避障
运动规划
计算机科学
路径(计算)
障碍物
避碰
实时计算
人工智能
移动机器人
机器人
计算机安全
政治学
法学
程序设计语言
碰撞
作者
Zijian Wu,Dejun Yin,Junyao Xiao
摘要
As a decision-making layer, path planning technology plays an important role in intelligent driving. Using the A* algorithm or the TEB (timed elastic band) algorithm alone cannot achieve global path optimization and dynamic obstacle avoidance at the same time. This paper adopts a path planning strategy combining A* and TEB algorithms. First, use the A* algorithm to test in a static environment, then use the TEB algorithm to test in a dynamic environment, and finally, conduct experiments in a complex environment with both static and dynamic obstacles, the feasibility and effectiveness of the method for path planning in static maps with dynamic obstacles are verified.
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