SL1M: Sparse L1-norm Minimization for contact planning on uneven terrain

Steve Tonneau, Daeun Song, Pierre Fernbach, Nicolas Mansard, Michel Taïx, Andrea Del Prete

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

Abstract

One of the main challenges of planning legged locomotion in complex environments is the combinatorial contact selection problem. Recent contributions propose to use integer variables to represent which contact surface is selected, and then to rely on modern mixed-integer (MI) optimization solvers to handle this combinatorial issue. To reduce the computational cost of MI, we exploit the sparsity properties of L1 norm minimization techniques to relax the contact planning problem into a feasibility linear program. Our approach accounts for kinematic reachability of the center of mass (COM) and of the contact effectors. We ensure the existence of a quasi-static COM trajectory by restricting our plan to quasi-flat contacts. For planning 10 steps with less than 10 potential contact surfaces for each phase, our approach is 50 to 100 times faster that its MI counterpart, which suggests potential applications for online contact re-planning. The method is demonstrated in simulation with the humanoid robots HRP-2 and Talos over various scenarios.
Original languageEnglish
Title of host publication2020 IEEE International Conference on Robotics and Automation (ICRA)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages6604-6610
ISBN (Electronic)978-1-7281-7395-5
ISBN (Print)978-1-7281-7396-2
DOIs
Publication statusPublished - 15 Sep 2020
Event2020 International Conference on Robotics and Automation - Virtual conference, France
Duration: 31 May 202031 Aug 2020
https://www.icra2020.org/

Publication series

Name
ISSN (Print)1050-4729
ISSN (Electronic)2577-087X

Conference

Conference2020 International Conference on Robotics and Automation
Abbreviated titleICRA 2020
Country/TerritoryFrance
CityVirtual conference
Period31/05/2031/08/20
Internet address

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