In the field of automatic driving, the combination of 3D LIDAR and inertial measurement unit (IMU) is a common sensor configuration scheme in laser point-cloud localization, high-precision map making and point-cloud target detection. So it is critical to calibrate LIDAR and IMU accurately. At present, due to the large volume and high cost of 3D LIDAR with high-line-number(Such as 64 lines or 128 lines), the configuration scheme of using multiple low-line-number 3D LIDARs appears in the automatic driving vehicle sensing system. However, the common calibration methods are not suitable for multi 3D LIDARs and IMU parameters calibration on autonomous vehicle, which have the disadvantages of cumbersome implementation and low accuracy. In this paper, a joint calibration test platform composed of dual LIDARs and IMU is assembled, and a method of precise automatic calibration based on GPS/RTK data is proposed. Firstly, the initial parameters of the main 3D LIDAR and IMU are obtained by hand-eye calibration method, and then the motion distortion of the point cloud are removed by using the pose information. After global and local optimization of nearest neighbor error, the conversion parameters from the main LIDAR to IMU are obtained. Then, the remaining LIDARs are calibrated with the main LIDAR by combining coarse registration and fine registration, and finally realize the automatic calibration of external parameters of the entire system. The experimental results show that the proposed method has high calibration accuracy for the system composed of multiple 3D LIDARs and IMU, and the calibration effect is stable.
