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Robot Path Planning Method Based on Improved Genetic Algorithm

Mingyang Jiang, Xiaojing Fan, Zhili Pei, Jingqing Jiang, Yulan Hu, Qinghua Wang

Year
2013
Citations
6

Abstract

Abstract: This paper presents an improved genetic algorithm for mobile robot path planning. The algorithm uses artificial potential method to establish the initial population, and increases value weights in the fitness function, which increases the controllability of robot path length and path smoothness. In the new algorithm, a flip mutation operator is added, which ensures the individual population collision path. Simulation results show that the proposed algorithm can get a smooth, collision-free path to the global optimum, the path planning algorithm which is used to solve the problem is effective and feasible. Copyright © 2014 IFSA Publishing, S. L.

Keywords

Path (computing)Computer scienceGenetic algorithmMotion planningAlgorithmArtificial intelligenceRobotMachine learningComputer network

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