Biologically inspired decision making for collective robotic systems

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.