Resilient Multi-Sensor Exploration of Multifarious Environments with a Team of Aerial Robots

Abstract

We present a coordinated autonomy pipeline for multi-sensor exploration of confined environments. We simultaneously address four broad challenges that are typically overlooked in prior work: (a) make effective use of both range and vision sensing modalities, (b) perform this exploration across a wide range of environments, (c) be resilient to adverse events, and (d) execute this onboard a team of physical robots. Our solution centers around a behavior tree architecture, which adaptively switches between various behaviors involving coordinated exploration and responding to adverse events. Our exploration strategy exploits the benefits of both visual and range sensors with a new frontier-based exploration algorithm. The autonomy pipeline is evaluated with an extensive set of field experiments, with teams of up to 3 robots that fly up to 3 m/s and distances exceeding one kilometer. We provide a summary of various field experiments and detail resilient behaviors that arose: maneuvering narrow doorways, adapting to unexpected environment changes, and emergency landing. We provide an extended discussion of lessons learned, release software as open source, and present a video in the supplementary material.