Extrinsic calibration and usage of a single-point laser rangefinder and single camera

Abstract

Laser and visual imagery have been broadly utilized in computer vision and mobile robotics applications because these sensors provide complementary information. So we focus attention on the fusion of 1-D laser rangefinder and camera. However, finding the transformation between the camera and the 1-D laser rangefinder is the first necessary step for the fusion of information. Many algorithms have been proposed to calibrate camera and 2-D or 3-D laser rangefinder, but few methods for 1-D laser rangefinder. In this paper, we propose a robust extrinsic calibration algorithm that is implemented easily and has small calibration error. Due to the 1-D laser rangefinder only returns a data in one dimension direction, it is difficult to build geometric constraint equations like 2-D laser rangefinder. So we are no longer constrained to build constraint equations to finish calibration. Due to the spot of the single-point laser rangefinder we commonly use is mostly invisible, we can determine the full calibration even without observing the laser rangefinder observation point in the camera image. We evaluate the proposed method demonstrating the efficiency and good behavior under noise. Finally we calibrate the installation error of camera utilizing the calibration result.