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Cooperative Particle Swarm Optimization-based Model Predictive Control for Multi-Robot Formation

군집 로봇 편대 제어를 위한 협력 입자 군집 최적화 알고리즘 기반 모델 예측 제어 기법

  • Lee, Seung-Mok (Dept. of Civil and Environmental Engineering, KAIST) ;
  • Kim, Hanguen (Dept. of Civil and Environmental Engineering, KAIST) ;
  • Myung, Hyun (Dept. of Civil and Environmental Engineering, KAIST)
  • 이승목 (KAIST Urban Robotics Lab. 건설 및 환경공학과) ;
  • 김한근 (KAIST Urban Robotics Lab. 건설 및 환경공학과) ;
  • 명현 (KAIST Urban Robotics Lab. 건설 및 환경공학과)
  • Received : 2013.02.20
  • Accepted : 2013.03.15
  • Published : 2013.05.01

Abstract

This paper proposes a CPSO (Cooperative Particle Swarm Optimization)-based MPC (Model Predictive Control) scheme to deal with formation control problem of multiple nonholonomic mobile robots. In a distributed MPC framework, each robot needs to optimize control input sequence over a finite prediction horizon considering control inputs of the other robots where their cost functions are coupled by the state variables of the neighboring robots. In order to optimize the control input sequence, a CPSO algorithm is adopted and modified to fit into the formation control problem. Experiments are performed on a group of nonholonomic mobile robots to demonstrate the effectiveness of the proposed CPSO-based MPC for multi-robot formation.

Keywords

References

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