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Leader-follower multi-robot formation system using model predictive control method based on particle swarm optimization
Xiao H.1; Chen C.L.P.1
2017-06-30
Conference Name32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC)
Source PublicationProceedings - 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017
Pages480-484
Conference DateMAY 19-21, 2017
Conference PlaceHefei, PEOPLES R CHINA
Abstract

For controlling the multi-robot formation system, a leader-follower separation-bearing-orientation scheme (S-BOS) is proposed and the leader-follower relationship can be represented as a formation-error kinematic system through SBOS strategy. In order to achieve the control objective, a nonlinear model predictive control (NMPC) strategy is applied to formulate the formation-error kinematic into a minimization optimization problem according to cost function. To solve this optimization problem online efficiently, a particle swarm optimization (PSO) is proposed to search for the global optimal solution as the control input. In the end of this work, simulations of the multi-robot formation are performed to verify the effectiveness of the developed strategy.

KeywordMultiple Mobile Robots Formation Nonlinear Model Predictive Control (Nmpc) Particle Swarm Optimization (Pso) Separation-bearing-orientation Scheme (Sbos)
DOI10.1109/YAC.2017.7967457
URLView the original
Language英語English
WOS IDWOS:000425862800090
Scopus ID2-s2.0-85026877068
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Citation statistics
Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Universidade de Macau
2.Dalian Maritime University
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Xiao H.,Chen C.L.P.. Leader-follower multi-robot formation system using model predictive control method based on particle swarm optimization[C], 2017, 480-484.
APA Xiao H.., & Chen C.L.P. (2017). Leader-follower multi-robot formation system using model predictive control method based on particle swarm optimization. Proceedings - 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017, 480-484.
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