Minimum Time Search Path Planning for Multiple Fixed-Wing Unmanned Aerial Vehicles with Adaptive Formation

Planning the flight path for a fleet of fixed-wing unmanned aerial vehicles during search and rescue operations poses a significant challenge as it requires minimizing search time and optimizing the formation of the unmanned aerial vehicles. This paper proposes a novel integration of a leaderfollower formation flight technique for multiple fixed-wing unmanned aerial vehicles with a minimumtime search path planning algorithm. In the first step, the proposed algorithm, based on continuous ant colony optimization, plans a sequence of safe and feasible waypoints for the leader while determining appropriate azimuth angles for the followers. In the next step, the algorithm utilizes a nonlinear threedegree-of-freedom model, developed based on a leader-follower formation flight technique, to plan the followers’ flight paths. Applying Dubins curves based on kinematic constraints of the unmanned aerial vehicles not only reduces computational time but also ensures the feasibility of the best search paths between planned waypoints. Furthermore, in the presence of static obstacles, a developed function in the planning process addresses collision and obstacle avoidance constraints. The effectiveness and performance of the suggested method in detecting targets in minimum-time search missions and the ability of the planner to reconfigure the formation of unmanned aerial vehicles in cluttered environments are demonstrated through comprehensive simulation studies and Monte Carlo analysis .