Hierarchical Cooperative Assignment Algorithm (CAA) for mission and path planning of multiple fixed-wing UAVs based on maximum independent sets

Mission planning can be solved as a combinatorial optimization problem which involves computing the path and selecting the agents that will be assigned to a given task. In scenarios with multiple UAVs, the proper control of the vehicle to achieve the proposed path is also a relevant task. This paper proposes a solution to the mission planning problem that involves probabilistic search and optimization of path planning and a graph-based combinatorial solution of task assignment. In addition, we propose an invariant model predictive controller based on the SO(2) manifold to deal with the execution of UAV missions. Our results demonstrate that the algorithm is capable of assigning all agents to tasks and computing a viable and smooth trajectory for the UAVs to follow. Also, the control strategy is capable of guiding the vehicle through the trajectories generated from a start position to the task location.