An inverse square root filter for robust indoor/outdoor magneto-visual-inertial odometry

We explore a new sensor suite to provide a precise and robust navigation information, primarily intended for pedestrian localisation. We use an IMU sensor augmented with an array of magnetometers, called MIMU (for Magneto-Inertial measurement Unit) hereafter, and a single central camera as the vision sensor. The MIMU sensor has been shown in previous work to significantly improve the inertial dead-reckoning for pedestrian, provided we can assume a stationary and non-uniform magnetic environment. Such conditions are encountered in particular in indoor environment, where visual methods can be challenged by textureless or low-light areas. Alternatively, visual methods are useful in outdoor trajectories, where MIMU often fails because of a uniform magnetic field. We build a fusion estimator based on an inverse square-root filter fed with the raw measurement from magnetometers, accelerometers, gyrometers and visual features extracted and tracked in the video. Real-data experiments show the benefits of the fusion : on the one hand, the added information from the MIMU allows to complement the vision/inertial system in case where the vision does not provide useful information during an extended period of time; on the other hand, vision does extend the operational domain of the navigation system compared to a pure MIMU solution, in particular for outdoor sections of the trajectory.