A Tightly-Coupled and Keyframe-Based Visual-Inertial-Lidar Odometry System for UGVs With Adaptive Sensor Reliability Evaluation

In this article, a novel visual-inertial-lidar odometry (VILO) system named TCK-VILO is proposed to assist unmanned ground vehicles in reaching high localization performance. We introduce an adaptive sensor reliability evaluation method to configure weights of visual and lidar measurements dynamically in the backend optimization, which can improve both the accuracy and robustness of the localization in real-world outdoor scenarios. A two-stage initialization method is proposed to initialize the system by solving the spatio-temporal alignment of system states. In the TCK-VILO system, a lightweight frontend is designed to update system states while lidar or visual data is fed into the system, and then a tightly-coupled and keyframe-based backend is used to refine system states. We evaluate the proposed TCK-VILO pipeline on the public Newer College dataset and a self-collected real-world dataset. Experimental results show that our system can achieve low drifts in various challenging scenes and outperforms competing state-of-the-art VILO systems.