Robust Visual-Inertial State Estimation with Multiple Odometries and Efficient Mapping on an MAV with Ultra-Wide FOV Stereo Vision

Abstract

The here presented flying system uses two pairs of wide-angle stereo cameras and maps a large area of interest in a short amount of time. We present a multicopter system equipped with two pairs of wide-angle stereo cameras and an inertial measurement unit (IMU) for robust visual-inertial navigation and time-efficient omni-directional 3D mapping. The four cameras cover a 240 degree stereo field of view (FOV) vertically, which makes the system also suitable for cramped and confined environments like caves. In our approach, we synthesize eight virtual pinhole cameras from four wide-angle cameras. Each of the resulting four synthesized pinhole stereo systems provides input to an independent visual odometry (VO). Subsequently, the four individual motion estimates are fused with data from an IMU, based on their consistency with the state estimation. We describe the configuration and image processing of the vision system as well as the sensor fusion and mapping pipeline on board the MAV. We demonstrate the robustness of our multi-VO approach for visual-inertial navigation and present results of a 3D-mapping experiment.