A morphogenetic framework for self-organized multirobot pattern formation and boundary coverage

Authors:
Hongliang Guo;Yaochu Jin;Yan Meng
Affiliations:
Stevens Institute of Technology, Hoboken, NJ;University of Surrey, UK;Stevens Institute of Technology, Hoboken, NJ
Venue:
ACM Transactions on Autonomous and Adaptive Systems (TAAS) - Special section on formal methods in pervasive computing, pervasive adaptation, and self-adaptive systems: Models and algorithms
Year:
2012

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Abstract

Embryonic development of multicellular organisms, also known as morphogenesis, is regarded as a robust self-organization process for pattern generation. Inspired by the recent findings in biology indicating that morphogen gradients, together with a Gene Regulatory Network (GRN), play a key role in biological patterning, we propose a framework for self-organized multirobot pattern formation and boundary coverage based on an artificial GRN model. The proposed framework does not need a global coordinate system, which makes it more practical to be implemented in a physical robotic system. Moreover, an adaptation mechanism is included in the framework so that the self-organization algorithm is robust to changes in the number of robots. Various case studies of multirobot pattern formation and boundary coverage show the effectiveness of the framework.