Variable stiffness locomotion with guaranteed stability for quadruped robots traversing uneven terrains
Quadruped robots are widely applied in real-world environments where they have to face the challenges of walking on unknown rough terrains. This paper presents a control pipeline that generates robust and compliant legged locomotion for torque-controlled quadruped robots on uneven terrains. The Cart...
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Published in | Frontiers in robotics and AI Vol. 9; p. 874290 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Frontiers Media S.A
29.08.2022
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Subjects | |
Online Access | Get full text |
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Summary: | Quadruped robots are widely applied in real-world environments where they have to face the challenges of walking on unknown rough terrains. This paper presents a control pipeline that generates robust and compliant legged locomotion for torque-controlled quadruped robots on uneven terrains. The Cartesian motion planner is designed to be reactive to unexpected early and late contacts using the estimated contact forces. Moreover, we present a novel scheme of optimal stiffness modulation that aims to coordinate desired compliance and tracking performance. It optimizes joint stiffness and contact forces coordinately in a quadratic programming (QP) formulation, where the constraints of non-slipping contacts and torque limits are imposed as well. In addition, the issue of stability under variable stiffness control is solved by imposing a tank-based passivity constraint explicitly. We finally validate the proposed control pipeline on our quadruped robot CENTAURO in experiments on uneven terrains and, through comparative tests, demonstrate the improvements of the variable stiffness locomotion. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Manolo Garabini, University of Pisa, Italy Chenkun Qi, Shanghai Jiao Tong University, China Yuan Tian, Unitree Robotics, China This article was submitted to Robotic Control Systems, a section of the journal Frontiers in Robotics and AI Hongchao Zhuang, Tianjin University of Technology and Education, China Reviewed by: Ivan Virgala, Technical University of Košice, Slovakia |
ISSN: | 2296-9144 2296-9144 |
DOI: | 10.3389/frobt.2022.874290 |