Behaviour-based decentralised cooperative control for unmanned systems

Abstract

The study of swarm intelligence has provided researchers with powerful tools to apply biological inspired problem solving techniques to the cooperative control of multi-agent systems. The coordination mechanism based on interactions among the lower lever components makes the solution more flexible, robust, adaptive and scalable when compared to a centralised approach. The previous research that applied swarm methodology was limited to relative simple scenarios. The objective of this thesis is twofold: first, to explore the feasibility of using a decentralised framework to coordinate a group of agents in complex mission scenarios; and second, to identify the areas of development that can have the maximum impact on the performance of the swarm. The primary contribution of this research is the development and analysis of a behaviour-based cooperative controller for unmanned systems. In the cooperative moving target engagement problem, the proposed controller enables each Unmanned Aerial Vehicle (UAV) to switch between multiple behaviour states, each of which contains a set of rules. The rules control the agent level interactions through the combination of direct interaction and indirect interaction and assign the UAVs to time-dependant cooperative tasks. The simulation results that are presented demonstrate the applicability of the method and indicate that the performance depends on the complexity of the coupled task constraints. A predictive model was then integrated into the controller to let the agents estimate the intentions of their neighbours and choose activities which enhance the overall team utility. Additionally the same methodology is used to address the problem of repositioning a spacecraft within a swarm in order to balance the fuel consumption of the individual spacecraft. The proposed controller guides the spacecraft in the high-fuel-consumption positions to switch with those in the low-fuel consumption positions. The coordination is driven by the local environment without explicit external communication. From the simulation data, an extension of mission lifetime can be observed. This research extends the current literature on swarm intelligent systems by considering complex mission scenarios. A deeper understanding of the performance of the decentralised controllers is developed from the analysis of the results.