首页 /研究 /Path planning method based on neural network and genetic algorithm
LEARNING

Path planning method based on neural network and genetic algorithm

Huahua Chen, Xin Du, Weikang Gu

发表年份
2005
引用次数
8

摘要

In this paper, a method of dynamic obstacle avoidance and path planning based on neural network and genetic algorithm is proposed. The neural network model of dynamic environmental information in the workspace for a robot is constructed. The relationship between dynamic obstacle pveidaace and t8e alpat ef tko model is embiished based on this model and the two-dimensional coding for the via-points of path is converted to onedimensional one. Then the fitness of the dynamic obstacle avoidance and that of the shortest distance are fused to a fitness function. The simulation results show that the proposed method is correct and effective.

关键词

Fitness functionObstacle avoidanceMotion planningWorkspaceComputer scienceArtificial neural networkGenetic algorithmObstacleCoding (social sciences)Path (computing)

相关论文

查看 LEARNING 分类全部论文