Insect Pheromone Strategy for the Robots Coordination

Article Preview

Abstract:

Insect colony inspires scientists for years to create similar behavior in the robotic application. The main goal of our work was to develop simple and powerful algorithm which will accept dynamically changes in the size of a robot swarm due the mission. This algorithm is suitable for situations where unpredictable conditions may lead to robot fault in multi-robotics system and mission completion is endangered. In this article we would like to investigate properties of a simple pheromone based algorithm. The algorithm operates as cellular automata and partially uses an insect pheromone strategy for the robots coordination. Our abstract model is a decentralized adaptive system with a shared memory which represents the environment.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

163-171

Citation:

Online since:

August 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] K.S. Senthilkumar, K.K. Bharadwaj: Multi-robot exploration and terrain coverage in an unknown environment, Robotics and Autonomous Systems, Volume 60, Issue 1, January 2012, pp.123-132, ISSN 0921-8890.

DOI: 10.1016/j.robot.2011.09.005

Google Scholar

[2] Noa Agmon, Noam Hazon, Gal A. Kaminka: The giving tree: constructing trees for efficient offline and online multi-robot coverage, Annals of Mathematics and Artificial Intelligence, Volume 52, Issue 2-4, April 2008, pp . 143-168, ISSN 1012-2443, DOI: 10. 1007/s10472-009-9121-1.

DOI: 10.1007/s10472-009-9121-1

Google Scholar

[3] John A. Sauter , Robert Matthews , H. Van , Dyke Parunak , Sven A. Brueckner: Performance of Digital Pheromones for Swarming Vehicle Control, In Proceedings of Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems, ACM Press, 2005, pp.903-910.

DOI: 10.1145/1082473.1082610

Google Scholar

[4] Miguel Julia Cristobal: Autonomous Exploration and Mapping of Unknown Environments with Teams of Mobile Robots: http: /dspace. umh. es/bitstream/11000/1370/1/Miguel%20Julia%20-%20Autonomous%20Exploration%20and%20Mapping. pdf (available: Feb. 2014).

Google Scholar

[5] A. Zelinsky and R. A. Jarvis and J. C. Byrne and S. Yuta: Planning Paths of Complete Coverage of an Unstructured Environment by a Mobile Robot, In Proceedings of International Conference on Advanced Robotics, 1993, p.533 – 538.

Google Scholar

[6] Sven Koenig, Boleslaw Szymanski, Yaxin Liu: Efficient and inefficient ant coverage methods, Annals of Mathematics and Artificial Intelligence, Volume 31, Issue 1-4, 10-2001, pp.41-76, ISSN: 1012-2443, DOI: 10. 1023/A: 1016665115585.

DOI: 10.1023/a:1016665115585

Google Scholar