Swarm-robot Formation Optimization Based on Multiobjective Genetic Algorithm
On improving the performance in which the swarm-robot grid formation motion arc controlled in a complicated circumstance based on virtual force method, it is used the multiobjective genetic algorithm to optimize control parameters. Performance indexes include collision?break the ranks?connectivity, etc. The weight value of the indexes is determined by their importance. Optimization model is established, the multiobjective genetic algorithm based on Pareto sets is used to search the solution of the problem. Simulation results show that this algorithm is effectively capable of obtaining a set of non-dominated solution within a finite evolutionary generation, which overcomes the weakness of handiwork to set control parameters.
Swarm-robot System Multiobjective Optimization Genetic Algorithm Formation Motion
XIONG Ju-feng TAN Guan-zheng
College of Information Science and Engineering, Central South University, Changsha 410083 College of College of Information Science and Engineering, Central South University, Changsha 410083
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
3700-3704
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）