Comparison of Distributed Ad-Hoc Network Planning Algorithms for Autonomous Flying Robots

Abstract

The constraints of current monitoring systems, such as stationary data loggers, wired sensor arrays, manned reconnaissance aircraft or remote sensing by means of satellites, have prompted extensive research in wireless sensor networks. Consequently, the use of Unmanned Aerial Vehicles (UAV) for aerial exploration enables the introduction of aerial sensor networks. In this paper we focus on the development of communication aware steering strategies for UAV swarms to achieve quick and comprehensive Spatial Exploration Ratio while maintaining connectivity within the swarm. We develop, enhance and compare two new random based steering strategies, namely Smart Cube and Cooperative RepellingWalk. Our results show that the proposed algorithms simultaneously attain an efficient equilibrium for the mesh connectivity, sensor perception and distribution in the aerial network. Considering autonomous communication awareness enhances the exploration efficiency in terms of swarm coherence and subsequently reliability.