RLI-SLAM:快速稳固的距离-LiDAR-惯性紧密结合的定位和映射
Rui Xin1, Ningyan Guo1, Xingyu Ma1
1Department of Information and Communication Engineering, Beijing University of Posts and Telecommunication, Beijing 100874, China.
Sensors (Basel, Switzerland)
|September 14, 2024
概括
本研究介绍了RLI-SLAM,这是一种用于同时定位和映射 (SLAM) 的新框架. 它提高了机器人导航的准确性和稳定性,在具有挑战性的环境中使用距离-LiDAR-惯性融合和高效的循环闭合.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 计算机视觉 计算机视觉
- 传感器融合式传感器
背景情况:
- 同时定位和映射 (SLAM) 对于在未知的环境中自主导航机器人至关重要.
- 现有的SLAM系统面临着传感器漂移和实时准确性方面的挑战,特别是在快速运动期间.
研究的目的:
- 开发一个高精度,快速和强大的SLAM框架,用于长期的快速动作场景.
- 为了提高状态估计和绘图精度在封闭和具有挑战性的环境.
主要方法:
- 提出了一个新的紧密合的距离-LiDAR-惯性SLAM框架 (RLI-SLAM).
- 超宽带 (UWB) 距离和惯性传感器被融合在一起,以纠正惯性传感器偏差和漂移.
- 集成了一个高效的循环关闭检测模块,使用增量光滑因子图.
主要成果:
- 与最先进的系统相比,RLI-SLAM在状态估计和映射方面表现出卓越的准确性.
- 该框架甚至在单个范围的测量和在具有挑战性的环境中实现了强大的性能.
- 保持了较低的计算复杂性,从而实现实时应用.
结论:
- 拟议的RLI-SLAM框架有效地弥补了快速运动期间的LiDAR点云扭曲.
- 紧密融合的UWB距离和惯性数据增强了长期SLAM准确性和稳定性.
- 该系统为复杂,未绘制区域的自主机器人提供了高精度的绘图功能.
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