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紧密结合的激光雷达 - 惯性计数和地底环境的绘图
Jianhong Chen1, Hongwei Wang1, Shan Yang1
1School of Resources and Safety Engineering, Central South University, Changsha 410083, China.
Sensors (Basel, Switzerland)
|August 12, 2023
概括
这项研究介绍了用于自动地下机器人的LiDAR-Inertial测距系统. 该系统在具有挑战性的地下环境中显著提高了定位和绘图准确性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 自主系统 自主系统
- 地理空间绘制地图
背景情况:
- 在地下环境中对自主勘探的需求日益增加.
- 在地下环境中精确地定位和绘制机器人的挑战.
- 在非结构化和动态的地下空间中需要强大的测距系统.
研究的目的:
- 开发和评估用于地下机器人导航的紧密合的LiDAR-惯性测距系统.
- 提高地下环境中自主绘图和定位的准确性和稳定性.
- 为了应对尘埃,空间变化和地下数据中的传感器噪声所带来的挑战.
主要方法:
- 实施了一个紧密合的LiDAR-惯性测距系统.
- 使用NanoGICP进行点云注册和IMU预集成,并进行增量平滑和映射.
- 采用适应性voxel过器用于点云处理和除尘颗粒.
- 集成的IMU预集成用于运动校正和初始LiDAR测距估计.
- 应用扫描到地图注册用于精细的姿势估计和IMU偏差估计.
主要成果:
- 在地下数据集中实现了显著的性能提升,根平均平方误差 (RMSE) 减少了多达50-60%.
- 与现有方法相比,在定位和映射方面表现出更好的准确性.
- 在来自DARPA地下 (SubT) 挑战的各种数据集上验证了系统的有效性.
结论:
- 拟议的LiDAR-惯性测距系统为地下环境中的自主导航提供了强大而准确的解决方案.
- 纳米GICP和IMU预集的集成有效地处理传感器扭曲和环境复杂性.
- 该系统显示了在具有挑战性的地下领域推进机器人探索和绘图的巨大潜力.
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