Infrastructureless indoor navigation with an hybrid magneto inertial and depth sensor system
We present a novel visual magneto inertial system for pedestrian indoor navigation. It includes magnetic, inertial and depth sensors integrated into a device that can be hand held by a pedestrian. Our method builds upon a magneto inertial tachymeter that is able to accurately reconstruct body speed in presence of magnetic gradient and a depth registration algorithm for computing inter image movement. We propose a simple fusion strategy using the magneto inertial tachymeter in the predition step and the depth image registration in the correction step. We demonstrate accurate reconstruction of indoor trajectories in infrastructureless environments, with a drift often below one percent of the length of the trajectory. We emphasize the benefit of the proposed hybrid system in situations where the 3D environment is too simple, making depth registration useless, or situations where the magnetic environment lead to failure of the magneto inertial tachymetry.
2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN)