摘要
针对移动机器人传统路径规划算法效率不高,寻优能力差等问题,提出一种基于神经网络和粒子群优化算法相结合的移动机器人路径规划方法.该方法利用神经网络实现大量的并行和分布计算,发挥PSO简单、容易实现的优点,提高了路径规划的计算效率和可靠性.仿真结果表明,这种新路径规划方法是可行且有效的.
The quality and efficiency of calculation is the two puzzling problems in the traditional algorithm for the robot path planning. In this paper, a new method of obstacle avoidance and path planning based on neural network and particle swarm optimization is proposed. In this method, a neural network is used to realize substantive parallel and distributed computing. And also this exerts the merit of PSO, which improves the computational efficiency and reliability. As it is proved by analysis and test, that a better result is obtained by the proposed algorithm,
出处
《沈阳理工大学学报》
CAS
2007年第6期11-14,共4页
Journal of Shenyang Ligong University
关键词
神经网络
粒子群优化算法
路径规划
neural network
particle swarm optimization （PSO） algorithm
Path Planning
