Mobile Robot Path Planning and Research in the Improved Artificial Immune Algorithm

Abstract:

Aim at local optimal problem in the path planning of mobile robot by artificial immune algorithm, it is proposed that the improved artificial immune algorithm of mobile robot path planning. Based on artificial immunity algorithm, the potential function method of an artificial potential field is used in this algorithm, improving randomness of the initial population of the artificial immune algorithm, then the algorithm make initial population turn to evolutionary operation through crossover, variance and selection operator to get optimum antibody. The simulation results showed that this algorithm is easy to get the optimal path, at the same time, increasing the speed of the path planning, and the length of the optimal path planning is less 28.5% compare with the traditional immune algorithm.

• Periodical: Advanced Materials Research (Volumes 466-467)
• Pages: 864-869
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.466-467.864
• Online since: February 2012
• Authors: Yuan Bin Hou, Wei Wang, Xiao Yue Lu
• Keywords: Artificial Immune Algorithm, Field Function, Immune Evolutionary, Mobile Robot, Path Planning

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