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首页> 外文期刊>Journal of Intelligent & Robotic Systems: Theory & Application >Hybrid Path Planning Based on Safe A* Algorithm and Adaptive Window Approach for Mobile Robot in Large-Scale Dynamic Environment
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Hybrid Path Planning Based on Safe A* Algorithm and Adaptive Window Approach for Mobile Robot in Large-Scale Dynamic Environment

机译：基于安全A *算法的混合路径规划和大规模动态环境中移动机器人的自适应窗口方法

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摘要

When mobile robot used in large-scale dynamic environments, it face more challenging problems in real-time path planning and collision-free path tracking. This paper presents a new hybrid path planning method that combines A* algorithm with adaptive window approach to conduct global path planning, real-time tracking and obstacles avoidance for mobile robot in large-scale dynamic environments. Firstly, a safe A* algorithm is designed to simplify the calculation of risk cost function and distance cost. Secondly, key path points are extracted from the planned path which generated by the safe A* to reduce the number of the grid nodes for smooth path tracking. Finally, the real-time motion planning based on adaptive window approach is adopted to achieve the simultaneous path tracking and obstacle avoidance (SPTaOA) together the switching of the key path points. The simulation and practical experiments are conducted to verify the feasibility and performance of the proposed method. The results show that the proposed hybrid path planning method, used for global path planning, tracking and obstacles avoidance, can meet the application needs of mobile robots in complex dynamic environments.
机译：当移动机器人在大型动态环境中使用时，它在实时路径规划和无碰撞路径跟踪中面临更具挑战性问题。本文介绍了一种新的混合路径规划方法，将A *算法与自适应窗口方法相结合，为大规模动态环境中的移动机器人进行全局路径规划，实时跟踪和障碍。首先，设计安全A *算法以简化风险成本函数和距离成本的计算。其次，从由安全A *生成的计划路径中提取键路点，以减少用于平滑路径跟踪的网格节点的数量。最后，采用基于自适应窗口方法的实时运动规划来实现钥匙路径点的切换的同时路径跟踪和障碍物避免（SPTAOA）。进行了仿真和实践实验，以验证所提出的方法的可行性和性能。结果表明，用于全球路径规划，跟踪和障碍避免的提议的混合路径规划方法可以满足复杂动态环境中移动机器人的应用需求。

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