Methods for the efficient deployment and coordination of swarm robotic systems

Swarming has been observed in many animal species, including fish, birds, insects and mammals. These biological observations have inspired mathematical models of distributed coordination that have been applied to the development of multi-agent robotic systems, such as collections of unmanned autonomous vehicles (UAVs). The advantages of a swarming approach to distributed coordination are clear: each agent acts according to a simple set of rules that can be implemented on resource-constrained devices, and so it becomes feasible to replicate agents in order to build more resilient systems. However, there remain significant challenges in making the approach practicable. This thesis addresses two of the most significant: coordination and scalability. New coordination algorithms are proposed here, all of which manage the problem of scalability by requiring only local proximity sensing between agents, without the need for any other communications infrastructure. A major source of inefficiency in the deployment of a swarm is ‘oscillation’: small movements of agents that arise as a side effect of the application of their rules but which are not strictly necessary in order to satisfy the overall system function. The thesis introduces a new metric for ‘oscillation’ that allows it to be identified and measured in swarm control algorithms. A new perimeter detection mechanism is introduced and applied to the coordination of goal-based swarms. The mechanism is used to improve the internal coordination of agents whilst maintaining a directional focus to the swarm; this is then analysed using the new metric. A mechanism is proposed to allow a swarm to exhibit a ‘healing’ behaviour by identifying internal perimeter edges (doughnuts) and then altering the movement of agents, based upon a simple criterion, to remove the holes; this also has the emergent effect of smoothing the outer edges of a swarm and creating a more uniform swarm structure. Area coverage is an important requirement in many swarm applications. Two new, efficient area-filling techniques are introduced here and exit conditions are identified to determine when a swarm has filled an area. In summary, the thesis makes significant contributions to the analysis and design of efficient control algorithms for the coordination of large scale swarms.