Real-time mesh-based scene estimation for aerial inspection

With society and industry pushing for robot-assisted systems to automate cumbersome tasks, such as inspection and maintenance, a vast amount of research effort has been dedicated to relevant technologies. Right at the forefront are small Unmanned Aerial Vehicles (UAVs) equipped with onboard cameras, recently demonstrating that vision-based autonomous flights without reliance on GPS are possible, sparking great interest in a plethora of areas. Current solutions, however, still lack in portability and generality struggling to perform outside the controlled laboratory environment, with onboard robotic perception constituting the biggest impediment. Driven by the need for real-time denser scene estimation, in this work we present a dramatically cheap approach enabling estimation of the immediate surroundings of a UAV using the inertial and visual cues from a single onboard camera. Instead of following the recent trend towards dense scene reconstruction, we trade detail of reconstruction for efficiency of estimation, albeit without compromising accuracy. We also present ETHZ CAB building dataset for aerial inspection. We present results against scene ground truth obtained by a millimetre-precise laser scanner.