融合安全A^(*)算法和改进人工势场法的巡检机器人路径规划

Path planning of inspection robot integrated safety A^(*) algorithm and improved artificial potential field method

大型仓储中心等货物密集的地方,安全性要求也更高。随着机器人技术的成熟,巡检机器人逐渐代替人工巡检,机器人路径规划算法也逐渐出现。本文针对巡检机器人,采取全局路径规划和局部路径规划相结合的方法,提出了一种融合安全A^(*)和人工势场法的算法,在A^(*)代价函数中添加安全距离,并选取安全A^(*)的关键节点加入到人工势场法中作为引力,引导巡检机器人前进。经过MATLAB仿真及障碍物实验,该方法规划出的路径较短且具有良好的避障能力,具有良好的性能。

In places where goods are dense,such as large storage centers,safety requirements are also higher.With the maturity of robot technology,inspection robots gradually replace manual inspection,and robot path planning algorithms also gradually appear.For inspection robots,a combination of global path planning and local path planning is adopted,and an algorithm that integrates safety A^(*)and artificial potential field method is proposed.The safety distance is added to the A^(*)cost function,and the key nodes of the safety A^(*)are selected and added to the artificial potential field method as the gravitational force to guide the inspection robot forward.After MATLAB simulation,a short path with good obstacle avoidance capability and good performance is planed with this method.