Monocular Reactive Collision Avoidance Based on Force Fields for Enhancing the Teleoperation of MAVs

Abstract

The teleoperation of aerial vehicles can be onerous for naive operators unless the robot is endowed with some autonomy, including sense-and-avoid capabilities. This ensures a safe and smooth navigation even in case of users' lack of experience or distraction. In this paper, we propose a reactive collision avoidance strategy that allows a micro aerial vehicle (MAV) to autonomously avoid obstacles while being steered by an operator. We assume that the only available measurements come from an onboard RGB camera and we adopt a collision avoidance strategy based on virtual force fields. A U-Net is used to estimate the depth map starting from RGB images. Simulations conducted in several different outdoor environments validate the proposed approach.