针对16线激光雷达负障碍检测过程中, 垂直分辨率低导致对负障碍检测和识别困难的问题, 提出了一种基于IMU-LiDAR的负障碍检测方法。建立了激光点云数据的融合模型, 有效利用历史点云数据与历史检测结果, 获得较多的环境信息, 提高了负障碍的检测精度。利用16线激光雷达与自研的惯性测量单元(IMU)传感器进行实验验证, 结果表明能够实现激光雷达点云的融合, 进一步提高激光雷达对负障碍的检测能力, 并且以较低的硬件成本实现更加高级的环境感知能力, 对无人驾驶等技术的研究具有实际应用价值。

To solve the problem that the vertical resolution is low when using 16-line LiDAR to realize negative obstacle detection,which leads to the difficulty of negative obstacle detection and recognition, a detection method of negative obstacle based on IMU-LiDAR is proposed.The method establishes a multi-frame LiDAR point cloud data fusion model,which can effectively use previous point cloud data and detection results to obtain more environmental information,and improve the detection accuracy of negative obstacles.The 16-line LiDAR and the self-developed IMU sensor are used to conduct the tests.The results demonstrate that the proposed method can achieve the multi-frame fusion of the LiDAR point cloud,and the detection ability of the LiDAR on negative obstacles can be further improved.A more advanced environment awareness is achieved with lower hardware costs,which shows that the method has practical application value for the study of driverless technology.