用扫描区域图实现机器人在未知环境中的安全导航与建图。
Key-Scan-Based Mobile Robot Navigation: Integrated Mapping, Planning, and Control using Graphs of Scan Regions
- 以星凸扫描区构图，构建度量-拓扑融合地图。
- 通过局部导航策略组合实现全局安全路径规划。
- 自动选取关键扫描点，适合复杂环境探索任务。
在事先未知的环境中实现安全自主导航，是移动机器人在非结构化杂乱环境中可靠完成配送、巡检和交互等任务的关键能力。本文提出一种基于局部感知星凸扫描区域的姿态图作为度量-拓扑地图，星凸性支持简单有效的局部导航策略。设计了一类新型安全局部扫描导航策略，并通过顺序组合实现感知驱动的反馈运动规划，确保在局部扫描区域并集上的可证明正确且安全的导航。引入桥接扫描与前沿扫描的概念，实现未知环境中关键扫描点的自动选择与探索，完成集成建图与导航。通过搭载360°激光测距仪的移动机器人，在2D杂乱环境中通过ROS-Gazebo仿真和真实硬件实验验证了该框架的有效性。
原文摘要 · Abstract (English)
Safe autonomous navigation in a priori unknown environments is an essential skill for mobile robots to reliably and adaptively perform diverse tasks (e.g., delivery, inspection, and interaction) in unstructured cluttered environments. Hybrid metric-topological maps, constructed as a pose graph of local submaps, offer a computationally efficient world representation for adaptive mapping, planning, and control at the regional level. In this paper, we consider a pose graph of locally sensed star-convex scan regions as a metric-topological map, with star convexity enabling simple yet effective local navigation strategies. We design a new family of safe local scan navigation policies and present a perception-driven feedback motion planning method through the sequential composition of local scan navigation policies, enabling provably correct and safe robot navigation over the union of local scan regions. We introduce a new concept of bridging and frontier scans for automated key scan selection and exploration for integrated mapping and navigation in unknown environments. We demonstrate the effectiveness of our key-scan-based navigation and mapping framework using a mobile robot equipped with a 360$^{\circ}$ laser range scanner in 2D cluttered environments through numerical ROS-Gazebo simulations and real hardware~experiments.
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