Simultaneous Mapping Localization and Path Planning for UAV Swarm

The ability to control a swarm of Unmanned Aerial Vehicle (UAV) with minimal human intervention open new areas for autonomous UAV and drone applications. These applications include collaborative crop monitoring, aerial transportation, offshore delivery, facility monitoring, disaster relieve as well as search and rescue. Current UAV operations are heavily dependent on human operators that require each UAV to be controlled by dedicated safety pilot as well as a separate payload operator which limits the efficient use of UAVs required in envisaged swarm applications. Thus, there is an imperative to mature high autonomy guidance and navigation technologies to allow UAV swarm operations. This paper explores UAV swarm navigation and control strategies that allow higher levels of autonomy for a reliable UAV swarm operation. This paper presented the novel strategies developed in performing simultaneous swarm mapping, swarm search, and swarm path planning. The methods developed can be easily scaled up or down to adapt to different number of UAVs in a swarm for any application. The developed strategies are implemented and tested with Monte-Carlo simulations for a search and rescue type mission. The results from these simulation experiments have shown comparable achievements on the performance and robustness when compared to optimal control strategy.