Social networks as a task allocation tool for multi-robot teams

The last decade saw a renewed interest in the field of robotics research and a shift in research focus. In the eighties and early nineties, the focus of robotic research was on finding optimal robot architectures, often resulting in non-cognitive, insectlike entities. In recent years, the processing power available to embedded autonomous agents (robots) has improved and this development has allowed for more complex robot architectures. The focus has shifted from single robot to multi-robot teams. The key to the full utilisation of multi-robot teams lies in coordination. Although a robot is a special case of an agent, many existing multi-agent coordination techniques could not be directly ported to multi-robot teams. In this paper, we overview mainstream multi-robot coordination techniques and propose a new approach to coordination, based on models of organisational sociology, namely social networks. The social network based approach relies on trust and kinship relationships, modified for use in heterogeneous multi-robot teams. The proposed task allocation mechanism is then tested using two approaches: the multi-robot team task allocation simulation and a more realistic coordination problem in simulated robot environments. For the purpose of these two tests, two robotic simulators were developed. The social networks based task allocation algorithm has performed according to expectations and the obtained results are very promising. Although it is applied to simulated multi-robot teams, the proposed coordination model is not robot specific, but can also be applied to any multi-agent system without major modifications.