A Decentralized Pattern Formation and Navigation Approach For Swarms: Multi-UAV Perspective

This paper proposes a decentralized formation control approach for the swarm of Unmanned Aerial Vehicles (UAVs). The system requires no predefined leaders and followers, and only local information is needed to control the individual UAV. In the proposed algorithm, each UAV motion constitutes local information such as pose and velocities shared with several other closest neighbors using the Nearest Neighbour Search (NNS) algorithm. The proposed approach leveraged a 3D mapping technique known as OctoMap for mapping unknown terrain and uses a variant of Rapid Exploration Random Trees (RRT*) algorithm with path length minimization as optimization objective for UAVs swarm path planning and navigation. We found that our proposed approach can be applied in a hazardous environment where an extensive area needs to be covered for search and rescue missions. The proposed algorithm is tested and validated with three different experiments on a dynamic simulator showing promising results.