Compass aided visual-inertial odometry

Abstract

With the development of vision and optimization techniques, visual-inertial odometry (VIO) has shown the capability of motion estimating in the GNSS-denied condition. The VIO can provide absolute pitch and roll angles estimating value, but no the absolute azimuth. In the paper, we proposed a VIO aided by compass, which can obtain the azimuth with respect to the north direction in the geographic frame. Moreover, aided by compass, the yaw angle estimating error was reduced to a greater degree, due to the measurement of azimuth. Furthermore, the consistency of the VIO backend estimator is improved as well, while the accuracy of the estimated pose states was also wholly improved. The aiding approach is a tightly-couple information fusion system of camera, IMU and magnetoresistive sensors. The optimization method is based on the pre-integration and bundle adjustment. In the paper, we derived the compass residual model based on the pre-integration model, and then its Jacobian and covariance formation were deduced to solve the nonlinear equations. The compass aided VIO software was implemented based on the Nvidia Jetson Tx2. The system was fully tested based on hardware-in-the-loop simulation and vehicle test in the real physical environment. The pose errors of VIOs with and without compass aiding were compared in the above tests. The simulation results showed that the position was and yaw errors were improved obviously; the compass aided VIO was still consistent, but the pure VIO was consistent not. The consistency character is evaluated by average NEES by Monte-Carlo in simulation. The vehicle test showed that the position error was reduced by 23%; the yaw error was reduced by 21%. As a result, the compass aided VIO not only improved the pose estimated accuracy, especially position and yaw, but also improved the consistency of VIO system.