Enhanced Agility and Safety in Mobile Manipulators through Centroidal Momentum-Based Motion Planning

This paper presents a framework for the planning and control of wheeled mobile manipulators, integrating a novel reduced-order dynamics model that can be used during motion planning to enhance safety and prevent tip-overs. Leveraging centroidal momentum dynamics, the model captures key forces at the center of mass, enabling efficient, dynamically feasible trajectory generation that considers both manipulator motion and ground interaction forces. Unlike traditional methods that rely on conservative planning or separate reactive tip-over prevention mechanisms, our approach incorporates stability considerations directly into the motion planning phase. By embedding the zero moment point criterion within the model, our framework ensures tip-over prevention even during fast and payload-intensive tasks. Simulations demonstrate the effectiveness of this approach, achieving stable and efficient task execution across various scenarios.

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Publication Details

Published
2025-06-24
DOI
https://doi.org/10.23919/ecc65951.2025.11186833
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

Enhanced Agility and Safety in Mobile Manipulators through Centroidal Momentum-Based Motion Planning

Zehui Lu, Yebin Wang, Na Li, Min Dai
Robotic Path Planning Algorithms
article

Enhanced Agility and Safety in Mobile Manipulators through Centroidal Momentum-Based Motion Planning

Zehui Lu, Yebin Wang, Na Li, Min Dai
article en

Abstract

This paper presents a framework for the planning and control of wheeled mobile manipulators, integrating a novel reduced-order dynamics model that can be used during motion planning to enhance safety and prevent tip-overs. Leveraging centroidal momentum dynamics, the model captures key forces at the center of mass, enabling efficient, dynamically feasible trajectory generation that considers both manipulator motion and ground interaction forces. Unlike traditional methods that rely on conservative planning or separate reactive tip-over prevention mechanisms, our approach incorporates stability considerations directly into the motion planning phase. By embedding the zero moment point criterion within the model, our framework ensures tip-over prevention even during fast and payload-intensive tasks. Simulations demonstrate the effectiveness of this approach, achieving stable and efficient task execution across various scenarios.

California Institute of Technology (US), Harvard University (US), Vaughn College of Aeronautics and Technology (US), American Institute of Aeronautics and Astronautics (US), Nanjing University of Aeronautics and Astronautics (CN)
Openalex Percentile: Top 71%
Robotic Path Planning Algorithms
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Enhanced Agility and Safety in Mobile Manipulators through Centroidal Momentum-Based Motion Planning — Zehui Lu, Yebin Wang, et al. · (2025) | TGRS Research Map | TGRS