Dynamic Mission Control for UAV Swarm via Task Stimulus Approach

Interest in self-organized (SO), multi-robotic systems is increasing because of their flexibility, robustness, and scalability in performing complex tasks. This paper describes a decentralized task allocation model based on both task stimulus intensity and a responding threshold. The response threshold method was developed through observations of social insects. It allows a swarm of insects with a relatively low-level of intelligence to perform complex tasks. In this work, an agent based simulation environment is developed incorporating these ideas. The mission scenario simulated in this study is a wide area search and destroy mission in an initially unknown environment. The mission objectives are to effectively allocate a UAV swarm to both optimize coverage of the search space and attack a target. Rule based behaviours were used to create UAV formations. Two sets of simulations with different swarm size and target numbers were performed. The simulation results show that with task stimulus intensity and a responding threshold, the UAV swarm demonstrates emergent behaviour and individual vehicles respond adaptively to the changing environment.