High-Precision External Parameter Calibration Method for Camera and Lidar Based on a Calibration Device

Abstract

The fusion of camera and lidar plays an important role in the field of robotic perception. The accurate external parameter calibration is a necessary prerequisite for sensor fusion. Herein, an auxiliary calibration device with distinctive geometric features was designed to address the problems of low accuracy and poor robustness associated with external parameter calibrations of camera and lidar. Moreover, a coarse-to-fine two-stage calibration method was proposed for the external parameters of the camera and lidar. The first stage of the method is the extraction of multiple groups of two-dimensional (2D) and three-dimensional (3D) lines corresponding to the edge of the calibration device from the image and lidar point cloud that yields a unique initial estimation of the external parameters. In the second stage, the 2D–3D center point of the sphere of the calibration device was detected, and the initial external parameters were further optimized using a nonlinear optimization method. The proposed method provides two different features that add stability against noise to the calibration system. Both simulated and actual experiments show that the method can yield high-precision external parameters without an initial value. Compared to state-of-the-art methods, our method has advantages in terms of accuracy. the calibration system has a certain degree of noise resistance and stability under different laser noise and vertical resolution.

Keywords

• Calibration device
• camera and lidar fusion
• external parameter calibration
• nonlinear optimization