LIRO: Tightly Coupled Lidar-Inertia-Ranging Odometry

In recent years, thanks to the continuously reduced cost and weight of 3D lidar, the applications of this type of sensor in the community have become increasingly popular. Despite many progresses, estimation drift and tracking loss are still prevalent concerns associated with these systems. However, in theory these issues can be resolved with the use of some observations to fixed landmarks in the operation environments. This motivates us to investigate a sensor fusion scheme of lidar and inertia measurements with Ultra-Wideband (UWB) range measurements to such landmarks, which can be easily deployed in the environments with minimal cost and time. Hence, data from IMU, lidar and UWB are tightly-coupled with the robot's states on a sliding window based on their timestamps. Then, we construct a cost function comprising of factors from UWB, lidar and IMU preintegration measurements. Finally an optimization process is carried out to estimate the robot's position and orientation. It is demonstrated through some real world experiments that the method can effectively resolve the drift issue, while only requiring two or three anchors deployed in the environment.