Automatic Targetless Monocular Camera and LiDAR External Parameter Calibration Method for Mobile Robots

Abstract

With the continuous development and popularization of sensor-fusion technology for mobile robots, the application of camera and light detection and ranging (LiDAR) fusion perception has become particularly important. Moreover, the calibration of extrinsic parameters between the camera and LiDAR is a crucial prerequisite for fusion. Although traditional target-based calibration methods have been widely adopted, their cumbersome operation and high costs necessitate the development of more efficient and flexible calibration methods. To address this problem, this study proposed a two-stage calibration method based on motion and edge matching. In the first stage, the preliminary estimation of the extrinsic parameters between the camera and LiDAR was performed by matching visual odometry and LiDAR odometry using a hand–eye target method. In the second stage, the calibration results from the first stage were further refined by matching the image edges and discontinuous depth point clouds. The calibration system was then tested in both simulated and actual environments. The experimental results showed that this method, which did not require specially structured targets, could achieve highly flexible and robust automated calibration. Compared to other advanced methods, the accuracy of the proposed method was higher.

Keywords

• calibration
• extrinsic parameters
• edge matching
• sensor-fusion technology
• mobile robots