Bio-inspired locomotion control for UBot self-reconfigurable modular robot
Cui, Xindan and Zhu, Yanhe and Zhao, Jie and Piao, Songhao and Yang, Erfu; (2023) Bio-inspired locomotion control for UBot self-reconfigurable modular robot. In: 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023. 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023 . IEEE, Piscataway, NJ, pp. 1-6. ISBN 9798350347074 (https://doi.org/10.1109/iccad57653.2023.10152395)
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Abstract
This paper first presents a mathematic CPG (central pattern generator) model which has been developed based on the characteristics of a self-reconfigurable modular robot (UBot)'s modules with universal joints. Then, a bionic motion neural control network based on the CPG is proposed to solve the problem of multi-mode locomotion control problem in the complex environment. The bionic network is composed of perceptual neurons, CPG phase modulation network and motor neurons, so it can coordinate the walking and creeping gait of the modular robot before and after deformation, and adapt to autonomous movement in the complex environment with challenging features, such as steps, slopes and obstacles. Finally, the proposed motion control algorithm is verified by experiments.
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Item type: Book Section ID code: 86280 Dates: DateEvent10 May 2023Published20 March 2023AcceptedNotes: © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Subjects: Technology > Engineering (General). Civil engineering (General) > Engineering design Department: Faculty of Engineering > Design, Manufacture and Engineering Management Depositing user: Pure Administrator Date deposited: 25 Jul 2023 11:14 Last modified: 14 Aug 2024 00:52 URI: https://strathprints.strath.ac.uk/id/eprint/86280