Free-Form Coverage Path Planning of Quadcopter Swarms for Search and Rescue Missions Using Multi-Objective Optimization

Unmanned aerial vehicles have become affordable and adaptable tools for various real-world applications, in which path planning is often a crucial component. Consequently, this paper introduces a novel approach to Coverage Path Planning for UAVs, aiming to optimize paths without restricting their shape. Unlike existing methods, the proposed approach focuses on generating free-form paths. The method employs a multi-objective evolutionary algorithm grounded in graph-based path planning principles. The application scenario involves a search and rescue mission in forestry terrain, considering prior knowledge about forest density and the target's probable location. The optimization goal is twofold: minimize the chance of not finding the target, while keeping the resulting paths short.