Segregation in swarms of mobile robots based on the Brazil nut effect

— We study a simple algorithm inspired by the Brazil nut effect for achieving segregation in a swarm of mobile robots. The algorithm lets each robot mimic a particle of a certain size and broadcast this information locally. The motion of each particle is controlled by three reactive behaviors: random walk, taxis, and repulsion by other particles. The segregation task requires the swarm to self-organize into a spatial arrangement in which the robots are ranked by particle size (e.g., annular structures or stripes). Using a physics-based computer simulation, we study the segregation performance of swarms of 50 mobile robots. The robots represent particles of three different sizes. We first analyze the problem of how to combine the basic behaviors so as to minimize the percentage of errors in rank. We then show that the system is very robust to noise on inter-robot perception and communication. For a noise level of 50%, the mean percentage of errors in rank is 1%. Moreover, we investig...

• Type: Conference
• Year: 2009
• Where: IROS
• Authors: Roderich Groß, Stéphane Magnenat, Francesco Mondada
• Keywords: IROS 2009, Mean Percentage, Mobile Robots, Robotics, Robots Represent Particles