摘要
提出一种基于神经网络和遗传算法的路径规划算法。采用神经网络模型对机器人的环境信息进行描述,利用神经网络的输出建立遗传算法的适应度函数;然后使用遗传算法优化路径。在该算法中将需规划路径的二维编码简化成一维编码。仿真结果表明提出的路径规划方法是正确和有效的。
A method of path planning based on neural network and genetic algorithm is proposed. The Neural-Network （NN） model is used for depicting the information of environment around the robot, and then the output of the NN model is used to construct the fitness function of the genetic algorithm, which is used to optimize the path, In the genetic algorithm, the two-dimensional coding for the via-points of path is converted to one-dimensional one. The simulation result shows that the proposed method is correct and efficient.
出处
《计算机应用研究》
CSCD
北大核心
2007年第2期264-265,268,共3页
Application Research of Computers
基金
国家自然科学基金资助项目(60375001)
教育部博士点基金资助项目(20030532004)
