Development of Collective Control Architectures for Small Quadruped Robots Based on Human Swarming Behavior

We introduce a method of designing behaviors for swarms of micro-robots based on observation of human beings executing various tasks collectively. As a case study, we have focused on the development of decentralized control strategies specifically applicable to swarms of the Mini-Whegs quadruped robot. The design process consists of carefully mapping hardware requirements for the robotic platforms in question, then tasking large groups (swarms) of human beings to perform mission specific tasks within the constraints of the robotic vehicle. A basic software engine has been developed and implemented to support on-line human swarm experiments in a virtual environment, with subsequent off-line algorithm extraction following for eventual transfer onto robotic platforms. In our ongoing work, a variety of virtual robotic swarm experiments have been performed, and various methods of algorithm extraction explored. Beyond swarm controller development, one of the most useful and practical aspects of this technology is that it enables those involved in micro-robotic research to understand from a first hand perspective the issues involved in performing global tasks with limited sensor information. We believe that the mining of virtual human swarm behaviors will lead to the successful development of control architectures capable of directing microrobot swarms in the field, as well as provide insights into the social behavior of all manner of multi-agent systems.