A morphogenetic approach to flexible and robust shape formation for swarm robotic systems

Meng, Y, Guo, H and Jin, Y (2013) A morphogenetic approach to flexible and robust shape formation for swarm robotic systems Robotics and Autonomous Systems, 61 (1). pp. 25-38.

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Abstract

Embryonic development of multi-cellular organisms is governed by gene regulatory networks (GRNs), which are a collection of genes that interact with one another and with other chemicals in the cell. Inspired by the morphogenesis of biological organisms, in this paper, we propose a morphogenetic approach using a gene regulatory network (GRN) for swarm robotic systems to form complex shapes in a distributed manner. The target pattern, represented by non-uniform rational B-spline (NURBS), is embedded into the gene regulatory model, analogous to the morphogen gradients in multi-cellular development. Since the total number of robots is unknown to each robot, a dynamic neighborhood adaptation mechanism is proposed to evenly deploy the robots on the boundary of the target pattern. A theoretical proof of the system convergence is provided. Various simulation studies demonstrate that the proposed algorithm offers an effective and robust distributed control mechanism for swarm robotic systems to construct complex shapes. Furthermore, proof-of-concept experiments were successfully undertaken using e-puck mobile robots, which demonstrate that the proposed model works well with physical constraints of real robots. © 2012 Elsevier B.V. All rights reserved.

Item Type:	Article
Divisions :	Faculty of Engineering and Physical Sciences > Computing Science
Authors :	Name Email ORCID Meng, Y Guo, H Jin, Y
Date :	January 2013
DOI :	10.1016/j.robot.2012.09.009
Additional Information :	NOTICE: this is the author’s version of a work that was accepted for publication in Robotics and Autonomous Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Robotics and Autonomous Systems, 61 (1), January 2013, DOI 10.1016/j.robot.2012.09.009.
Depositing User :	Symplectic Elements
Date Deposited :	05 Dec 2014 14:41
Last Modified :	06 Dec 2014 02:33
URI:	http://epubs.surrey.ac.uk/id/eprint/806716

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