Terrain-Adaptive Planning and Control of Complex Motions for Walking Excavators

This article presents a planning and control pipeline for legged-wheeled (hybrid) machines. It consists of a Trajectory Optimization based planner that computes references for end-effectors and joints. The references are tracked using a whole-body controller based on a hierarchical optimization appr...

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Bibliographic Details
Published in2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) pp. 2684 - 2691
Main Authors Jelavic, Edo, Berdou, Yannick, Jud, Dominic, Kerscher, Simon, Hutter, Marco
Format Conference Proceeding
LanguageEnglish
Published IEEE 24.10.2020
Subjects
End effectors
Intelligent robots
Legged locomotion
Pipelines
Planning
Torque
Trajectory optimization
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Summary:This article presents a planning and control pipeline for legged-wheeled (hybrid) machines. It consists of a Trajectory Optimization based planner that computes references for end-effectors and joints. The references are tracked using a whole-body controller based on a hierarchical optimization approach. Our controller is capable of performing terrain adaptive whole-body control. Furthermore, it computes both torque and position/velocity references, depending on the actuator capabilities. We perform experiments on a Menzi Muck M545, a full size 31 Degrees of Freedom (DoF) walking excavator with five limbs: four wheeled legs and an arm. We show motions that require full-body coordination executed in realistic conditions. To the best of our knowledge, this is the first work that shows the execution of whole-body motions on a full size walking excavator, using all DoFs for locomotion.
ISSN:2153-0866
DOI:10.1109/IROS45743.2020.9341655