This paper presents the path planning and motion control of a self-reconfigurable mobile robot system, focusing on module-to-module autonomous docking and alignment tasks. STORM, which stands for Self-configurable and Transformable Omni-Directional Robotic Modules, features a unique mode-switching ability and novel docking mechanism design. This enables the modules that make up STORM to dock with each other and form a variety configurations in or to perform a large array of tasks. The path planning and motion control presented here consists of two parallel schemes. A Lyapunov function-based precision controller is proposed to align the target docking mechanisms in a small range of the target position. Then, an optimization-based path planning algorithm is proposed to help find the fastest path and determine when to switch its locomotion mode in a much larger range. Both numerical simulations and real-world experiments were carried out to validate these proposed controllers.
机构:
Chinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Peoples R ChinaChinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Peoples R China
Butt, Jawad Mehmood
Chu, Xiangyu
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Chinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Peoples R ChinaChinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Peoples R China
Chu, Xiangyu
Zheng, Hao
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Chinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Peoples R ChinaChinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Peoples R China
Zheng, Hao
Wang, Xiaomei
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Univ Hong Kong, Dept Mech Engn, Hong Kong, Peoples R ChinaChinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Peoples R China
Wang, Xiaomei
Kwok, Ka-Wai
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Univ Hong Kong, Dept Mech Engn, Hong Kong, Peoples R ChinaChinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Peoples R China
Kwok, Ka-Wai
Au, K. W. Samuel
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Chinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Peoples R ChinaChinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Peoples R China
Au, K. W. Samuel
2021 20TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS (ICAR),
2021,
: 531
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538