Cue-based aggregation with a mobile robot swarm: a novel fuzzy-based method

Aggregation in swarm robotics is referred to as the gathering of spatially distributed robots into a single aggregate. Aggregation can be classified as cue-based or self-organized. In cue-based aggregation, there is a cue in the environment that points to the aggregation area, whereas in self-organized aggregation no cue is present. In this paper, we proposed a novel fuzzy-based method for cue-based aggregation based on the state-of-the-art BEECLUST algorithm. In particular, we proposed three different methods: naïve, that uses a deterministic decision-making mechanism; vector-averaging, using a vectorial summation of all perceived inputs; and fuzzy, that uses a fuzzy logic controller. We used different experiment settings: one-source and two-source environments with static and dynamic conditions to compare all the methods. We observed that the fuzzy method outperformed all the other methods and it is the most robust method against noise.

[1]  Heiko Hamann Towards Swarm Calculus: Universal Properties of Swarm Performance and Collective Decisions , 2012, ANTS.

[2]  Ali Emre Turgut,et al.  Fuzzy-Based Aggregation with a Mobile Robot Swarm , 2012, ANTS.

[3]  Simon A. Levin,et al.  Frontiers in Mathematical Biology , 1995 .

[4]  Juan Luis Castro,et al.  Fuzzy logic controllers are universal approximators , 1995, IEEE Trans. Syst. Man Cybern..

[5]  Hong Zhang,et al.  Collective Robotics: From Social Insects to Robots , 1993, Adapt. Behav..

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

[7]  Richard Vaughan,et al.  Massively multi-robot simulation in stage , 2008, Swarm Intelligence.

[8]  Guy Theraulaz,et al.  Self-Organized Aggregation Triggers Collective Decision Making in a Group of Cockroach-Like Robots , 2009, Adapt. Behav..

[9]  Erol Sahin,et al.  Probabilistic aggregation strategies in swarm robotic systems , 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

[10]  Duc Truong Pham,et al.  Fuzzy-logic-based behaviour coordination in a multi-robot system , 2004 .

[11]  Guy Theraulaz,et al.  The Embodiment of Cockroach Aggregation Behavior in a Group of Micro-robots , 2008, Artificial Life.

[12]  Richard L. Scheaffer,et al.  Probability and statistics for engineers , 1986 .

[13]  Ali Emre Turgut,et al.  Self-organized flocking in mobile robot swarms , 2008, Swarm Intelligence.

[14]  Marco Dorigo,et al.  Evolving Aggregation Behaviors in a Swarm of Robots , 2003, ECAL.

[15]  Eliseo Ferrante,et al.  Swarm robotics: a review from the swarm engineering perspective , 2013, Swarm Intelligence.

[16]  Farshad Arvin,et al.  Encoderless position estimation and error correction techniques for miniature mobile robots , 2013 .

[17]  L. Edelstein-Keshet,et al.  Complexity, pattern, and evolutionary trade-offs in animal aggregation. , 1999, Science.

[18]  Serge Kernbach,et al.  Get in touch: cooperative decision making based on robot-to-robot collisions , 2009, Autonomous Agents and Multi-Agent Systems.

[19]  A. Ōkubo,et al.  MODELLING SOCIAL ANIMAL AGGREGATIONS , 1994 .

[20]  Yoshiki Uchikawa,et al.  A variable ordinal structure model for fuzzy reasoning and its application to decision problem of working order , 1991, Proceedings IECON '91: 1991 International Conference on Industrial Electronics, Control and Instrumentation.

[21]  Erol Şahin,et al.  Aggregation in Swarm Robotic Systems: Evolution and Probabilistic Control , 2007 .

[22]  Abdul Rahman Ramli,et al.  Development of IR-based short-range communication techniques for swarm robot applications , 2010 .

[23]  Alcherio Martinoli,et al.  Aggregation-mediated collective perception and action in a group of miniature robots , 2010, AAMAS.

[24]  Abdul Rahman Ramli,et al.  Imitation of Honeybee Aggregation with Collective Behavior of Swarm Robots , 2011, Int. J. Comput. Intell. Syst..

[25]  Meng Wang,et al.  Fuzzy logic-based real-time robot navigation in unknown environment with dead ends , 2008, Robotics Auton. Syst..

[26]  S Erol Swarm Robotics: From Sources of Inspiration to Domains of Application , 2005 .

[27]  Chris Melhuish,et al.  An interactive method for controlling group size in multiple mobile robot systems , 1997, 1997 8th International Conference on Advanced Robotics. Proceedings. ICAR'97.

[28]  Farshad Arvin,et al.  A Real-Time Note Transcription Technique Using Static and Dynamic Window Sizes , 2009, 2009 International Conference on Signal Acquisition and Processing.

[29]  M. Dorigo,et al.  Self-Organized Discrimination of Resources , 2011, PloS one.

[30]  Paul S. Schenker,et al.  CAMPOUT: a control architecture for multirobot planetary outposts , 2000, SPIE Optics East.

[31]  Thomas Schmickl,et al.  Beeclust: A Swarm Algorithm Derived from Honeybees Derivation of the Algorithm, Analysis by Mathematical Models and Implementation on a Robot Swarm , 2011 .

[32]  Wouter-Jan Rappel,et al.  Self-organized Vortex State in Two-Dimensional Dictyostelium Dynamics , 1998, patt-sol/9811001.

[33]  John Tyler Bonner,et al.  A DESCRIPTIVE STUDY OF THE DEVELOPMENT OF THE SLIME MOLD DICTYOSTELIUM DISCOIDEUM , 1944 .

[34]  Suzana Dragicevic,et al.  A fuzzy-constrained cellular automata model of forest insect infestations , 2006 .

[35]  Abdul Rahman Ramli,et al.  Development of a miniature robot for swarm robotic application , 2009 .

[36]  F Mondada,et al.  Social Integration of Robots into Groups of Cockroaches to Control Self-Organized Choices , 2007, Science.

[37]  Herbert Heran,et al.  Untersuchungen über den Temperatursinn der Honigbiene (Apis mellifica) unter besonderer Berücksichtigung der Wahrnehmung strahlender Wärme , 1952, Zeitschrift für vergleichende Physiologie.

[38]  Serge Kernbach,et al.  Re-embodiment of Honeybee Aggregation Behavior in an Artificial Micro-Robotic System , 2009, Adapt. Behav..

[39]  Syamsiah Mashohor,et al.  A highly interpretable fuzzy rule base using ordinal structure for obstacle avoidance of mobile robot , 2011, Appl. Soft Comput..

[40]  Richard James,et al.  Mechanisms for aggregation in animals: rule success depends on ecological variables , 2008 .

[41]  J. Deneubourg,et al.  Self-organized aggregation in cockroaches , 2005, Animal Behaviour.

[42]  Shigeki Ishikawa,et al.  A method of indoor mobile robot navigation by using fuzzy control , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.