Coco-LIC: Continuous-Time Tightly-Coupled LiDAR-Inertial-Camera Odometry using Non-Uniform B-spline

In this paper, we propose an efficient continuous-time LiDAR-Inertial-Camera Odometry, utilizing non-uniform B-splines to tightly couple measurements from the LiDAR, IMU, and camera. contrast uniform B-spline-based methods, our B-spline approach offers significant advantages in terms of achieving real-time efficiency high accuracy. This is accomplished by dynamically adaptively placing control points, taking into account varying dynamics motion. To enable fusion heterogeneous data within a short sliding-window optimization, assign depth visual pixels using corresponding map points global LiDAR map, formulate frame-to-map reprojection factors for associated current image frame. way circumvents necessity optimization pixels, which typically entails lengthy sliding window with numerous trajectory estimation. We conduct dedicated experiments on real-world datasets demonstrate advantage efficacy adopting representation. Our odometry system also extensively evaluated both challenging scenarios sensor degenerations large-scale scenarios, has shown comparable or higher accuracy than state-of-the-art methods. The codebase paper will be open-sourced at https://github.com/APRIL-ZJU/Coco-LIC.