UAS Swarm Shares Survey Data to Expedite Coordinated Mapping of Radiation Hotspots

Abstract

This study explores the capability of an Unmanned Aircraft System (UAS) swarm to locate and survey areas of interest as quickly as possible. The swarming process involves decentralized control in which UAS periodically select their respective paths after sharing information sensed in their environment. The implementation of a new swarming algorithm, Greedy Share&Seek, was found to be capable of conducting time-sensitive survey missions with higher performance than a baseline algorithm without such information sharing. Numerical simulations were employed to verify the increase in performance of the algorithm in a controlled environment. In addition, the behavior was implemented on an actual UAS swarm system and successfully demonstrated in a live outdoor flight test in which the system surveyed an active radiation site using on-board sensors. This approach generally worked and demonstrated realworld implementation feasibility.