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Adaptive Swarm Robot Region Coverage Using Gene Regulatory Networks

1 Sep 2014
Hyondong Oh, Yaochu Jin
Department of Computing, University of Surrey, Guildford, Surrey, GU2 7XH, UK
Advances in Autonomous Robotics Systems. Lecture Notes in Computer Science. Volume 8717, 2014, pp 197-208
15th Annual Conference, TAROS 2014, Birmingham, UK. September 1-3, 2014. Proceedings 
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.
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