Enhance Pose and Extrinsic Accuracy With Online Spatial and Temporal Compensation in Monocular Camera-Aided GNSS/SINS Integration

Abstract

Continuous, reliable, and accurate pose estimation is the basis for perception, planning, and control, which are parts of an autonomous vehicle system or a mobile robot system. For complementarity to each other, the global navigation satellite system (GNSS) can achieve accurate pose solutions in many cases after being integrated with the strap-down inertial navigation system (SINS), which can be further enhanced via fusing visual information. However, unmodeled errors will be introduced in the multi-sensor fusion system by inaccurate spatial parameters caused by coarse calibration or slight changes in mechanical structure. Moreover, an unsynchronized temporal relationship will also influence the pose and extrinsic accuracies. To reduce the negative influence brought by spatial and temporal misalignment, we propose a monocular camera-aided GNSS/SINS integration system with online spatial and temporal compensation, where the time delay and extrinsic of SINS and camera will be estimated and compensated online together with the SINS state. The influence of temporal compensation and GNSS information on extrinsic accuracy is analyzed with a Monte Carlo simulation. The Monte Carlo simulation demonstrates that the extrinsic accuracy improves by 31.33% and 70.00% for rotation and translation after adding temporal compensation and GNSS information. Additionally, the performance of the proposed multi-sensor fusion system is analyzed with two real-world experiments. The position accuracy improves by 19.16%~31.04% in both experiments, which further reveals that online spatial-temporal compensation can significantly improve the pose accuracy of the fusion system.