Optimal trajectory UAV path design based on bezier curves with multi-hop cluster selection in wireless networks

In the past decade, multi-UAV systems have gained significant attention and companies from in various fields. The main aims of growing such are able to operate a coordinated way complicated situations. To encompass increase speed applications, this research proposed optimization with intelligence. existing work, it does not detect collision effectively. Particle Swarm Optimization algorithm based on fast matching square is for flightpath planning Multi-UAVs used. A distributed full coverage optimal route design derived using particle swarm (PSO) technique, trajectory planner built utilizing dynamic fitness function. We applied PSO technique every UAV individually achieve active fitness, maximizing function while reducing cost novelty work selecting data. Fast FM2 helps avoid collisions between paths. suggested method generates an path multi-UAVs updates maps swarms UAVs. According experimental findings, PSO-FM2 outperforms previous FOA aspects convergence accuracy. Finally, compared algorithms as MSFOA PSO.