基于粒子群径向基函数网络的矿井救援机器人局部路径规划研究

Study on Local Path Planning of Mine Rescue Robot Based on Particle Group Radial Basis Function Network

提出了基于粒子群径向基函数网络的矿井救援机器人局部路径规划研究。利用算法模拟矿井复杂环境对救援机器人进行训练,调整权值,从而得到最优解,同时利用确定性局部规划算法来优化粒子群算法,使其对局部的处理更加合理。研究表明,该算法规避了最小二乘法容易陷入局部极小值的问题,且能用非常快的速度去逼近最优解,对结果的优化更加合理,实用性更好,准确性更高。

The local path planning of mine rescue robot based on particle swarm radial basis function network is proposed. The rescue robot is trained by using the algorithm to simulate the complex environment of mine; adjusting weight, the optimal solution is obtained. At the same time, the deterministic local planning algorithm is used to optimize the particle swarm algorithm to make it more reasonable for local processing. Studies show that the algorithm avoid the least-square method easily trapped in local minimum problem, and can use a very fast speed to approximate the optimal solution, the optimization of the result is more reasonable, more practical and more accurate.