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Multi mobile robot path planning based on genetic algorithm

Shuhua Liu, Yantao Tian, Jinfang Liu

Year
2004
Citations
26

Abstract

Genetic Algorithm has implicit parallelism and global optimization, however its computation speed constrains its on-line application. This paper attempts to apply improved genetic algorithm to multi mobile robot path planning. By using based-knowledge genetic operators, the performance of genetic algorithm is improved greatly. Simulation results showed that the improved genetic algorithm can satisfy real-time demand. In the future, it is used on-line to replan the multi mobile robot path.

Keywords

Computer scienceGenetic algorithmMotion planningMobile robotPath (computing)ComputationRobotGenetic representationCultural algorithmParallelism (grammar)

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