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Load-adaptive control for quadruped mobile manipulation platforms

Published online by Cambridge University Press:  02 February 2026

Zeyu Cai Open the ORCID record for Zeyu Cai [Opens in a new window] ,
Ruipeng Cai ,
Zhentao Xie ,
Ning Huang  and
Qinchuan Li
Zeyu Cai
Affiliation:
School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, 310018, China
Ruipeng Cai
Affiliation:
School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, 310018, China
Zhentao Xie
Affiliation:
School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, 310018, China
Ning Huang
Affiliation:
School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, 310018, China
Qinchuan Li*
Affiliation:
School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, 310018, China
*
Corresponding Author: Qinchuan Li; Email: lqchuan@zstu.edu.cn
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Abstract

Currently, quadruped robots are widely used in diverse scenarios due to their high mobility, creating a demand for more advanced interaction capabilities. This study proposes a whole-body planning and control framework that integrates adaptive control into a hierarchical model predictive control (MPC) and whole-body control (WBC) structure, enhancing the environmental adaptability and interaction performance of quadruped mobile manipulators. Key innovations include: a recursive least squares and feedforward compensation strategy for accurate end-effector force estimation; relaxed barrier functions embedded in the MPC to combine dynamic obstacle avoidance with adaptive control; and a WBC-based priority hierarchy to enforce critical constraints. Validated in Gazebo simulation and on the B1-Z1 platform, the method allows the robot to handle unknown loads up to 3 kg and maintain tracking errors under 2 cm despite 35 N external disturbances. It also demonstrates strong adaptability in non-uniform object transportation, providing a reliable solution for unstructured environments.

Keywords

adaptive controlmodel predictive controlwhole-body controlquadruped robotsunknown impact model

Information

Type
Research Article
Information
Robotica , Volume 44 , Issue 1 , January 2026 , pp. 195 - 209
Copyright
© The Author(s), 2026. Published by Cambridge University Press

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