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Biosystems. 2009 Dec;98(3):193-203. doi: 10.1016/j.biosystems.2009.05.003. Epub 2009 May 13.

A cellular mechanism for multi-robot construction via evolutionary multi-objective optimization of a gene regulatory network.

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Department of Electrical and Computer Engineering, Stevens Institute of Technology, NJ 07030, USA.


A major research challenge of multi-robot systems is to predict the emerging behaviors from the local interactions of the individual agents. Biological systems can generate robust and complex behaviors through relatively simple local interactions in a world characterized by rapid changes, high uncertainty, infinite richness, and limited availability of information. Gene Regulatory Networks (GRNs) play a central role in understanding natural evolution and development of biological organisms from cells. In this paper, inspired by biological organisms, we propose a distributed GRN-based algorithm for a multi-robot construction task. Through this algorithm, multiple robots can self-organize autonomously into different predefined shapes, and self-reorganize adaptively under dynamic environments. This developmental process is evolved using a multi-objective optimization algorithm to achieve a shorter travel distance and less convergence time. Furthermore, a theoretical proof of the system's convergence is also provided. Various case studies have been conducted in the simulation, and the results show the efficiency and convergence of the proposed method.

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