Terrain-Adaptive Planning and Control of Complex Motions for Walking Excavators
Edo Jelavic, Yannick Berdou, Dominic Jud, Simon Kerscher, Marco Hutter
Abstract
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.
BibTeX
@inproceedings{iros2020_terrainadaptivep,
title = {Terrain-Adaptive Planning and Control of Complex Motions for Walking Excavators},
author = {Edo Jelavic and Yannick Berdou and Dominic Jud and Simon Kerscher and Marco Hutter},
booktitle = {IROS 2020},
year = {2020}
}