Three-dimensional route planning for multiple unmanned aerial vehicles using Salp Swarm Algorithm

Route planning for multiple Unmanned Aerial Vehicles (UAVs) is a series of translation and rotational steps from given start location to the destination goal location. The route problem determine most optimal avoiding any collisions with obstacles present in environment. an NP-hard optimisation problem. In this paper, newly proposed Salp Swarm Algorithm (SSA) used, its performance compared deterministic other Nature-Inspired Algorithms (NIAs). results illustrate that SSA outperforms all meta-heuristic algorithms UAVs 3D approach improves average cost overall time by 1.25% 6.035%, respectively, when recently reported data. involved many real-life applications like robot navigation, self-driving car, autonomous UAV search rescue operations dangerous ground-zero situations, civilian surveillance, military combat even commercial services package delivery drones.