College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China.
Sensors (Basel). 2023 Mar 14;23(6):3119. doi: 10.3390/s23063119.
Calibration of sensors is critical for the precise functioning of lidar-IMU systems. However, the accuracy of the system can be compromised if motion distortion is not considered. This study proposes a novel uncontrolled two-step iterative calibration algorithm that eliminates motion distortion and improves the accuracy of lidar-IMU systems. Initially, the algorithm corrects the distortion of rotational motion by matching the original inter-frame point cloud. Then, the point cloud is further matched with IMU after the prediction of attitude. The algorithm performs iterative motion distortion correction and rotation matrix calculation to obtain high-precision calibration results. In comparison with existing algorithms, the proposed algorithm boasts high accuracy, robustness, and efficiency. This high-precision calibration result can benefit a wide range of acquisition platforms, including handheld, unmanned ground vehicle (UGV), and backpack lidar-IMU systems.
传感器的校准对于 lidar-IMU 系统的精确运行至关重要。然而，如果不考虑运动失真，系统的准确性可能会受到影响。本研究提出了一种新颖的无控制两步迭代校准算法，可消除运动失真，提高 lidar-IMU 系统的准确性。该算法首先通过匹配原始帧间点云来校正旋转运动的失真。然后，在预测姿态后，将点云与 IMU 进一步匹配。该算法通过迭代运动失真校正和旋转矩阵计算来获得高精度的校准结果。与现有算法相比，该算法具有高精度、鲁棒性和高效率的优点。这种高精度的校准结果可以应用于多种采集平台，包括手持、无人地面车辆 (UGV) 和背包 lidar-IMU 系统。
