Y. Tong, X. Zhang*, R. Wang, Z. Song, S. Wu, S. Zhang, Y. Wang, J. Yuan. TC²LI-SLAM: A Tightly-Coupled Camera-LiDAR-Inertial SLAM System. IEEE Robotics and Automation Letters (RA-L), 2024, accepted.

Abstract

      In this paper, we propose TC²LI-SLAM, a novel and tightly-coupled camera-LiDAR-inertial SLAM system with a separated front end and a unified back end. The front end accepts non-identical frequency inputs and performs real-time pose estimation while incorporating different inputs into keyframes for the back end, benefiting from our novel keyframe-oriented data synchronization method. To improve the accuracy of the back-end optimization, we innovatively leverage multi-sensor consecutive co-vision constraints in a keyframe-based local bundle adjustment problem.  To bridge the gap between different residual terms from different sensors in the optimization problem, we propose a cross-modal residual standardization method that can be easily applied. Furthermore, the proposed system can degrade into TC²L-SLAM, a tightly-coupled camera-LiDAR SLAM system without IMU, to cope with situations where inertial measurements are not available or reliable. Finally, both TC²LI-SLAM and TC²L-SLAM are tested on public and self-recorded datasets. The results show their superior performance in terms of accuracy compared with the state-of-the-art SLAM systems.