Autonomous Self-Reconfiguration of Modular Robots by Evolving a Hierarchical Mechanochemical Model

In this paper, we present a two-layer hierarchical mechanochemical model for self-reconfiguration of modular robots in changing environments. The model, which is inspired by the embryonic development of multi-cellular organisms and chemical morphogenesis, can autonomously generate and form different patterns for modular robots to adapt to environmental changes. Layer 1 of the model utilizes a virtual-cell based mechanochemical model to generate appropriate target patterns (i.e., chemical blueprints) for current environment. Layer 2 is a gene regulatory network (GRN) based controller to -coordinate the modules of modular robots for physically realizing the chemical target pattern defined by the first layer. This hierarchical mechanochemical framework is a distributed system in that each module makes decisions based on its local perceptions. To optimize pattern de-sign of modular robots, the covariance matrix adaptation evolution strategy (CMA-ES) is adopted to evolve the pattern parameters of the mechanochemical model. Simulation results demonstrate that the proposed system is effective and robust in autonomously reconfiguring modular robots to adapt to environmental changes.

[1]  Nikolaus Hansen,et al.  Completely Derandomized Self-Adaptation in Evolution Strategies , 2001, Evolutionary Computation.

[2]  Frédéric Gruau,et al.  Genetic Synthesis of Modular Neural Networks , 1993, ICGA.

[3]  Wei-Min Shen,et al.  Transformation of Control in Congruent Self-Reconfigurable Robot Topologies , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Daniela Rus,et al.  Miche: Modular Shape Formation by Self-Dissasembly , 2007, ICRA.

[5]  Henrik Hautop Lund,et al.  Modular ATRON: modules for a self-reconfigurable robot , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[6]  R. Brent,et al.  Modelling cellular behaviour , 2001, Nature.

[7]  Dario Floreano,et al.  Genetic Representation and Evolvability of Modular Neural Controllers , 2010, IEEE Computational Intelligence Magazine.

[8]  Mark Moll,et al.  SUPERBOT: A Deployable, Multi-Functional, and Modular Self-Reconfigurable Robotic System , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Mark Moll,et al.  Distributed Control of the Center of Mass of a Modular Robot , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Yan Meng,et al.  Analysis of local communication load in shape formation of a distributed morphogenetic swarm robotic system , 2010, IEEE Congress on Evolutionary Computation.

[11]  Kevin Kelly,et al.  Out of Control: The New Biology of Machines, Social Systems, and the Economic World , 1992 .

[12]  Serge Kernbach,et al.  Symbiotic Multi-Robot Organisms - Reliability, Adaptability, Evolution , 2010, Cognitive Systems Monographs.

[13]  Hod Lipson,et al.  Three Dimensional Stochastic Reconfiguration of Modular Robots , 2005, Robotics: Science and Systems.

[14]  Yaochu Jin,et al.  A cellular mechanism for multi-robot construction via evolutionary multi-objective optimization of a gene regulatory network , 2009, Biosyst..

[15]  Wei-Min Shen,et al.  Multimode locomotion via SuperBot reconfigurable robots , 2006, Auton. Robots.

[16]  Eiichi Yoshida,et al.  Self-Repairing Mechanical Systems , 1999, Optics East.

[17]  U. Alon.  Network motifs: theory and experimental approaches , 2007, Nature Reviews Genetics.

[18]  Satoshi Murata,et al.  Distributed Self-Reconfiguration of M-TRAN III Modular Robotic System , 2008, Int. J. Robotics Res..

[19]  Hiroki Sayama.  Application notes: robust morphogenesis of robotic swarms , 2010 .

[20]  Hidde de Jong,et al.  Modeling and Simulation of Genetic Regulatory Systems: A Literature Review , 2002, J. Comput. Biol..

[21]  Yan Meng,et al.  A Morphogenetic Approach to Self-Reconfigurable Modular Robots using a Hybrid Hierarchical Gene Regulatory Network , 2010, ALIFE.

[22]  Petros Koumoutsakos,et al.  Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) , 2003, Evolutionary Computation.

[23]  Yan Meng,et al.  Morphogenetic Robotics: An Emerging New Field in Developmental Robotics , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[24]  Ying Zhang,et al.  Limbless Conforming Gaits with Modular Robots , 2004, ISER.

[25]  Hod Lipson,et al.  Molecubes: An Open-Source Modular Robotics Kit , 2007 .

[26]  Aristid Lindenmayer,et al.  Mathematical Models for Cellular Interactions in Development , 1968 .

[27]  Philip K. Maini,et al.  Mechanochemical models for generating biological pattern and form in development , 1988 .

[28]  Kasper Støy,et al.  Using cellular automata and gradients to control self-reconfiguration , 2006, Robotics Auton. Syst..

[29]  Stefano Nolfi,et al.  The Facilitatory Role of Linguistic Instructions on Developing Manipulation Skills , 2010, IEEE Computational Intelligence Magazine.

[30]  Jeffrey L. Krichmar,et al.  Evolutionary robotics: The biology, intelligence, and technology of self-organizing machines , 2001, Complex..

[31]  Wei-Min Shen,et al.  Hormone-inspired adaptive communication and distributed control for CONRO self-reconfigurable robots , 2002, IEEE Trans. Robotics Autom..

[32]  Yaochu Jin,et al.  A morphogenetic self-organization algorithm for swarm robotic systems using relative position information , 2010, 2010 UK Workshop on Computational Intelligence (UKCI).

[33]  D. Murray.  Modeling Biological Pattern Formation in Embryology , 2003 .

[34]  Iuliu Vasilescu,et al.  Miche: Modular Shape Formation by Self-Disassembly , 2008, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[35]  Eiichi Yoshida,et al.  Distributed adaptive locomotion by a modular robotic system, M-TRAN II , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[36]  L. Munari.  How the body shapes the way we think — a new view of intelligence , 2009 .

[37]  Lewis Wolpert,et al.  Principles of Development , 1997 .

[38]  Chih-Han Yu,et al.  Self-adapting modular robotics: A generalized distributed consensus framework , 2009, 2009 IEEE International Conference on Robotics and Automation.

[39]  Eiichi Yoshida,et al.  Planning behaviors of a modular robot: an approach applying a randomized planner to coherent structure , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[40]  H. Kurokawa,et al.  Distributed self-reconfiguration control of modular robot M-TRAN , 2005, IEEE International Conference Mechatronics and Automation, 2005.

[41]  Aude Billard,et al.  Roombots: Reconfigurable Robots for Adaptive Furniture , 2010, IEEE Computational Intelligence Magazine.

[42]  Chih-Han Yu,et al.  Morpho: A self-deformable modular robot inspired by cellular structure , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[43]  Pradeep K. Khosla,et al.  A Modular Self-Reconfigurable Bipartite Robotic System: Implementation and Motion Planning , 2001, Auton. Robots.