用几何方法快速生成可扩展的圆形安全区，提升局部路径规划效率
Fast Expanding Safe Circular Regions for Efficient Local Path Planning
- 基于激光雷达扫描构建向目标方向扩展的圆形安全区域
- 计算速度更快，规划时长远超传统优化方法
- 适合对实时性要求高的复杂环境机器人导航
局部导航是机器人导航中的核心问题，已有多种方法被提出，如动态窗口法、模型预测控制、控制屏障函数及基于机器学习的技术。尽管这些方法在简单环境中表现良好，但许多依赖优化或学习过程，在复杂场景中表现受限。本文提出一种更几何化的算法，通过从局部激光雷达扫描中计算一系列向目标方向扩展的圆形区域，高效捕获可通行空间，实现更快的计算速度和更长的规划时域。该方法在ROS2框架中实现，并在仿真环境中进行评估。
原文摘要 · Abstract (English)
Local navigation is one of the fundamental problems in robot navigation, and numerous approaches have been proposed over the years, including methods such as the Dynamic Window Approach, Model Predictive Control, and more recently, Control Barrier Functions and machine learning based techniques. While these methods perform well in simple environments, many of them rely on optimization or learning based procedures that can struggle in more complex scenarios. In contrast, this article proposes a more geometric algorithmic approach that enables a local navigation method with faster computation times and longer planning horizons. The proposed method is based on the computation of a sequence of circular regions from a local LiDAR scan that expand in the direction of the goal and capture free local navigable space. The proposed method was implemented in the ROS2 framework and evaluated in a simulated environment.
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