Buscar en
Revista Iberoamericana de Automática e Informática Industrial RIAI
Toda la web
Inicio Revista Iberoamericana de Automática e Informática Industrial RIAI Arquitectura Basada en Roles Aplicada en Equipos de Fútbol de Robots con Contro...
Información de la revista
Vol. 13. Núm. 3.
Páginas 370-380 (Julio - Septiembre 2016)
Compartir
Compartir
Descargar PDF
Más opciones de artículo
Visitas
2349
Vol. 13. Núm. 3.
Páginas 370-380 (Julio - Septiembre 2016)
Open Access
Arquitectura Basada en Roles Aplicada en Equipos de Fútbol de Robots con Control Centralizado
Centralized Robot Soccer Architecture Based on Roles
Visitas
2349
José G. Guarnizoa,b,
Autor para correspondencia
jguarnizo@udistrital.edu.co

Autor para correspondencia.
, Martín Melladob
a Laboratorio de Investigación en Fuentes Alternativas de Energía, Universidad Distrital Francisco José de Caldas, Carrera 7 No 40-53 Piso 5, Bogotá Colombia
b Instituto de Automática e Informática Industrial, Universitat Politècnica de València, Camino de Vera, s/n, 46022, Valencia, España
Este artículo ha recibido

Under a Creative Commons license
Información del artículo
Resumen
Texto completo
Bibliografía
Descargar PDF
Estadísticas
Resumen

El fútbol de robots ofrece un entorno adecuado para el diseño y la validación de arquitecturas de sistemas multi-robot. Al clasificar las ligas de fútbol de robots existentes se encuentran ligas con arquitecturas centralizadas que poseen percepción global del entorno y donde los robots son controlados desde un ordenador a través de un único sistema de toma de decisiones. En este artículo se presenta una arquitectura basada en roles para equipos de fútbol de robots con percepción global y control centralizado. En esta arquitectura un rol es seleccionado para cada jugador por medio de una función. A partir de este rol y de las condiciones de juego presentes se selecciona un comportamiento que el jugador deberá ejecutar. La función que es utilizada para la asignación de roles es activada cuando el balón cambia de cuadrante en el campo de juego. La estrategia presentada es comparada en simulación realizando partidos contra un equipo que posee una estrategia de roles constantes y un equipo con una estrategia jerárquica basada en selección de tácticas y posteriormente asignación de roles a partir de la táctica seleccionada. Los resultados mostraron no solo un mejor rendimiento del equipo con la estrategia basada en roles, sino también uniformidad en los comportamientos realizados por los jugadores del equipo durante las transiciones de roles y comportamientos.

Palabras clave:
Agentes
toma de decisiones
robots móviles autónomos
control centralizado
arquitecturas.
Abstract

Robot soccer offers an adequate domain in order to design and validate architectures for robot-coordination. One classification refers to centralized architectures, which correspond to robot soccer environments with global perception and centralized control of the robots, using only one decision-making system. In this paper it is presented a centralized robot soccer architecture based on roles, where one role is assigned to each player in order to select a specific behaviour depending on game conditions. Roles are assigned using an assignment function, which is activated when the ball changes of the quadrant in the playing field. This strategy has been compared by simulation in games against an opposition team with constant roles, and other team with a hierarchical strategy which assigns roles depending on a tactic previously selected. The results showed a better performance in the team with the role-based strategy outperformed the rest of the methods. As well as uniformity within the players’ behaviors during the role and behavior transitions.

Keywords:
Agents
decision making
autonomous mobile robots
centralized control
architectures.
Referencias
[Abeyruwan et al., 2012]
S. Abeyruwan, A. Seekircher, U. Visser.
Dynamic Roles Assigment Using General Value Functions.
7th Workshop on Humanoid Soccer Robots, IEEE-RAS International Conference on Humanoid Robots,
[Abreu et al., 2014]
P.H. Abreu, D. Castro, F. Almeida, J. Mendes-Moreira.
Improving a Simulated Soccer Team‘s Performance Through a Memory-Based Collaborative Filtering Approach.
Applied Soft Computing, 23 (2014), pp. 180-193
[Acosta Calderon et al., 2010]
C.A. Acosta Calderon, R.E. Mohan, C. Zhou.
Distributed Architecture for Dynamic Role Behaviour in Humanoid Soccer Robots. En: V. Papi.
Robot Soccer. Intech, (2010), pp. 121-138
[Agüero et al., 2006]
C.E. Agüero, V. Matellán, J.M. Cañas, V.M. Gómez.
SWITCH! Dynamic roles exchange among cooperative robots.
Second International Workshop on Multi-Agent Robotic Systems (MARS 2006),
[Arias and Ramirez, 2008]
M. Arias, J. Ramirez.
Team Agent Behavior Architecture in Robot Soccer.
Robotic Symp., 2008. LARS‘2008. IEEE Latin American, (2008), pp. 20-25
[Atkinson and Rojas, 2009]
J. Atkinson, D. Rojas.
On-the-fly generation of multi-ropbot team formation strategies based in game conditions.
Expert Systems with Applications, 3 (2009), pp. 6082-6090
[Baldoni et al., 2008]
M. Baldoni, G. Boella, N. Dorni, A. Mugnaini, R. Grenna.
Organizations and roles as primitives in the JADE framework.
Workshop on Objects and Agents, (2008), pp. 89-92
[Bayindir, 2016]
L. Bayindir.
A review of swarm robotics tasks. Neurocomputing, 172 (2016), pp. 292-321
[Bravo et al., 2011]
C. Bravo, J. Aguilar-Castro, A. Ríos, J. Aguilar-Martin, F. Rivas.
Arquitectura Basada en Inteligencia Artificial Distribuida para la Gerencia Integrada de Producción Industrial.
Revista Iberoamericana de Automática e Informática Industrial RIAI, 8 (2011), pp. 405-417
[Campbell and Wu, 2011]
A. Campbell, A.S. Wu.
Multi-agent rolle allocation: issues, approaches and multiple perspective.
Autonomous Agents and Multi-Agent Systems, 22 (2011), pp. 317-355
[Chen et al., 2014]
B. Chen, A. Zhang, L. Cao.
Autonomous intelligent decision-making system based on Bayesian SOM neural network for robot soccer.
Neurocomputing, 128 (2014), pp. 447-458
[Cravo et al., 2014]
J. Cravo, F. Almeida, P.H. Abreu, L.P. Reis, N. Lau, L. Mota.
Strategy planner: Graphical definition of soccer set-plays.
Data & Knowledge Engineering, 9 (2014), pp. 110-131
[Cardoso et al., 2012]
Cardoso, P., Molina, L., Freire, E.O., Carvalho, E.A.N., 2012,. A Methodology to Designing Strategies for Robot Soccer Based on Discrete Event Systems Fornalism. Robotics Symposium and Latin American Robotics Symposium (SBR-LARS), 2012 Brazilian. 143-149.
[El Barachi et al., 2013]
M. El Barachi, S. Rabah, N. Kara, R. Dssouli, J. Paquet.
Wireless Communications and Networking Conference (WCNC), (2013), pp. 4777-4782
[Esquivel-Flores and Benítez-Pérez, 2012]
O. Esquivel-Flores, H. Benítez-Pérez.
Reconfiguración Dinámica de Sistemas Distribuidos en Tiempo-Real Basada en Agentes.
Revista Iberoamericana de Automática e Informática Industrial RIAI, 9 (2012), pp. 300-313
[Fernandes and Bianchi, 2015]
Fernandes, M., Bianchi, R.A.C., Heuristically-Acelerated Reinforcement Learning: A Comparative Analysis of Performance. 14th Annual Conference, TAROS 2013, Oxford, UK, August 28--30, 2013. 15-27. Fira. May. 2015. Fira SimuroSot League. http://www.fira.net/contents/sub03/sub03_7.asp.
[Garcia et al., 2013]
P. Garcia, J.M. Balmaceda, S. Schiaffino, A. Amandi.
Automatic Detection of Team Roles in Computer Supported Collaborative Work.
IEEE Latin America Transactions, 11 (2013), pp. 1066-1074
[Guarnizo et al., 2015]
J.G. Guarnizo, M. Mellado, C. Low, F. Blanes.
Architecting centralized coordination of soccer robots based on principle solution.
Advanced Robotics, 29 (2015), pp. 989-1004
[Hernández et al., 2013]
L. Hernández, C. Balandrón, J.M. Aguiar, B. Carro, A. Sánchez-Esguevillas, J. Llorent, D. Chinaro, J.J. Gomez-Sanz, D. Cook.
A Multi-Agent System Architecture for Smart Grid Management and Forecasting of Energy Demand in Virtual Power Plants.
IEEE Communications Magazine, 51 (2013), pp. 106-113
[Hilaire et al., 2008]
V. Hilaire, F. Lauri, P. Gruer, A. Koukam, S. Rodriguez.
An Adaptative Agent Architecture for Holonic Multi-Agent Systems.
ACM Transactions on Autonomous and Adaptive Systems, 3 (2008), pp. 1-24
[Hwang et al., 2007]
K.S. Hwang, S.W. Tan, Y.J. Chen, C.H. Lee..
Reinforcement Learning in Strategy Selection for a Coordinated Multirobot System.
Systems, Man and Cybernetics, Part A: Systems and Humans IEEE Transactions on, 37 (2007), pp. 1151-1157
[Hwang et al., 2011]
K.S. Hwang, W.C. Jiang, H.S. Yu, S.Y. Lin..
Cooperative Reinforcement Learning Based on Zero-Sum Games.
Mobile Robots – Control Architectures, Bio-Interfacing, Navigation, Multi Robot Motion Planning and Operator. Intech, pp. 289-308 http://dx.doi.org/10.5772/26620
[Hwang et al., 2014]
K.S. Hwang, S.W. Tan, C.C. Chen.
Cooperative strategy based on adaptive Q-learning for robot soccer systems.
Fuzzy Systems, IEEE Transactions on, 12 (2014), pp. 569-576
[Jolly et al., 2010]
K. Jolly, R. Sreerama Kumar, R. Vijayakumar.
Intelligent task planning and action selection of a mobile robot in a multi-agent system through a fuzzy neural network approach.
Engineering Applications of Artificial Intelligence, 23 (2010), pp. 923-933
[Kendall, 2000]
E.A. Kendall.
Role modeling for agent systems analysis, design and implementation.
Concurrency, IEEE, 8 (2000), pp. 34-41
[Kim et al., 1997]
J.H. Kim, H.S. Shim, H.S. Kim, M.J. Jung, I.H. Choi, J.O. Kim.
A cooperative multi-agent system and its real time application to robot soccer.
Robotics and Automation, 1997. Proceedings. 1997 IEEE International Conference on, (1997), pp. 20-25
[Klančar et al., 2007]
G. Klančar, B. Zupančič, R. Karba.
Modelling and simulation of a group of mobile robots.
Simulation Modelling Practice and Theory, 15 (2007), pp. 647-658
[Kontes and Lagoudakis, 2007]
G. Kontes, M. Lagoudakis.
Coordinated Team Play in the Four- Legged RoboCup League.
Tools with Artificial Intelligence, 2007. ICTAI 2007. 19th IEEE International Conference on, pp. 109-116
[Lau et al., 2009]
N. Lau, L.S. Lopes, G. Corrente, N. Filipe.
Multi-robot team coordination through roles, positionings and coordinated procedures.
Intelligent Robots and Systems 2009. IROS 2009, (2009), pp. 5841-5848
[Lauer et al., 2010]
M. Lauer, R. Hafner, S. Lange, M. Riedmiller.
Cognitive Concepts in Autonomous Soccer Playing Robots.
Cognitive Systems Research, 11 (2010), pp. 287-309
[Lou et al., 2012]
Y. Lou, B. Chen, H. Shi.
Decision making model based on state assessment and hierarchical FSM in robot soccer.
Automatic Control and Artificial Intelligence (ACAI 2012), International Conference on, (2012), pp. 756-759
[McMillen and Veloso, 2006]
C. McMillen, M. Veloso.
Distributed Play-Based Role Assignment for Robot Teams in Dynamic Environments.
Distributed Autonomous Robotic Systems 7, pp. 145-154 http://dx.doi.org/10.1007/4-431-35881-7
[Palamar et al., 2009]
P.F. Palamar, V. Ziparo, L. Locchi, D. Nardi, P. Lima.
Teamwork Design Based on Petri Net Plans.
RoboCup 2008: Robot Soccer World Cup XII, (2009), pp. 200-211
[Riley and Veloso, 2002]
P. Riley, M. Veloso.
Recognizing Probabilistic Opponent Movement Models.
RoboCup 2001: Robot Soccer World Cup V, (2002), pp. 453-458
[Shi et al., 2015]
H. Shi, L. Xu, L. Zhang, W. Pan, G. Xu.
Research on self-adaptive decision-making mechanism for competition strategies in robot soccer.
Frontiers of Computer Science, 9 (2015), pp. 485-494
[Stone and Veloso, 1999]
P. Stone, M. Veloso.
Task decomposition, dynamic role assignment, and low-bandwidth communication for real-time strategic teamwork.
Journal of Artificial Intelligence, 110 (1999), pp. 241-273
[Stulp et al., 2010]
F. Stulp, H. Utz, M. Isik, G. Mayer.
Implicit Coordination with Shared Belief: A Heterogeneous Robot Soccer Team Case Study.
Advanced Robotics, 24 (2010), pp. 1017-1036
[Testart et al., 2011]
J. Testart, J. Ruiz del Solar, R. Schulz, P. Guerrero, R. Palma-Amestoy.
A Real-Time Hybrid Architecture for Biped Humanoids with Active Vision Mechanisms.
Journal of Intelligent and Robotic Systems, 63 (2011), pp. 233-255
[Wang et al., 2009]
Wang, J., Wang, T., Wang, X., Meng, X., 2009,. Multi-robot decision making based on coordination graphs. Mechatronics and Automation, 2009. ICMA 2009. International Conference on. 2393-2398.
[Wu and Lee, 2004]
C.-J. Wu, T.-L. Lee.
A Fuzzy Mechanism for Action Selection of Soccer Robots.
Journal of Intelligent & Robotic Systems, 39 (2004), pp. 57-70
[Wu et al., 2013]
J. Wu, V. Snášel, E. Ochodková, J. Martinovič, V. Svatoň, A. Abraham.
Analysis of strategy in robot soccer game.
Neurocomputing, 109 (2013), pp. 66-75
[Yang and Jia, 2012]
Yang, M., Jia, Y., 2012,. Action Utility Prediction and Role Task Allocation in Robot Soccer System. Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on . 112-117.
[Yu et al., 2015]
W.Y. Yu, V.W. Soo, M.S. Tsai.
Power distribution system service restoration bases on a committee-based intelligent agent architecture.
Engineering Applications of Artificial Intelligence, 41 (2015), pp. 92-102
[Zhou et al., 2015]
L. Zhou, V. Varadharajan, M. Hitchens.
Trust Enhanced Cryptographic Role-Based Access Control for Secure Cloud data Storage.
Information Forensics and Security, IEEE Transactions on, 10 (2015), pp. 2381-2395
[Zhu, 2006]
H. Zhu.
A role-Based Architecture for intelligent Agent Systems.
Distributed Intelligent Systems: Collective Intelligence and Its Applications, 2006. DIS 2006. IEEE Workshop on, pp. 354-362
Opciones de artículo
Herramientas