用普通UWB设备在浓烟中实现实时高精度定位与建图
Range-SLAM: Ultra-Wideband-Based Smoke-Resistant Real-Time Localization and Mapping
- 仅用距离和信号强度构建2D栅格地图，无需激光雷达
- 在浓烟环境实测定位误差低于15厘米，建图耗时<1秒/帧
- 适合消防、救援等低可见度场景的机器人导航
本文提出Range-SLAM，一种基于超宽带（UWB）信号的实时轻量级SLAM系统，用于在烟雾及其他恶劣环境下实现精准定位与建图。当激光雷达和摄像头等光学传感器在能见度极低环境中失效时，UWB信号仍可提供可靠定位。该系统仅依赖通用UWB设备提供的距离和接收信号强度指示（RSSI）信息，结合携带标签的移动体运动轨迹与射线投射算法，在不依赖昂贵激光雷达或其他专用硬件的情况下，实时构建二维占用栅格地图。为提升复杂条件下的定位性能，采用加权最小二乘法（WLS）。大量真实场景实验，包括烟雾弥漫环境及模拟挑战场景，验证了系统的鲁棒性与实时性。结果表明，系统在烟雾环境下定位误差低于15厘米，每帧建图处理时间小于1秒，且对动态障碍物具有较强适应能力。
原文摘要 · Abstract (English)
This paper presents Range-SLAM, a real-time, lightweight SLAM system designed to address the challenges of localization and mapping in environments with smoke and other harsh conditions using Ultra-Wideband (UWB) signals. While optical sensors like LiDAR and cameras struggle in low-visibility environments, UWB signals provide a robust alternative for real-time positioning. The proposed system uses general UWB devices to achieve accurate mapping and localization without relying on expensive LiDAR or other dedicated hardware. By utilizing only the distance and Received Signal Strength Indicator (RSSI) provided by UWB sensors in relation to anchors, we combine the motion of the tag-carrying agent with raycasting algorithm to construct a 2D occupancy grid map in real time. To enhance localization in challenging conditions, a Weighted Least Squares (WLS) method is employed. Extensive real-world experiments, including smoke-filled environments and simulated
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