Title: Multiple mobile robots system with network-based subsumption architecture

Authors: Fusaomi Nagata; Akimasa Otsuka; Keigo Watanabe; Maki K. Habib

Addresses: Department of Mechanical Engineering, Faculty of Engineering, Tokyo University of Science, 1-1-1 Daigaku-Dori, Sanyo-Onoda 756-0884, Yamaguchi, Japan ' Department of Mechanical Engineering, Faculty of Engineering, Tokyo University of Science, 1-1-1 Daigaku-Dori, Sanyo-Onoda 756-0884, Yamaguchi, Japan ' Department of Systems Engineering, Faculty of Engineering, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan ' Mechanical Engineering Department, School of Sciences and Engineering, American University in Cairo, 113, Kasr El Eini St., P.O. Box 2511, Cairo 11511, Egypt

Abstract: In this paper, a unique multiple mobile robots system is proposed to enable engineering students and engineers in the field to efficiently learn subsumption architecture and develop swarm intelligence. The subsumption architecture is known as one of the behaviour-based artificial intelligence. Each of multiple mobile robots within the system has three wheels driven by DC motors and six position sensitive detector (PSD) sensors. Network-based subsumption architecture is considered to realise a schooling behaviour by using only information from the PSD sensors. Further, a server supervisory control is introduced for poor hardware platforms with limitations of software development, i.e., the mobile robots can only behave based on the most simply subdivided reaction behaviours, i.e., reflex actions, generated from agents. Experimental results show interesting behaviour among the multiple mobile robots, such as following, avoidance and schooling.

Keywords: multiple robots; multi-robot systems; mobile robots; network-based subsumption architecture; mechatronics education; PSD sensors; position sensitive detector; behaviour-based AI; artificial intelligence; engineering education; swarm intelligence; swarm robots; robot sensors; schooling behaviour; supervisory control; path following; obstacle avoidance.

DOI: 10.1504/IJMMS.2013.052784

International Journal of Mechatronics and Manufacturing Systems, 2013 Vol.6 No.1, pp.57 - 71

Received: 16 Apr 2012
Accepted: 24 Oct 2012

Published online: 12 Jul 2014 *

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