动态障碍环境下，机器人能安全绕行并自动生成无碰撞路径。
Local Path Planning with Dynamic Obstacle Avoidance in Unstructured Environments
- 结合切线规划与轨迹外推，实时生成避障路径。
- 在多随机移动障碍物环境中，路径始终避开碰撞。
- 适合需要实时避障的无人地面车辆应用。
在充满动态障碍物的非结构化环境中，障碍物规避与路径规划对无人地面车辆（UGVs）至关重要。本文提出一种新方法，将基于切线的路径规划与轨迹外推相结合，构建局部路径规划决策算法。假设机器人已知起点和目标点，并预先计算全局路径及一系列航点。当机器人在航点间移动时，算法旨在避免与动态障碍物发生碰撞。这些障碍物沿多项式轨迹运动，其初始位置在局部地图中随机分布，速度在0至机器人允许的最大物理速度之间随机设定，同时伴有随机加速度。在多个动态障碍物随机运动的场景中进行了测试，仿真结果表明，所提出的局部路径规划策略能逐步生成无碰撞路径，使机器人安全抵达目标位置。
原文摘要 · Abstract (English)
Obstacle avoidance and path planning are essential for guiding unmanned ground vehicles (UGVs) through environments that are densely populated with dynamic obstacles. This paper develops a novel approach that combines tangentbased path planning and extrapolation methods to create a new decision-making algorithm for local path planning. In the assumed scenario, a UGV has a prior knowledge of its initial and target points within the dynamic environment. A global path has already been computed, and the robot is provided with waypoints along this path. As the UGV travels between these waypoints, the algorithm aims to avoid collisions with dynamic obstacles. These obstacles follow polynomial trajectories, with their initial positions randomized in the local map and velocities randomized between O and the allowable physical velocity limit of the robot, along with some random accelerations. The developed algorithm is tested in several scenarios where many dynamic obstacles move randomly in the environment. Simulation results show the effectiveness of the proposed local path planning strategy by gradually generating a collision free path which allows the robot to navigate safely between initial and the target locations.
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