-4092
ISSN-E: 2379-9552
ISSN-L: 2152-4092
ISBN: 978-1-5386-6027-0
ISBN Print: 978-1-5386-8176-3
Pages: 8676 - 8682
DOI: 10.1109/ICRA.2019.8793977
OADOI: https://oadoi.org/10.1109/ICRA.2019.8793977
Host publication: 2019 International Conference on Robotics and Automation (ICRA). 20-24 May 2019, Montreal, Canada
Conference: International Conference on Robotics and Automation
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This work was supported by Academy of Finland, decision 286580.
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