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在高度动态的环境中,基于索引点和延迟移除策略的LiDAR惯性计数
1College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China.
Sensors (Basel, Switzerland)
|June 10, 2023
概括
本研究介绍了ID-LIO,这是一种新的LiDAR惯性测距系统,可以在动态环境中增强同时定位和映射 (SLAM). 它通过有效地处理移动的物体,显著提高了定位的准确性.
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) 对自主系统至关重要.
- 带有移动物体的动态环境对传统的SLAM算法构成重大挑战.
- 现有的LiDAR惯性测距方法在含有众多移动实体的场景中难以准确.
研究的目的:
- 开发一种新的LiDAR惯性测距框架 (ID-LIO) 用于在动态环境中强大的SLAM.
- 在面对移动物体时,提高定位和映射系统的准确性和可靠性.
- 通过结合先进的动态点处理技术,以LIO-SAM框架为基础.
主要方法:
- 提出了一个动态点检测方法,在空间维度上使用伪占用.
- 开发了一个基于索引点的动态点传播和移除算法,用于时间地图更新.
- 实现了延迟删除历史关键和动态加权在滑动窗口优化中的延迟删除策略.
主要成果:
- 拟议的ID-LIO框架显示,在高度动态的环境中,本地化准确度显著提高.
- 与LIO-SAM相比,实现了绝对轨迹误差 (ATE) 和根平均平方误差 (RMSE) 的实质性减少.
- 在公共数据集上的实验结果验证了动态点处理策略的有效性.
结论:
- ID-LIO为动态环境所带来的SLAM挑战提供了一个强大的解决方案.
- 新的动态点管理技术有效地减轻移动物体引入的错误.
- 这一框架代表了LiDAR惯性测距领域的重大进步,用于现实世界的应用.
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