Manipulability optimization for multi-arm teleoperation

Florian Kennel-Maushart, Roi Poranne, Stelian Coros

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

Abstract

Teleoperation provides a way for human operators to guide robots in situations where full autonomy is challenging or where direct human intervention is required. It can also be an important tool to teach robots in order to achieve autonomous behaviour later on. The increased availability of collaborative robot arms and Virtual Reality (VR) devices, provides ample opportunity for development of novel teleoperation methods. Since robot arms are often kinematically different from human arms, mapping human motions to a robot in real-time is not trivial. Additionally, a human operator might steer the robot arm toward singularities or its workspace limits, which can lead to undesirable behaviour. This is further accentuated for the orchestration of multiple robots. In this paper, we present a VR interface targeted to multi-arm payload manipulation, which can closely match real-time input motion. Allowing the user to manipulate the payload rather than mapping their motions to individual arms we are able to simultaneously guide multiple collaborative arms. By releasing a single rotational degree of freedom, and by using a local optimization method, we can improve each arm's manipulability index, which in turn lets us avoid kinematic singularities and workspace limitations. We apply our approach to predefined trajectories as well as real-time teleoperation on different robot arms and compare performance in terms of end-effector position error and relevant joint motion metrics.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Robotics and Automation, ICRA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3956-3962
Number of pages7
ISBN (Electronic)9781728190778
DOIs
StatePublished - 2021
Event2021 IEEE International Conference on Robotics and Automation, ICRA 2021 - Xi'an, China
Duration: 30 May 20215 Jun 2021

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2021-May
ISSN (Print)1050-4729

Conference

Conference2021 IEEE International Conference on Robotics and Automation, ICRA 2021
Country/TerritoryChina
CityXi'an
Period30/05/215/06/21

Bibliographical note

Funding Information:
1 The authors are with the Department of Computer Science, ETH, Zurich, Switzerland. florian.maushart@inf.ethz.ch; roi.poranne@inf.ethz.ch; scoros@inf.ethz.ch 2Roi Poranne is with the Department of Computer Science, University of Haifa, Haifa, Israel. roiporanne@cs.haifa.ac.il This work was supported in part by the Swiss National Science Foundation NCCR on Digital Fabrication (Agreement 51NF40-182887) and by the HILTI group.

Publisher Copyright:
© 2021 IEEE

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Manipulability optimization for multi-arm teleoperation'. Together they form a unique fingerprint.

Cite this