Formation solution for heterogeneous swarm of UAVs and MAVs in crowded environment

Unmanned aerial vehicles (UAVs) and micro aerial vehicles (MAVs) gain more attraction in swarm applications as their cost reduces and their availability increases. Heterogeneous swarm solutions where these different types of aerial vehicles share the same environment is an intriguing problem encountered in reconnaissance, surveillance and collaborative navigation missions. For heterogeneous swarms sharing the same workspace, rapidly extracting a collision-free and optimal formation in a congested environment including obstacles becomes a crucial optimization problem. Methods based on particle swarm optimization (PSO) are popular. nPSO is a variant of PSO that exhibits more rapid convergence compared to traditional counterparts. This paper solves the problem of optimal collision free positioning for heterogeneous swarm of different numbers of UAVs and MAVs in the presence of obstacles using nPSO algorithm. The area covered and the number of vehicles are optimized. The results demonstrate that in no more than 800 iterations, a near-optimal solution for formation of heterogeneous swarm of UAVs and MAVs can be achieved in an environment crowded with different types of obstacles.