A Collaborative Relative Localization Method for Vehicles using Vision and LiDAR Sensors

Yanhao Li, Hao Li

Abstract: Inter-vehicle relative localization is essential to various multi-vehicle collaborative tasks such as environment perception augmentation, long range path planning and communication-assisted driving applications. We propose a real-time collaborative relative localization framework to estimate inter-vehicle poses via vision and LiDAR sensors. The vision sensor is used for inter-vehicle pose initialization, whereas the LiDAR sensor is used for SLAM and pose refinement. A comparative study between our proposed method and a representative baseline method based on ORB-SLAM2-stereo is performed in the CARLA simulator, which demonstrates advantages of the proposed method in terms of accuracy and robustness in real-time operation.