基于融合引-斥力与动态窗口法的机器人静动态局部路径规划方法优化

Optimization of Robot Static Dynamic Local Path Planning Method Based on Integrating Attraction-Repulsion and Dynamic Window Approach

针对DWA(dynamic window approach)在建筑施工障碍场景中使用时存在的轨迹评价选择不合理、避障效率不高等问题,提出了一种融合引-斥力与动态窗口法的机器人静动态局部路径规划方法。首先,提出利用有无障碍物两种情况下的速度采样约束条件来完善速度采样约束。其次,优化导航评价函数以提升DWA的运行速度。最后,提出引力评价函数,以提升避障规划速度;结合斥力思想优化避障函数,解决轨迹选择不合理的问题。不同栅格地图实验结果表明:在静态地图环境下,所提算法迭代次数、运行时间、路径长度三种指标性能均可优化20%左右;在动态环境地图下,3种性能指标提升优化可达25%以上,解决了原始及其他改进型DWA在建筑施工复杂障碍环境下存在的轨迹评价选择不合理、避障效率不高等问题。

To address unreasonable trajectory evaluation selection and low obstacle avoidance efficiency problems of the dynamic window approach(DWA)used in obstacle scenes of building construction,we propose a static and dynamic local path planning method for robots based on integrating attraction-repulsion and DWA.First,we improve the constraint conditions of velocity sampling with and without obstacles for multi-obstacle environments.Second,we optimize the navigation evaluation function to increase the running speed.Finally,we propose an evaluation function to solve the unreasonable trajectory selection problem and optimize the obstacle avoidance evaluation function by combining repulsion thought.Experiment results in different environments show that the performance of the proposed algorithm,including iteration times,running time,and path length,can be optimized by 20%approximately.The improvement in various performance indicators can reach more than 25%,which solves the problems of unreasonable trajectory evaluation selection and low obstacle avoidance efficiency in the original and improved DWAs in complex obstacle environments.