论文标题
动态环境中的移动机器人路径计划：调查
Mobile Robot Path Planning in Dynamic Environments: A Survey
论文作者
论文摘要
在人口稠密的动态环境中，机器人导航面临许多挑战。本文介绍了在密集环境中机器人导航的路径规划方法的调查。特别是，关于计划范围和可执行性，移动机器人导航框架中的路径规划由全球路径计划和本地路径计划组成。在此框架内，论文中介绍了路径计划方法的最新进展，同时研究了它们的优势和劣势。值得注意的是，全面分析了最近开发的速度障碍法及其作为本地规划师的变体。此外，作为当前机器人应用中广泛使用的无模型方法，本文详细介绍了基于增强学习的路径计划算法。
There are many challenges for robot navigation in densely populated dynamic environments. This paper presents a survey of the path planning methods for robot navigation in dense environments. Particularly, the path planning in the navigation framework of mobile robots is composed of global path planning and local path planning, with regard to the planning scope and the executability. Within this framework, the recent progress of the path planning methods is presented in the paper, while examining their strengths and weaknesses. Notably, the recently developed Velocity Obstacle method and its variants that serve as the local planner are analyzed comprehensively. Moreover, as a model-free method that is widely used in current robot applications, the reinforcement learning-based path planning algorithms are detailed in this paper.
