Adaptive decentralised cooperative vision based simultaneous localization and mapping for multiple UAV

This paper aims to present an Adaptive Decentralized Cooperative Visual Simultaneous Localization and Mapping (AD-CVSLAM) solution based on a stereovision system. With the proposed solution, a group of Unmanned Aerial Vehicles (UAVs) will be able to construct a large reliable map and localize themselves in this map without any user intervention. The robust Nonlinear H− filter is adapted to the multiple vehicle case to ensure a robust Pose estimation; as well a new approach for feature initialization based on an Adaptive Covariance Intersection technique is used. Finally, validation and comparison using simulation data are presented and discussed.