UGV路径重规划的自主决策

Ning Li, Huachao Yu, Liang Zhou, W. Cheng, Xijun Zhao, Bo Su
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引用次数: 0

摘要

提出了一种无人驾驶汽车在遇到阻塞道路时自主决策路径重新规划的方法。该系统包括一个全局路径规划器和一个局部路径规划器。基于已知环境中的先验信息,首先构建拓扑地图来描述道路的连通性。全局路由规划器根据拓扑图进行路径规划或重新规划,生成全局路由。根据路径,采用A*搜索算法结合模型预测控制,对阻塞路段进行局部路径规划和判断。完整的自主决策过程包括:判断局部阻塞道路,倒车至岔路口/十字路口道路节点,重新规划全局路线,绕行通过阻塞道路。实验表明,在已知的动态环境下,该方法能够有效地解决路径重新规划问题,从而提高UGV的自主交通性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autonomous Decision-Making of Path Re-planning for UGV
A novel approach of autonomous decision-making of path re-planning for UGV is proposed when encountering the blocked road. The system includes a global route planner and a local path planner. Based on prior information in known environment, a topological map is built first to describe connectivity of roads. The global route planner does path planning or re-planning based on the topological map to generate the global route. According to the route, A* search algorithm combined with model predictive control is used for local path planning and judgment on the blocked road. The complete autonomous decision-making process includes: judgment of the local blocked road, reversing to the fork/intersection road node, the global route re-planning and detour through the blocked road. Experiments show that in known dynamic environment, the proposed approach can effectively solve the problem of path re-planning in order to improve the autonomous traffic performance for UGV.
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