INS/LIDAR/立体SLAM集成用于在GNSS拒绝环境中的精确导航
Nader Abdelaziz1,2, Ahmed El-Rabbany1
1Department of Civil Engineering, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada.
Sensors (Basel, Switzerland)
|September 9, 2023
概括
本研究介绍了一种综合导航系统,结合了惯性导航 (INS),LiDAR和立体视觉 (SLAM),以克服全球导航卫星系统 (GNSS) 的信号损失. 该系统在没有GNSS的情况下显著提高了定位准确性,优于传统方法.
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
- 导航系统 导航系统
背景情况:
- 传统的导航依赖于全球导航卫星系统 (GNSS) /惯性导航系统 (INS) 的整合.
- 只有INS在长时间的GNSS信号中断期间会遭受重大漂移.
- 需要强大的导航解决方案,独立于GNSS信号.
研究的目的:
- 开发一个集成的INS/LiDAR/立体声同时定位和绘图 (SLAM) 导航系统.
- 在没有GNSS的环境中评估系统的性能.
- 与仅使用INS系统相比,提高定位准确性.
主要方法:
- 扩展卡尔曼波器 (EKF) 用于传感器融合.
- EKF首先将INS与LiDAR数据集成在一起,然后是立体SLAM.
- 该系统在各种城市和农村驾驶场景中在KITTI数据集上进行了测试.
主要成果:
- 拟议的INS/LiDAR/立体声SLAM系统在没有GNSS的情况下证明了优越的位置估计.
- 平方根平均误差 (RMSE) 水平降低了83%,垂直降低了82%.
- 该系统在定位准确性方面超过了几种最先进的算法.
结论:
- 集成的INS/LiDAR/立体声SLAM为无GNSS导航提供了一个强大的解决方案.
- 拟议的基于EKF的融合显著提高了定位准确性.
- 这种方法为在具有挑战性的环境中可靠导航提供了可行的替代方案.
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