Membrane Computing in Robotics

This paper presents a new computational paradigm which can be successfully applied in robotics for the control of autonomous mobile robots. Membrane computing is a naturally parallel and distributed model of computation inspired by the structure and functioning of living cells. Numerical P systems, a type of membrane systems which operates with numerical values, and the extension, enzymatic numerical P systems, were used for modeling robot behaviors. Current results and developments of this innovative approach are also discussed and analyzed.

[1]  Catalin Buiu,et al.  Development of membrane controllers for mobile robots , 2012, Inf. Sci..

[2]  Vincenzo Manca,et al.  A Methodology Based on MP Theory for Gene Expression Analysis , 2011, Int. Conf. on Membrane Computing.

[3]  Gheorghe Paun,et al.  Membrane Computing and Economics: Numerical P Systems , 2006, Fundam. Informaticae.

[4]  Mario J. Pérez-Jiménez,et al.  Modeling Population Growth of Pyrenean Chamois (Rupicapra p. pyrenaica) by Using P-Systems , 2010, Int. Conf. on Membrane Computing.

[5]  Mario J. Pérez-Jiménez,et al.  Modeling Ecosystems Using P Systems: The Bearded Vulture, a Case Study , 2009, Workshop on Membrane Computing.

[6]  Catalin Buiu,et al.  Integrating human swarm interaction in a distributed robotic control system , 2011, 2011 IEEE International Conference on Automation Science and Engineering.

[7]  Gheorghe Paun,et al.  Computing with Membranes , 2000, J. Comput. Syst. Sci..

[8]  Ioan Dumitrache,et al.  Robot Localization Implemented with Enzymatic Numerical P Systems , 2012, Living Machines.

[9]  Vincenzo Manca,et al.  Log-Gain stoichiometric Stepwise Regression for MP Systems , 2011, Int. J. Found. Comput. Sci..

[10]  Henry Hoffmann,et al.  SEEC: A General and Extensible Framework for Self-Aware Computing , 2011 .

[11]  Catalin Buiu,et al.  Enzymatic numerical P systems - a new class of membrane computing systems , 2010, 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA).

[12]  Vincenzo Manca,et al.  Solving dynamical inverse problems by means of Metabolic P systems , 2012, Biosyst..

[13]  Gheorghe Paun,et al.  The Oxford Handbook of Membrane Computing , 2010 .

[14]  Catalin Buiu,et al.  Using enzymatic numerical P systems for modeling mobile robot controllers , 2011, Natural Computing.