Verification of the emergence in an architecture for multi-robot systems (AMEB)
Abstract
This article analyzes the emerging behavior of a multi-robot system managed by an architecture structured in three layers: the first provides local support to the robot, manages its processes of action, perception and communication, as well as its behavioral aspect, which considers the reactive, cognitive and social aspects of the robot. In addition, it introduces an affective component that influences its behavior and the way it relates to the environment and to the other individuals in the system, based on an emotional model that takes into account fourArticle history:Received 12 September 2018Accepted 08 November 2018A Gil, pertenece al Laboratorio de Prototipos en la Universidad Nacional Experimental del Táchira y a Tepuy R+D Group. Artificial Intelligence Software Development. Mérida, Venezuela (email: agil@unet.edu.ve)basic emotions. The second provides support to the collective processes of the system, based on the concept of emerging coordination. The latter is responsible for knowledge management and learning processes, both individually and collectively, in the system. In this article the metrics are defined to verify the emergency in the system, by means of the use of a method of verification of emergent behaviors based on Fuzzy Cognitive Maps.
Downloads
References
A. Gil, J. Aguilar, R. Rivas, E. Dapena & K. Hernandez. “Architecture for Multi-robot Systems with Emergent Behavior,” inInternational Conference onArtificial Intelligence (ICAI), 2015,pp. 41-46.
A. Gil, J. Aguilar, R. Rivas & E. Dapena, “Behavioral Module in a Control Architecture for Multi-robots,” Revista Ingeniería al Día, 2016, vol. 2, No. 1, pp. 40-57.
M. S.Couceiro, C. M Figueiredo, J. M. A. Luz, N. M. Ferreira & R. P. Rocha. “A Low-Cost Educational Platform for Swarm Robotics,”International Journal of Robots, Education & Art,2012, vol. 2, no 1.
V.K. Pilania, S. Mishra, S. Panda & A. Mishra. “A novel approach to swarm bot architecture,” inInternational Asia Conference onInformatics in Control, Automation and Robotics, 2009, pp. 418-422.
K. Hernández, A. Gil, J. Aguilar, R. Rivas & E. Dapena. “Diseño de una plataforma multi-robot de propósito general,” in Simulación y aplicaciones recientes para ciencia y tecnología, 2016, vol.8, pp. 785-796.
N. Perozo, J. Aguilar & O. Terán. “Proposal for a Multiagent Architecture for Self-Organizing Systems (MA-SOS),” Lecture Notes in Computer Science, Springer-Verlag, 2008, vol. 5075, pp. 434-439.
N. Perozo, J. Aguilar, O. Terán & H. Molina. “A verification method for MASOES,”IEEE transactions on cybernetics, 2013,vol. 43, no 1, pp. 64-76.
N. Perozo, J. Aguilar, O. Terán & H. Molina. “An affective model for the multiagent architecture for self-organizing and emergent systems (MASOES),”Revista Técnica de la Facultad de Ingeniería Universidad del Zulia, 2012,vol. 35, no. 1, pp. 080-090.
D. Cañamero. “Modeling motivations and emotions as a basis for intelligent behavior,” inProceedings of the first international conference on Autonomous agents, 1997, pp. 148-155.
D. Cañamero. “Designing emotions for activity selection in autonomous agents,”in Emotions in humans and artifacts, 2003,pp. 115-148.
O. Simonin, T. Huraux, F. Charpillet. “Interactive surface for bio-inspired robotics, re-examining foraging models,” in23rd IEEE International Conference onTools with Artificial Intelligence (ICTAI), 2011, pp. 361-368.
J. Sebestyénová & P. Kurdel. “Multi-robotic system with self-organization for search of targets in covered area,” in11th International Conference onInformatics in Control, Automation and Robotics (ICINCO), 2014, vol. 2, pp. 451-458.
J. Timmis, L. Murray & M. Neal. “A neural-endocrine architecture for foraging in swarm robotic systems,” inNature Inspired Cooperative Strategies for Optimization. Springer, 2010, pp. 319-330.
E. Sahin, T.H. Labella, V. Trianni, J.L. Deneubourg, P. Rasse, D. Floreano, & M. Dorigo. “SWARM-BOT: Pattern formation in a swarm of selfassembling mobile robots,” inIEEE International Conference on Systems, Man and Cybernetics, 2002.
S. Sang-Wook, Y. Hyun-Chang & S. Kwee-Bo. “Behavior learning and evolution of swarm robot system for cooperative behavior,” inIEEE/ASME International Conference onAdvanced Intelligent Mechatronics, 2009, pp. 673-678.
P. N. Rogla & E. C. Mateu. “La arquitectura Acromovi: una arquitectura para tareas cooperativas de robots móviles,” Una perspectiva de la inteligencia artificial en su 50 aniversario: Campus Multidisciplinar en Percepción e Inteligencia, 2006, pp. 365-376.
F. De la Rosa & M. E. Jiménez. “Simulation of Multi-robot Architectures in mobile Robotics,” inIEEE Electronics, Robotics and Automotive Mechanics Conference, 2009, pp. 199-203.
J. Shepard & C. Kitt. “A Multirobot Control Architecture for Collaborative Missions Comprised of Tightly Coupled, Interconnected Tasks,” IEEE Systems Journal, 2018, vol. 12, no. 2, pp. 1435-1446.
A. Singhal, H. Singh , A. Penumatsa, N. Bhatt, A. Prakash, S. Kumar & R. Sinha R. “An Actor Based Architecture for Multi-Robot System with Application to Warehouse,” in ACM 1st International Workshop on Internet of People, Assistive Robots and Things, 2018, pp. 13-18.
K. Skarzynski, M. Stepniak, W. Bartyna & S. Ambroszkiewicz. “SO-MRS: a multi-robot system architecture based on the SOA paradigm and ontology,” inAnnual Conference Towards Autonomous Robotic Systems, Springer, 2018, pp. 330-342.
J. Aguilar. “A Survey about Fuzzy Cognitive Maps Papers,” International Journal of Computational Cognition. Yang ́s Scientific Research Institute, 2005, vol. 3, no. 2, pp. 27-33.
J. Aguilar, Introducción a los Sistemas Emergentes. Mérida:Talleres Gráficos, Universidad de los Andes, Venezuela, 2014.
J. Surowieck, “Wisdom of Crowds”. Random House, USA, 2005.
J. Aguilar. “Different dynamic causal relationship approaches for cognitive maps,”Applied Soft Computing, 2013,vol. 13, no. 1, pp. 271-282.
J. Aguilar. “A fuzzy cognitive map based on the random neural model.” inInternational Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems. Springer, 2001, pp. 333-338.
J. Aguilar. “Dynamic Fuzzy Cognitive Maps for the Supervision of Multiagent Systems,” Fuzzy Cognitive Maps: Advances in Theory, Methodologies, Tools and Application, Springer, 2010, pp. 307-324.
J. Aguilar, M. Cerrada, G. Mousalli, F. Rivas & F. Hidrobo. “A Multiagent Model for Intelligent Distributed Control Systems,” Lecture Notes in Artificial Intelligence, Springer-Verlag, 2005, vol. 3681, pp. 191-197.
J. Aguilar & J. Contreras. “The FCM designer tool”,Fuzzy Cognitive Map: Advances in Theory, Methodologies, Tools and Application, Springer, 2010, pp. 71-87.
Y. Tohyama & H. Igarashi. “Cooperative transportation by multi-robots with selecting leader,” in35th Annual Conference of IEEE Industrial Electronics, 2009, pp. 4179-4184.
S.Moon, D. Kwak & H. J. Kim. “Cooperative control of differential wheeled mobile robots for box pushing problem,” in12th International Conference IEEE on Control, Automation and Systems (ICCAS), 2012,pp. 140-144.
A. Ghosh, A. Konar & R. Janarthanan. “Multi-robot cooperative box-pushing problem using multi-objective particle swarm optimization technique,” inIEEE World Congress on Information and Communication
This article is published by LAJC under a Creative Commons Attribution-Non-Commercial-Share-Alike 4.0 International License. This means that non-exclusive copyright is transferred to the National Polytechnic School. The Author (s) give their consent to the Editorial Committee to publish the article in the issue that best suits the interests of this Journal. Find out more in our Copyright Notice.
Disclaimer
LAJC in no event shall be liable for any direct, indirect, incidental, punitive, or consequential copyright infringement claims related to articles that have been submitted for evaluation, or published in any issue of this journal. Find out more in our Disclaimer Notice.
