Alice in Pheromone Land: An Experimental Setup for the Study of Ant-like Robots

The pheromone trail laying and trail following behaviors of ants have proved to be an efficient mechanism to optimize path selection in natural as well as in artificial networks. Despite this efficiency, this mechanism is under-used in collective robotics because of the chemical nature of pheromones. In this paper we present a new experimental setup which allows to investigate with real robots the properties of a robotics systems using such behaviors. To validate our setup, we present the results of an experiment in which a group of 5 robots has to select between two identical alternatives a path linking two different areas. Moreover, a set of computer simulations provides a more complete exploration of the properties of this system. At last, experimental and simulation results lead us to interesting prediction that will be testable in our setup.

[1]  Nikolaos Papanikolopoulos,et al.  Dispersion behaviors for a team of multiple miniature robots , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[2]  R.A. Russell,et al.  Heat trails as short-lived navigational markers for mobile robots , 1997, Proceedings of International Conference on Robotics and Automation.

[3]  Olivier Michel,et al.  Webots: Symbiosis Between Virtual and Real Mobile Robots , 1998, Virtual Worlds.

[4]  B. Webb What does robotics offer animal behaviour? , 2000, Animal Behaviour.

[5]  Marco Dorigo,et al.  Ant algorithms and stigmergy , 2000, Future Gener. Comput. Syst..

[6]  Laurent Keller,et al.  Ant-like task allocation and recruitment in cooperative robots , 2000, Nature.

[7]  Jean-Louis Deneubourg,et al.  From local actions to global tasks: stigmergy and collective robotics , 2000 .

[8]  Guy Theraulaz,et al.  Self-Organization in Biological Systems , 2001, Princeton studies in complexity.

[9]  Roland Siegwart,et al.  Fascination of down scaling — Alice the sugar cube robot , 2001 .

[10]  Chris Melhuish,et al.  Stigmergy, Self-Organization, and Sorting in Collective Robotics , 1999, Artificial Life.

[11]  Francesco Mondada,et al.  Understanding collective aggregation mechanisms: From probabilistic modelling to experiments with real robots , 1999, Robotics Auton. Syst..

[12]  Jean-Louis Deneubourg,et al.  Harvesting by a group of robots , 1992 .

[13]  Ken Sugawara,et al.  Foraging behavior of interacting robots with virtual pheromone , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[14]  J. Deneubourg,et al.  Collective patterns and decision-making , 1989 .

[15]  R. Andrew Russell,et al.  Ant trails - an example for robots to follow? , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[16]  A. Martinoli,et al.  A macroscopic model of an aggregation experiment using embodied agents in groups of time-varying sizes , 2002, IEEE International Conference on Systems, Man and Cybernetics.

[17]  J. Deneubourg,et al.  Modulation of individual behavior and collective decision-making during aggregation site selection by the ant Messor barbarus , 2004, Behavioral Ecology and Sociobiology.

[18]  M. Burd,et al.  Head-on encounter rates and walking speed of foragers in leaf-cutting ant traffic , 2003, Insectes Sociaux.

[19]  David W. Payton,et al.  Pheromone Robotics and the Logic of Virtual Pheromones , 2004, Swarm Robotics.

[20]  B. Webb,et al.  Can robots make good models of biological behaviour? , 2001, Behavioral and Brain Sciences.

[21]  F. Zambonelli,et al.  Spreading Pheromones in Everyday Environments through RFID Technology , 2005 .

[22]  D. Gordon,et al.  What is the function of encounter patterns in ant colonies? , 1993, Animal Behaviour.

[23]  Dirk Helbing,et al.  Optimal traffic organization in ants under crowded conditions , 2004, Nature.

[24]  Marco Dorigo,et al.  Swarm intelligence: from natural to artificial systems , 1999 .

[25]  Guy Theraulaz,et al.  Path efficiency of ant foraging trails in an artificial network. , 2006, Journal of theoretical biology.

[26]  J. Deneubourg,et al.  Self-organized shortcuts in the Argentine ant , 1989, Naturwissenschaften.

[27]  J. Deneubourg,et al.  Collective decision making through food recruitment , 1990, Insectes Sociaux.