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Heavy-duty hexapod robot sideline tipping judgment and recovery

Published online by Cambridge University Press:  15 March 2024

Lianzhao Zhang
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin, China
Fusheng Zha
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin, China
Wei Guo
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin, China
Chen Chen
Affiliation:
Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration, Harbin University of Science and Technology, Harbin, China Key Laboratory of Intelligent Technology for Cutting and Manufacturing Ministry of Education, Harbin University of Science and Technology, Harbin, China
Lining Sun*
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin, China
Pengfei Wang*
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin, China
*
Corresponding authors: Lining Sun; Email: lnsun@hit.edu.cn, Pengfei Wang; Email: wangpengfei@hit.edu.cn
Corresponding authors: Lining Sun; Email: lnsun@hit.edu.cn, Pengfei Wang; Email: wangpengfei@hit.edu.cn

Abstract

Heavy-duty hexapod robots are well-suited for physical transportation, disaster relief, and resource exploration. The immense locomotion capabilities conferred by the six appendages of these systems enable traversal over unstructured and challenging terrain. However, tipping can be a serious concern when moving with a tripod gait in these challenging environments, which may cause irreversible consequences such as compromised movement control and potential damage. In this paper, we focus on heavy-duty hexapod robot sideline tipping judgment and recovery during tripod gait motion, and a novel sideline tipping judgment and recovery method is proposed by adjusting an optimal swinging leg to the stance state. Considering the locomotion environments, motion mode, and tipping analysis, the robot’s stability margin is quantified, and the tipping event is evaluated by the Force Angle Stability Measure (FASM). The recovery method is initiated upon detecting that the robot is tipping, which involves the selection of an adjustment leg and the determination of an optimal foothold. Since the FASM is based on the foot force and robot center of gravity (CoG), the stability margin quantification expression is reformulated to the constraint form of quadratic programming (QP). Furthermore, a foot force distribution method, integrating stability margin considerations into the QP model, has been devised to ensure post-adjustment stability of the landing leg. Experiments on tipping judgment and recovery demonstrate the effectiveness of the proposed approaches on tipping judgment and recovery.

Information

Type
Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press

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