A Novel, Efficient and Accurate Method for Lidar Camera Calibration
Zhanhong Huang, Xiao Zhang, Antony García, Xinming Huang
Abstract
As autonomous systems evolve, the precise calibration of lidar and camera sensors remains a pivotal concern. Among the myriad of available techniques, target-based calibration methods, which employ planar boards with distinct geometry and image patterns, have been a popular choice. These methods simplify the task of extracting corresponding features between the image and lidar point cloud. But many of these approaches also face a significant challenge, which is their sensitivity to lidar resolution and Field of View (FOV), which may degrade the reliability of the calibration results. Therefore, our research introduces a novel calibration method using a uniquely designed acrylic checkerboard which allows the lidar beam to pass through the white grids and reflect back from the black grids. This innovative technique sidesteps the common challenges associated with lidar feature extraction. Our method’s distinct advantage lies in its ability to perform accurate calibrations at close distances, owing to the efficient feature extraction from both lidar and camera sensors. This novel, efficient, and accurate method can provide state-of-the-art results for camera lidar calibration in the field. Please also check our Github repository: https://github.com/WPI-APA-Lab/Acrylic-Board-Lidar-Camera-Calibration