融合动态障碍物运动信息的路径规划算法

doi:10.3778/j.issn.1002-8331.2103-0410

摘要/Abstract

摘要： 传统的路径规划算法只能在障碍物不发生位置变化的环境中计算最优路径。但是随着机器人在商场、医院、银行等动态环境下的普及，传统的路径规划算法容易与动态障碍物发生碰撞等危险。因此，关于随机动态障碍物条件下的机器人路径规划算法需要得到进一步改善。为了解决在动态环境下的机器人路径规划问题，提出了一种融合机器人与障碍物运动信息的改进动态窗口法来解决机器人在动态环境下的局部路径规划问题，并且与优化A*算法相结合来实现全局最优路径规划。主要内容体现为：在全局路径规划上，采用优化A*算法求解最优路径。在局部路径规划上，以动态障碍物的速度作为先验信息，通过对传统动态窗口法的评价函数进行扩展，实现机器人在动态环境下的自主智能避障。实验证明，该算法可以实现基于全局最优路径的实时动态避障，具体表现为可以在不干涉动态障碍物的条件下减少碰撞风险、做出智能避障且路径更加平滑、长度更短、行驶速度更快。

关键词: 动态避障, 动态窗口法, A*算法, 障碍物预测, 路径规划

Abstract: The traditional path planning algorithm can only calculate the optimal path in the environment where the position of obstacles does not change. However, with the popularity of robots in dynamic environments such as shopping malls, hospitals and banks, traditional path planning algorithms are prone to collision with dynamic obstacles. Therefore, the robot path planning algorithm with random dynamic obstacles needs to be further improved. Therefore, the robot path planning algorithm under the condition of random dynamic obstacles needs to be further improved. In order to solve the robot path planning problem in dynamic environment, an improved dynamic window approach is proposed to solve the robot path planning problem in dynamic environment, and it is combined with the optimization A* algorithm to realize the global optimal path planning. In the global path planning, the optimal A* algorithm is used to solve the optimal path. In local path planning, the speed of dynamic obstacles is used as a priori information, and the evaluation function of the traditional dynamic window approach is expanded to realize autonomous and intelligent obstacle avoidance of the robot in a dynamic environment. Experiments show that the algorithm can realize real-time dynamic obstacle avoidance based on the global optimal path, which is specifically manifested in reducing the risk of collision without interfering with dynamic obstacles, making intelligent obstacle avoidance and making the path smoother, shorter and faster.

Key words: dynamic obstacle avoidance, dynamic window approach, A* algorithm, obstacle prediction, path planning

封硕, 吉现友, 程博, 韩启东, 于少伟. 融合动态障碍物运动信息的路径规划算法[J]. 计算机工程与应用, 2022, 58(21): 279-285.

FENG Shuo, JI Xianyou, CHENG Bo, HAN Qidong, YU Shaowei. Path Planning Algorithm Based on Dynamic Obstacle Movement Information[J]. Computer Engineering and Applications, 2022, 58(21): 279-285.

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