Search and tracking in 3D space using a species based particle swarm optimizer

It is challenging for a group of Unmanned Aerial Vehicles (UAVs), termed as blue swarms, to successfully search for, and track, anonymous UAVs, termed as red swarms, that has unknown heterogeneous dynamic behavior. In this paper we propose a novel sub-swarming technique for a blue swarm of UAVs that attempts to achieve this aim within a predefined bounded region. A Species-based Particle Swarm Optimizer (SPSO) is used to coordinate the blue swarm, while Levy flight random walk is incorporated to enhance the search process. Once a red UAV is detected a blue sub-swarm is autonomously formed to track the detected UAV, while the rest of the blue swarm continues the search process. Results from a series of simulations demonstrate that the proposed solution is capable of finding and tracking red UAVs effectively within a bounded environment.