Biologically inspired decision making for collective robotic systems

Abstract

Practical collective robotic systems likely will be confronted with problems which have more than one unique solution. When deciding on which of a set of candidate solutions to a problem to pursue, a collective system should ensure that its members reach a unanimous decision regarding which solution to implement so that the system itself does not split apart with different members pursuing different solutions. If such a split were to occur, much of the collective system's functionality could be lost. In this paper, we present a unique approach to collective decision making that is based on an algorithm employed by a particular species of ant when it chooses a new nest site. We expand the ants' algorithm into a general purpose decision making scheme and apply it to the collective relocation problem. A detailed study of the performance of our decision making algorithm was carried out in simulation using the collective relocation task as a test bed. Consistent system performance was observed across three robot populations. It was found that one particular system variable, the decision quorum threshold played a large role in determining the system's behaviour and that system behaviour was maximized when this variable was set to 50% of the system's population.