Immune Inspired Cooperative Mechanism with Refined Low-level Behaviors for Multi-Robot Shepherding

Razali, Sazalinsyah and Meng, Qinggang and Yang, Shuang-Hua (2012) Immune Inspired Cooperative Mechanism with Refined Low-level Behaviors for Multi-Robot Shepherding. International Journal of Computational Intelligence and Applications, 11 (1). pp. 1250007-1250022. ISSN 1469-0268

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Abstract

In this paper, immune systems and its relationships with multi-robot shepherding problems are discussed. The proposed algorithm is based on immune network theories that have many similarities with the multi-robot systems domain. The underlying immune inspired cooperative mechanism of the algorithm is simulated and evaluated. The paper also describes a refinement of the memory-based immune network that enhances a robot’s action-selection process. A refined model, which is based on the Immune Network T-cell-regulated—with Memory (INT-M) model, is applied to the dog-sheep scenario. The refinements involves the low-level behaviors of the robot dogs, namely shepherds’ formation and shepherds’ approach. These behaviors would make the shepherds to form a line behind the group of sheep and also obey a safety zone of each flock, thus achieving better control of the flock and minimize flock separation occurrences. Simulation experiments are conducted on the Player/Stage robotics platform.

Item Type:	Article
Additional Information:	Electronic version of an article published as International Journal of Computational Intelligence and Applications, Vol. 11, No. 1, 2012, pp. 1250007–1250022 DOI: 10.1142/S1469026812500071 © copyright World Scientific Publishing Company http://www.worldscinet.com/ijcia/
Uncontrolled Keywords:	memory-based immune systems; immune network; multi-robot cooperation; shepherding
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QR Microbiology > QR180 Immunology
Divisions:	Faculty of Information and Communication Technology > Department of Industrial Computing
Depositing User:	Dr. Sazalinsyah Razali
Date Deposited:	14 Nov 2012 15:13
Last Modified:	29 Sep 2021 00:06
URI:	http://eprints.utem.edu.my/id/eprint/183
Statistic Details:	View Download Statistic

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