Group escape behavior of multiple mobile robot system by mimicking fish schools

Cooperative behaviors and control strategies using by animals, birds, fishes and human are usually good examples for designing distributed control architecture of multiple robot team. In last two decades, school behavior of fish was being used as a good model to control multi-mobile robots with local sensing ability and local interaction only, and several research groups have successfully demonstrated distributed control architectures on controlling robot swarm systems via simulations or experiments. Another interesting behavior of fish schools is group escape behavior which shows all fish change their moving directions rapidly without any explicit global communications while some fish sense a predator. In this paper, we proposed a distributed algorithm to perform group escape behavior without inter-robot communication by mimicking behavior of fish schools. This behavior provides an alternate method for a robot team to achieve some emergency tasks while inter-robot communication is restricted. The mechanism of the group escape behavior is introduced, and the characteristics of escape motion state transferring in the swarm are discussed. Some simulation results and experimental results are provided for illustrating the validity of the proposed group escape algorithm.

[1]  A. S. Morse,et al.  Coordination of Groups of Mobile Autonomous Agents , 2004 .

[2]  Jie Lin,et al.  Coordination of groups of mobile autonomous agents using nearest neighbor rules , 2003, IEEE Trans. Autom. Control..

[3]  Steven V. Viscido,et al.  Self-Organized Fish Schools: An Examination of Emergent Properties , 2002, The Biological Bulletin.

[4]  Hayakawa,et al.  Collective motion in a system of motile elements. , 1996, Physical review letters.

[5]  W ReynoldsCraig Flocks, herds and schools: A distributed behavioral model , 1987 .

[6]  B L Partridge,et al.  The structure and function of fish schools. , 1982, Scientific American.

[7]  Dongbing Gu,et al.  Using Fuzzy Logic to Design Separation Function in Flocking Algorithms , 2008, IEEE Transactions on Fuzzy Systems.

[8]  Nak Young Chong,et al.  Flocking Controls for Swarms of Mobile Robots Inspired by Fish Schools , 2008 .

[9]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[10]  Craig W. Reynolds Flocks, herds, and schools: a distributed behavioral model , 1987, SIGGRAPH.

[11]  Tucker R. Balch,et al.  Social potentials for scalable multi-robot formations , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).