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Volume 11 Issue 7
Jul.  2024

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Y. Lian, X. Xiao, J. Zhang, L. Jin, J. Yu, and  Z. Sun,  “Neural dynamics for cooperative motion control of omnidirectional mobile manipulators in the presence of noises: A distributed approach,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 7, pp. 1605–1620, Jul. 2024. doi: 10.1109/JAS.2024.124425
Citation: Y. Lian, X. Xiao, J. Zhang, L. Jin, J. Yu, and  Z. Sun,  “Neural dynamics for cooperative motion control of omnidirectional mobile manipulators in the presence of noises: A distributed approach,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 7, pp. 1605–1620, Jul. 2024. doi: 10.1109/JAS.2024.124425

Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

doi: 10.1109/JAS.2024.124425
Funds:  The work was supported in part by the National Natural Science Foundation of China (62373065, 61873304, 62173048, 62106023), the Innovation and Entrepreneurship Talent funding Project of Jilin Province (2022QN04), the Changchun Science and Technology Project (21ZY41), and the Open Research Fund of National Mobile Communications Research Laboratory, Southeast University (2024D09)
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  • This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators (MOMMs). The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning (CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming (QP) and solved online utilizing a noise-tolerant zeroing neural network (NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

     

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    Highlights

    • Distributed communication for multiple omnidirectional mobile manipulators
    • Cooperative quadratic planning for repetitive motion and trajectory tracking
    • Neural dynamics-based cooperative control of multi-mobile manipulators

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