Automatic design of stigmergy-based behaviours for robot swarms

Abstract

Stigmergy is a form of indirect communication and coordination in which individuals influence their peers by modifying the environment in various ways, including rearranging objects in space and releasing chemicals. For example, some ant species lay pheromone trails to efficiently navigate between food sources and nests. Besides being used by social animals, stigmergy has also inspired the development of algorithms for combinatorial optimisation and multi-robot systems. In swarm robotics, collective behaviours based on stigmergy have always been designed manually, which is time consuming, costly, hardly repeatable, and depends on the expertise of the designer. Here, we show that stigmergy-based behaviours can be produced via automatic design: an optimisation process based on simulations generates collective behaviours for a group of robots that can lay and sense artificial pheromones. The results of our experiments indicate that the collective behaviours designed automatically are as good as—and in some cases better than—those produced manually. By taking advantage of pheromone-based stigmergy, the automatic design process generated collective behaviours that exhibit spatial organisation, memory, and communication.

Sensory–Motor Loop Adaptation in Boolean Network Robots

“…Furthermore, the adaptive process that we used is analogous to an adaptive walk in a configuration space, which can be considered as a special case of evolutionary algorithms used in robotics. Many results in evolutionary robotics and automatic design of control software for robots have been validated on real robots, for example [ 37 , 38 , 39 , 40 , 41 , 42 ]. Therefore, we are rather confident that the core behavior observed can be also observed when the controller we have studied is implemented on physical robots.…”