Panoramic Visual-Inertial SLAM Tightly Coupled with a Wheel Encoder

Abstract

This paper presents a panoramic visual-inertial simultaneous localization and mapping (SLAM) system that is tightly coupled with a wheel encoder, which can be used in a mobile mapping system (MMS), robot, or driverless car. The whole SLAM system is made up of four modules: 1) measurement preprocessing; 2) system initialization; 3) tracking; and 4) local mapping. The core of the system is the combined adjustment we propose for the observations of the panoramic camera, inertial measurement unit (IMU), and wheel encoder, to optimize the system state, which includes the rotation, translation, velocity, IMU bias, and local map point coordinates in the initialization, tracking, and local mapping modules. In the preprocessing, the most important contribution is that we derive the wheel preintegration based on a two-wheel differential model, which combines the many wheel measurements between two frames into a single relative motion constraint. A novel initialization algorithm is also introduced, which can be divided into two steps: 1) the first step is to initialize the visual scale and parameters of the IMU; and 2) the second step is to perform the combined adjustment for the camera, IMU, and preintegrated wheel encoder data, to refine the initial parameters. The proposed panoramic camera-IMU-wheel SLAM (PIW-SLAM) system can achieve high-precision and robust localization in challenging scenes through multi-sensor fusion. We validated the performance of the proposed system on seven different challenging data sequences from the University of Michigan North Campus Long-Term Vision and LiDAR Dataset (NCLT) dataset. The results showed that the PIW-SLAM system has a higher localization accuracy than the other state-of-the-art SLAM systems, and it also showed a superior robustness in various complex environments. We also verified the accuracy of the scale obtained by the initialization algorithm. Furthermore, we confirmed the performance of the proposed PIW-SLAM system in a wide-baseline scene of the ground motion measurement system.