Energy-Efficient Path-Planning for UAV Swarm Based Missions: A Genetic Algorithm Approach

In all applications involving swarms, it's crucial for the group to achieve its objectives safely and with efficient energy utilisation, while adhering to constraints and meeting mission requirements. This article focuses on addressing the offline path planning problem for Unmanned Aerial Vehicles (UAVs), with a specific emphasis on enhancing energy efficiency. Each UAV in the swarm is guided along a candidate path represented by a Bézier curve, which evolves through a two-step procedure. Firstly, a genetic algorithm (GA) normalises the fitness function to ensure fair comparison of traits. Secondly, a multi-objective swarm-based path planning approach is employed to find the most energy-efficient and safe route for the swarm, meeting predefined criteria. The designed solution paths accommodate the functional and physical limitations of aerial vehicles, while also considering factors such as vessel traffic and weather conditions in the operational area. Simulation examples demonstrate the effectiveness of this approach.