Cooperative task assignment of heterogeneous unmanned aerial vehicles for simultaneous multi-directional attack on a moving target

Abstract

Multiple unmanned aerial vehicle (UAV) attacks, on moving targets with directional priorities, need careful task allocation especially when the UAVs have variable attacking power. In addition, the constraints of simultaneous attack from different directions multi-folds the complexity of the problem. In this work, an extended contract net protocol (ECNP) based autonomous and cooperative task assignment method is proposed to deal with the time-sensitive position assignment for multi-directional attack and uniform resource allocation. Initially, an optimization problem is formulated using distances between each UAV and expected attack positions (APs), arrival time, and attack power. In addition, for uniform resource allocation, a variable is introduced to monitor available resources at a given time. An agent-based model is built with UAV information, such as position and speed, along with the direction of the high-value moving target (HVMT). Each UAV identifies the possible arrival points based on its speed constraints, and current position, and the position and velocity of HVMT. Moreover, distance and expected arrival time to all APs are computed. Finally, the agents make attack point allocations using the proposed ECNP after making a consensus about simultaneous attack time. The proposed method ensures uniform resource allocation. The simulation results show the superiority of the proposed method (ECNP) in comparison with classical contract net protocol (CNP) and Genetic Algorithms (GA) in terms of uniform resource allocation and mission accomplishment.