Autonomous Exploration for Infrastructure Modeling with a Micro Aerial Vehicle

Abstract

Micro aerial vehicles (MAVs) are an exciting technology for mobile sens- ing of infrastructure as they can easily position sensors in to hard to reach positions. Although MAVs equipped with 3D sensing are starting to be used in industry, they currently must be remotely controlled by skilled pilot. In this paper we present an exploration path planning approach for MAVs equipped with 3D range sensors like lidar. The only user input that our approach requires is a 3D bounding box around the structure. Our method incrementally plans a path for a MAV to scan all sur- faces of the structure up to a resolution and detects when exploration is finished. We demonstrate our method by modeling a train bridge and show that our method builds 3D models with the efficiency of a skilled pilot.