A New Model for Solving the Simultaneous Object Collecting and Shepherding Problem in Flocking Robots

Ellips Masehian, Mitra Royan

Abstract

Shepherding behavior is a class of collective behaviors in flocking systems which requires that a swarm of mobile robots enter an area populated with known or unknown obstacles, collect a flock of static or dynamic particles (objects), and guide them safely to a predefined goal position. Applications of this behavior are in sheep or duck shepherding and fishing. In this paper, a new algorithmic model is developed for online for-mation control, decision making, behavior selection, and motion planning of a team of homogeneous and anonymous (no leader and follower) flocking robots which simultaneously perform object collecting and shepherding tasks. The model’s architecture is enriched with various complex flocking actions such as flock deformation, flock split and merge, flock expansion, and flock obstacle avoidance. Contributions of this paper include (i) defining a new class of problems for flocking robots called Simultaneous Object Collecting and Shepherding (SOCS) problem, (ii) incorporating online obstacle sensing and avoidance methods in the flocking behavior, and (iii) developing a fuzzy expert system for determining the strategy of environment exploration. The fuzzy inference engine provides an effective way to minimize the time spent on collecting objects while maximizing the gain obtained by object collection, in a way that the flock’s formation and in-tegrity is maintained. The proposed model was implemented on a number of simulations and produced rational and satisfactory results.

References

  1. Bayazit, O., Lien, J. and M. Amato, N., 2002. Simulating Flocking Behaviors in Complex Environments. Proc.of the Pacific Conf on Computer Graphics and Applications.
  2. Brett, J., 2009. Applied Flock Theory, in Scrum Alliance, Available at Http://Www.Agileacademy.Com.Au/ Agile/ Sites/Default/Files/Flock Theory Applied.Pdf.
  3. Christopher, V., Joseph, F. H. and Jyh-Ming, L., 2010. Scalable and Robust Shepherding via Deformable Shapes. in 3rd Int. Conf. on Motion in Games, Nov. 2010, Utrecht, Netherlands.
  4. Garrell, a., Sanfeliu, a. and Moreno-Noguer, F., 2009. Discrete Time Motion Model for Guiding People in Urban Areas using Multiple Robots. IEEE Int. Conf. on Intelligent Robots and Systems, 486-491.
  5. Khatib, O., 1986.Real-Time Obstacle Avoidance for Manipulators and Mobile Manipulators. International Journal of Robotics Research 5(1):90-98.
  6. Kennedy, J., Eberhart, R., 1995. Particle Swarm Optimization. in IEEE Int. Conf. on Neural Networks. IV. 1942- 1948.
  7. Lien, J. M., Rodriguez, S., Malric, J. and Amato, N. M., 2005. Shepherding Behaviors with Multiple Shepherds. in IEEE Int. Conf. on Robotics and Automation.
  8. Manh La, H., Lim, R. and Sheng, W., 2010. Hybrid System of Reinforcement Learning and Flocking Control in Multi-Robot Domain. in 2nd Annual Conference on Theoretical and Applied Computer Science, Stillwater.
  9. Navarro, I., Gutiérrez, a., Matía, F. and MonasterioHuelin, F., 2008. an Approach to Flocking of Robots using Minimal Local Sensing and Common Orientation. Proceedings of 3rd International Workshop on Hybrid Artificial Intelligent Systems, 5271, 616-624.
  10. Reynolds, C. W., 1987. Flocks, Herds, and Schools: a Distributed Behavioral Model. in Computer Graphics, 25-34.
  11. Renzaglia, A. and Martinelli, A., 2010. Potential Field based Approach for Coordinate Exploration with a Multi-Robot Team. in IEEE International Workshop on Safety, Security and Rescue Robotics, 1-6.
  12. Sharma, B., Vanualailai, J. and Chand, U., 2009. Flocking of Multi-Agents in Constrained Environments. European J. of Pure and Applied Math., 2, 401-425.
  13. Tanner, H. G., Jadbabaie, A., and Pappas, G. J., 2003. Stable Flocking of Mobile Agents, Part I: Fixed Topology. Decision and Control, 2010-2015.
  14. Varghese, B., and Mckee, G. T., 2010. a Mathematical Model, Implementation and Study of a Swarm System. Robotics and Autonomous Systems, 58(3): 287-294.
  15. Xiong, N., Li, Y., Park, J. H., Yang, L. T., Yang, Y. and Tao, S., 2008. Fast and Efficient Formation Flocking for a Group of Autonomous Mobile Robots. in IEEE International Symposium on Parallel and Distributed Processing, April 2008, Miami, FL, 1-8.
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Paper Citation


in Harvard Style

Masehian E. and Royan M. (2012). A New Model for Solving the Simultaneous Object Collecting and Shepherding Problem in Flocking Robots . In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 96-105. DOI: 10.5220/0004161600960105


in Bibtex Style

@conference{ecta12,
author={Ellips Masehian and Mitra Royan},
title={A New Model for Solving the Simultaneous Object Collecting and Shepherding Problem in Flocking Robots},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)},
year={2012},
pages={96-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004161600960105},
isbn={978-989-8565-33-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)
TI - A New Model for Solving the Simultaneous Object Collecting and Shepherding Problem in Flocking Robots
SN - 978-989-8565-33-4
AU - Masehian E.
AU - Royan M.
PY - 2012
SP - 96
EP - 105
DO - 10.5220/0004161600960105