Evolving Coverage Behaviours For MAVs Using NEAT

James Butterworth (University of Liverpool), Bastian Broecker (University of Liverpool), Karl Tuyls (University of Liverpool & Google DeepMind), Paolo Paoletti (University of Liverpool)

Abstract

Dynamic coverage-the problem of covering an area evenly and continuously in order to visit all areas of interest-is an important procedure to optimise for any autonomous surveillance system. This work introduces a novel solution to the multi-agent version of this problem in that it achieves high performance in a completely decentralised manner with no reliance on GPS. It does so by using NEAT [12] to optimise agent neural controllers. The controllers are first realised via simulation and then transferred to Micro-Aerial Vehicles (MAVs). The MAVs are modified to include a Ultra-wideband Frequency (UWB) chip which use radio waves to communicate inter drone distances to one another.