Calibration of multi-sensor fusion for autonomous vehicle system

Calibrating a platform with multiple sensors is a fundamental work for autonomous vehicle systems. This paper proposes an effective multi-sensor calibration method which consists of three aspects: single-sensor intrinsic calibration, multi-sensor extrinsic calibration and multi-sensor time synchronisation. Involved sensors in our proposed approach include LiDAR, Camera and Inertial Measurement Unit (IMU). Firstly, a motion model based method is proposed to calibrate the intrinsic parameters of the IMU. Secondly, besides using the distance factor of the laser beam to develop the intrinsic parameters calibration method of LiDAR, we also introduce the idea of frangibility to optimise the calibration parameters. The results of these two stages give the initial state information of the sensors for latter calibration. Thirdly, based on the idea of hand-eye calibration, we design an external parameter calibration method to estimate the actual external parameters for a multi-sensor system. Experiment results show the practical validity of the proposed algorithm.