An Autonomous Loop-Closure Approach for Simultaneous Exploration and Coverage of Unknown Infrastructure Using MAVs

Abstract

The recent proliferation of low-cost Micro Aerial Vehicles (MAV) offers an attractive means for inspecting critical infrastructure autonomously. However, to enable such autonomous tasks requires a precise spatial model of the structure and operational area, typically constructed using sensor measurements obtained from the environment. To facilitate autonomous inspection capabilities, we address the problem of autonomous MAV exploration and coverage of an unknown structure to acquire the spatial information necessary for the development of a high-fidelity 3D model of the structure. Key to this problem is to not only cover the entire structure to acquire a complete set of spatial measurements, but also to minimize accumulative data errors during the exploration through direct planning of loop closures. We introduce a real-time waypoint planning approach to guide MAV motions to achieve complete exploration, coverage, and loop closure while respecting limited onboard resources.