基于向量场的移动机器人动态路径规划

由于简洁、高效等优点,人工势场法已应用于自主移动机器人的在线实时路径规划,并受到广泛关注.目前,人工势场法在处理静态环境、动态匀速环境下的路径规划方面已有许多成果,但是,机器人在全变速环境下进行在线实时路径规划时,会出现路径冗余、避碰不及等现象.为此,将目标关于机器人的相对加速度因素引入引力势场函数中;在斥力势场函数的基础上融合避碰预测、减速避障策略;最终,机器人能够避免大量无谓避障,当与障碍物相对速度较大时能提前避障,且快速跟踪到目标.仿真结果验证了所提方法的有效性.

Dynamic Path Planning for Mobile Robot Based on Vector Field

Due to its simplicity and high efficiency,the artificial potential field method has been widely focused and used for autonomous robots.At present,potential field methods have received many accolades in dealing with path planning in static environments or dynamic uniform environments,but unnecessary obstacle avoidance or collision caused by excessive relative velocity of the mobile robot with respect to obstacle in a non-uniform environment will appear .Thus,this paper defined a new potential function with the relative displacement.The relative velocity and the relative acceleration factors are incorporated into the attractive potential function.The obstacle avoidance prediction and the velocity-decreasing collision avoidance strategy are brought into the repulsion potential function,which make the robot can not only track target with variable motion,but also keep the same movement trend with target and remove largely the unnecessary obstacle avoidance.When the relative velocity of the mobile robot with respect to obstacle is larger,the robot can also take an obstacle avoidance measure in advance.The simulation result verifies the effectiveness of method proposed.