Improving dual-arm assembly by master-slave compliance

Markku Suomalainen, Sylvain Calinon, Emmanuel Pignat, Ville Kyrki

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

3 Citations (Scopus)
73 Downloads (Pure)


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.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Robotics and Automation, ICRA 2019
Number of pages7
ISBN (Electronic)9781538660263
Publication statusPublished - 1 May 2019
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Robotics and Automation - Montreal, Canada
Duration: 20 May 201924 May 2019

Publication series

NameIEEE International Conference on Robotics and Automation
ISSN (Print)2152-4092
ISSN (Electronic)2379-9552


ConferenceIEEE International Conference on Robotics and Automation
Abbreviated titleICRA


  • Task analysis
  • Manipulators
  • Tools
  • Jamming
  • Wrist
  • Trajectory


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