基于改进人工势场法的多目标点路径规划

Multi-objective point path planning based on improved artificial potential field method

为实现智能小车移动时需到达多个目标点的目的,提出一种基于改进人工势场法的多目标点路径规划。首先,通过模拟退火算法解决了传统人工势场法中机器人移动时陷入局部势能最小点振荡的问题;随后,通过碰撞预测算法以及无效障碍物概念解决了人工势场中目标点不可达的问题;最后建立多目标点智能小车移动模型,将改进的人工势场法运用其中进行MATLAB仿真。结果表明,改进的人工势场法很好地规避了路径中的障碍物,到达各目标点。

In order to reach multiple target points when intelligent vehicle moves,a multi-target point path planning based on improved artificial potential field method was proposed.Firstly,the simulated annealing algorithm was used to solve the problem of the robot falling into the minimum oscillation of local potential energy when moving in traditional artificial potential field method.Then,the collision prediction algorithm and the concept of ineffective obstacles were used to solve the problem of unreachable target points in the traditional algorithm,finally the multi-objective moving model of smart car was established.The improved artificial potential field method was used to simulate the model with MATLAB,and the results showed that the improved artificial potential field method could avoid the obstacles encountered in the path well and arrive at each target point.The improved artificial potential field method could solve the problems of single local potential minima and multiple local potential minima,and it was of great reference significance to the path planning of mobile robot.