Online Optimal Impedance Planning for Legged Robots

Franco Angelini, Guiyang Xin, Wouter Wolfslag, Carlo Tiseo, Michael Mistry, Manolo Garabini, Antonio Bicchi, Sethu Vijayakumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Real world applications require robots to operate in unstructured environments. This kind of scenarios may lead to unexpected environmental contacts or undesired interactions, which may harm people or impair the robot. Adjusting the behavior of the system through impedance control techniques is an effective solution to these problems. However, selecting an adequate impedance is not a straightforward process. Normally, robot users manually tune the controller gains with trial and error methods. This approach is generally slow and requires practice. Moreover, complex tasks may require different impedance during different phases of the task. This paper introduces an optimization algorithm for online planning of the Cartesian robot impedance to adapt to changes in the task, robot configuration, expected disturbances, external environment and desired performance, without employing any direct force measurements. We provide an analytical solution leveraging the mass-spring-damper behavior that is conferred to the robot body by the Cartesian impedance controller. Stability during gains variation is also guaranteed. The effectiveness of the method is experimentally validated on the quadrupedal robot ANYmal. The variable impedance helps the robot to tackle challenging scenarios like walking on rough terrain and colliding with an obstacle.
Original languageEnglish
Title of host publication2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages6028-6035
Number of pages8
ISBN (Electronic)978-1-7281-4005-6
ISBN (Print)978-1-7281-4004-9
DOIs
Publication statusPublished - 27 Jan 2020
Event2019 IEEE/RSJ International Conference on Intelligent Robots and Systems - Macau, China
Duration: 4 Nov 20198 Nov 2019
https://www.iros2019.org/

Publication series

Name
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2019 IEEE/RSJ International Conference on Intelligent Robots and Systems
Abbreviated titleIROS 2019
Country/TerritoryChina
CityMacau
Period4/11/198/11/19
Internet address

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