Automatic Calibration of Dual-LiDARs Using Two Poles Stickered with Retro-Reflective Tape
This addresses the calibration challenge for autonomous vehicle perception systems, offering a more practical solution than existing methods that rely on specific markers or user input, though it is incremental in improving flexibility and accuracy.
The paper tackles the problem of calibrating multi-LiDAR systems for autonomous vehicles by introducing an automatic method using two poles with retro-reflective tape, achieving higher accuracy and better flexibility compared to state-of-the-art approaches.
Multi-LiDAR systems have been prevalently applied in modern autonomous vehicles to render a broad view of the environments. The rapid development of 5G wireless technologies has brought a breakthrough for current cellular vehicle-to-everything (C-V2X) applications. Therefore, a novel localization and perception system in which multiple LiDARs are mounted around cities for autonomous vehicles has been proposed. However, the existing calibration methods require specific hard-to-move markers, ego-motion, or good initial values given by users. In this paper, we present a novel approach that enables automatic multi-LiDAR calibration using two poles stickered with retro-reflective tape. This method does not depend on prior environmental information, initial values of the extrinsic parameters, or movable platforms like a car. We analyze the LiDAR-pole model, verify the feasibility of the algorithm through simulation data, and present a simple method to measure the calibration errors w.r.t the ground truth. Experimental results demonstrate that our approach gains better flexibility and higher accuracy when compared with the state-of-the-art approach.