基于IMU和LiDAR融合感知的数字地形建设研究
Chen Huang1,2, Yiqi Wang1, Xiaoqiang Sun1
1Institute of Automotive Engineering, Jiangsu University, Zhenjiang 212013, China.
Sensors (Basel, Switzerland)
|January 11, 2025
概括
这项研究引入了一种新方法,将惯性测量单元 (IMU) 和LiDAR数据融合在一起,以准确地绘制道路表面的高度. 开发的系统增强了对车辆的地形构造和道路数据提取.
科学领域:
- 机器人技术和自主系统
- 地理空间数据科学数据科学
- 传感器融合技术的技术
背景情况:
- 光探测和测距 (LiDAR) 传感器在准确捕捉道路表面的高度方面存在局限性,特别是在车辆前面.
- 现有的方法往往难以精确地形数据提取,影响自主导航和道路状况监测.
- 整合多种传感器模式对于克服个人传感器的弱点至关重要.
研究的目的:
- 通过融合惯性测量单元 (IMU) 和LiDAR数据,开发一种新的数字地形建设方案.
- 为了提高沿着车辆轨迹提取道路表面高度信息的准确性和有效性.
- 改进状态估计和绘图架构,以实时地形感知.
主要方法:
- 双传感器坐标系统的配置和LiDAR和IMU参数的校准.
- 为地形建设建立一个融合感知系统,优化状态估计和绘制地图.
- 在点云数据处理中应用一个类似移动平均线的算法,具有不同的滑动窗口宽度.
主要成果:
- 成功实施了集成IMU和LiDAR数据的地形施工系统.
- 确定一个4厘米的滑动窗口宽度是处理点云数据的最佳选择.
- 在提取的道路表面高度数据的准确性和有效性方面取得了显著的改进.
结论:
- 拟议的IMU和LiDAR数据的融合有效地解决了LiDAR在道路表面高度提取方面的局限性.
- 优化的地形施工系统和数据处理算法提供了更准确和可靠的道路高度信息.
- 这种方法提供了一个强大的解决方案,以提高车辆的感知和自动驾驶能力.
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