Distributed Team Formation for Humanoid Robot Soccer

In this paper, we propose an adaptive team formation strategy for humanoid robot soccer. The proposed strategy involves distributed cooperative decisions through both communication and observations. Two agent groups, namely defenders and attackers, are formed by a case-based group formation method. Attackers are formed for constructing an attacking formation around the ball and scoring a goal whenever possible while defenders are for blocking and constructing a defensive obstacle against the opponent team. Cooperative decisions are made using communication among team members. Distribution of agents on the field is ensured by Voronoi cell construction of each agent through observations in a distributed manner. Experiments are set in the RoboCup 3D Soccer Simulation League environment where our method is compared to earlier team formation methods. The results illustrate that a distributed Voronoi cell construction method combined with a case-based grouping algorithm outperforms the others. Furthermore, it has been shown that our method is also robust to communication failures.

[1]  Vijay Kumar,et al.  Synthesis of Controllers to Create, Maintain, and Reconfigure Robot Formations with Communication Constraints , 2009, ISRR.

[2]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[3]  Sanem Sariel,et al.  Nature-Inspired Optimization for Biped Robot Locomotion and Gait Planning , 2011, EvoApplications.

[4]  Luís Paulo Reis,et al.  Situation Based Strategic Positioning for Coordinating a Team of Homogeneous Agents , 2000, Balancing Reactivity and Social Deliberation in Multi-Agent Systems.

[5]  Huosheng Hu,et al.  Coordination in multi-agent RoboCup teams , 2001, Robotics Auton. Syst..

[6]  Raúl Rojas,et al.  RoboCup 2002: Robot Soccer World Cup VI , 2002, Lecture Notes in Computer Science.

[7]  Tucker R. Balch,et al.  Behavior-based formation control for multirobot teams , 1998, IEEE Trans. Robotics Autom..

[8]  Manuela M. Veloso,et al.  A case-based approach for coordinated action selection in robot soccer , 2009, Artif. Intell..

[9]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[10]  Sahar Asadi,et al.  Dynamic Positioning Based on Voronoi Cells (DPVC) , 2005, RoboCup.

[11]  Milind Tambe,et al.  Team Formation for Reformation in Multiagent Domains Like RoboCupRescue , 2002, RoboCup.

[12]  F. Frances Yao,et al.  Computational Geometry , 1991, Handbook of Theoretical Computer Science, Volume A: Algorithms and Complexity.

[13]  Ubbo Visser,et al.  RoboViz: Programmable Visualization for Simulated Soccer , 2011, RoboCup.

[14]  Thomas Röfer,et al.  An Architecture for a National RoboCup Team , 2002, RoboCup.

[15]  Shahriar Asta,et al.  beeStanbul RoboCup 3 D Simulation League Team Description Paper 2012 , 2010 .

[16]  Manuela M. Veloso,et al.  Task Decomposition and Dynamic Role Assignment for Real-Time Strategic Teamwork , 1998, ATAL.

[17]  Ryota Nakanishi,et al.  Dynamic Positioning Method Based on Dominant Region Diagram to Realize Successful Cooperative Play , 2008, RoboCup.