Omni-directional Mobile Robot Formation Control Based on Delayed Neural Network Optimized Model Predictive Approach
Authors: 
Wu Wei, Yao Chen, Dongliang Wang, Yao Yeboah, Shuai HeAuthors Info & Claims
Wu Wei, Yao Chen, Dongliang Wang, Yao Yeboah, Shuai HeAuthors Info & ClaimsPages 218 - 222
Abstract
In this paper, for two four-mecanum-wheeled omni-directional mobile robots (FM-OMRs), a leader-follower formation control scheme is proposed, which applies model predictive control (MPC) approach to solve the constraints of the FM-OMR. Firstly, according to the kinematic model of FM-OMR, the formation model is established for the further controller design. Then the MPC method is designed considering the constraints of FM-OMR. Besides, a delayed neural network is adopted to solve the quadratic programming problem derived from MPC. Finally, simulation experiments on the formation control of the FM-OMR are used for verifying the validity of the proposed scheme.
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- Omni-directional Mobile Robot Formation Control Based on Delayed Neural Network Optimized Model Predictive Approach
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March 2019
279 pages
ISBN:9781450361286
DOI:10.1145/3319921
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- Xi'an Jiaotong-Liverpool University: Xi'an Jiaotong-Liverpool University
- University of Texas-Dallas: University of Texas-Dallas
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Association for Computing Machinery
New York, NY, United States
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Published: 15 March 2019
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- Refereed limited
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- National Natural Science Foundation of China
- the Science and Technology Planning Project of Guangzhou
- Science and Technology Planning Project of Guangdong
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ICIAI 2019
ICIAI 2019: 2019 The 3rd International Conference on Innovation in Artificial Intelligence
March 15 - 18, 2019
Suzhou, China
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