Creative Swarms for Wireless Network Assistance in Restricted Environments

Swarm robotics investigates mechanisms for simple robots to work together on complex tasks; similar to biological insects. This thesis develops novel approaches to increase the adaptability of robotic swarms, allowing their operation in challenging environments. The three novel works explore: -behaviour creation, using evolutionary computation to evolve new behaviours; -behaviour adjustment, learning to utilise existing behaviours ; and -behaviour selection, using machine learning and other classification techniques to appropriately select behaviours for a given environment. These works are applied to a wireless communication task, having the swarm transport data between disconnected networking devices when traditional methods are unavailable.