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Adaptive swarm robot region coverage using gene regulatory networks

Oh, H and Jin, Y (2014) Adaptive swarm robot region coverage using gene regulatory networks Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8717 L. pp. 197-208.

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Abstract

This paper proposes a morphogenetic pattern formation approach for collective systems to cover a desired region for target entrapment. This has been achieved by combining a two-layer hierarchical gene regulatory network (H-GRN) with a region-based shape control strategy. The upper layer of the H-GRN is for pattern generation that provides a desired region for entrapping targets generated from local sensory inputs of detected targets. This pattern is represented by a set of arc segments, which allow us to form entrapping shape constraints with the minimum information that can be easily used by the lower layer of the H-GRN. The lower layer is for region-based shape control consisting of two steps: guiding all robots into the desired region designated by the upper layer, and maintaining a specified minimum distance between each robot and its neighbouring robots. Numerical simulations have been performed for scenarios containing either static and moving targets to validate the feasibility and benefits of the proposed approach. © 2014 Springer International Publishing.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Computing Science
Authors :
AuthorsEmailORCID
Oh, HUNSPECIFIEDUNSPECIFIED
Jin, YUNSPECIFIEDUNSPECIFIED
Date : 2014
Identification Number : 10.1007/978-3-319-10401-0_18
Additional Information : The original publication is available at http://www.springerlink.com
Depositing User : Symplectic Elements
Date Deposited : 28 Nov 2014 18:53
Last Modified : 16 Jun 2015 13:33
URI: http://epubs.surrey.ac.uk/id/eprint/806703

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