Rendezvous Trajectory Planning for Air-Launched UAV Swarms Using Wind Energy

Air-launched deployments of Unmanned Aerial Vehicle (UAV) swarms cause a broad spatial distribution among members, resulting inconsistencies in potential energy and wind conditions during flight. To optimize flight performance during swarm rendezvous, this paper proposes a trajectory planning method that enables members harvest wind energy. Integrate wind energy harvesting strategies for single vehicles with the spatial-temporal coordination of the swarm system. This strategy efficiently manages wind, mechanical, and electrical energies, thereby extending their endurance and range. This method is formulated using the Optimal Control Problem (OCP) framework, considering the dynamics of the swarm system. To ensure control input continuity and trajectory feasibility, the method incorporates constraints on thrust and its increment, which reduces the number of collocation points and lessens computational burden when the OCP is converted into a Nonlinear Programming (NLP) problem for solving. The optimal trajectory of a single UAV is employed as the initial guess to accelerate convergence and enhance solution global optimality. The trajectory planning results demonstrate that, to achieve mechanical energy consistency during the rendezvous process, members with differing initial potential energies after air-launch employ independent wind energy harvesting strategies to compensate for trajectory energy costs. This method optimally plans collaborative trajectories for multiple vehicles within spatiotemporal constraints, significantly broadening their reachable domain. The comprehensive management of energy reserves from air-launched vehicles, including potential and electrical energy, along with the harvesting of wind energy, can significantly extend the range and endurance of air-launched swarm missions.