Coalition Formation for Multiple UAVs Cooperative Search and Attack with Communication Constraints in Unknown Environment

A coalition formation algorithm is presented with limited communication ranges and delays in unknown environment, for the performance of multiple heterogeneous unmanned aerial vehicles (UAVs) in cooperative search and attack missions. The mathematic model of coalition formation is built on basis of the minimum attacking time and the minimum coalition size with satisfying resources and simultaneous strikes requirements. A communication protocol based on maximum number of hops is developed to determine the potential coalition members in dynamic network. A multistage sub-optimal coalition formation algorithm (MSOCFA) with polynomial time is established. The performances of MSOCFA and particle swarm optimization (PSO) algorithms are compared in terms of complexity, mission performance and computational time. A complex scenario is deployed to illustrate how the coalitions are formed and validate the feasibility of the MSOCFA. The effect of communication constraints (hop delay and max-hops) on mission performance is studied. The results show that it is beneficial to determine potential coalition members in a wide and deep range over the network in the presence of less delay. However, when the delays are significant, it is more advantageous to determine coalitions from among the immediate neighbors.