CAMBADA Soccer Team: from Robot Architecture to Multiagent Coordination

Robotic soccer is nowadays a popular research domain in the area of multi-robot systems. RoboCup is an international joint project to promote research in artificial intelligence, robotics and related fields. RoboCup chose soccer as the main problem aiming at innovations to be applied for socially relevant problems. It includes several competition leagues, each one with a specific emphasis, some only at software level, others at both hardware and software, with single or multiple agents, cooperative and competitive. In the context of RoboCup, the Middle Size League (MSL) is one of the most challenging. In this league, each team is composed of up to 5 robots with a maximum size of 50cm× 50cm, 80cm height and a maximumweight of 40Kg, playing in a field of 18m× 12m. The rules of the game are similar to the official FIFA rules, with minor changes required to adapt them for the playing robots CAMBADA, Cooperative Autonomous Mobile roBots with Advanced Distributed Architecture, is the MSL Soccer team from the University of Aveiro. The project started in 2003, coordinated by the Transverse Activity on Intelligent Robotics group of the Institute of Electronic and Telematic Engineering of Aveiro (IEETA). This project involves people working on several areas for building the mechanical structure of the robot, its hardware architecture and controllers (Almeida et al., 2002; Azevedo et al., 2007) and the software development in areas such as image analysis and processing (Caleiro et al., 2007; Cunha et al., 2007; Martins et al., 2008; Neves et al., 2007; 2008), sensor and information fusion (Silva et al., 2008; 2009), reasoning and control (Lau et al., 2008), cooperative sensing approach based on a Real-Time Database (Almeida et al., 2004), communications among robots (Santos et al., 2009; 2007) and the development of an efficient basestation. The main contribution of this chapter is to present the new advances in the areas described above involving the development of an MSL team of soccer robots, taking the example of the CAMBADA team that won the RoboCup 2008 and attained the third place in the last edition of the MSL tournament at RoboCup 2009. CAMBADA also won the last three editions

[1]  Bernardo Cunha,et al.  Communicating among Robots in the RoboCup Middle-Size League , 2009, RoboCup.

[2]  Bernardo Cunha,et al.  Obtaining the Inverse Distance Map from a Non-SVP Hyperbolic Catadioptric Robotic Vision System , 2008, RoboCup.

[3]  W. Eric L. Grimson,et al.  On the Sensitivity of the Hough Transform for Object Recognition , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Armando J. Pinho,et al.  Autonomous Configuration of Parameters in Robotic Digital Cameras , 2009, IbPRIA.

[5]  Greg Welch,et al.  An Introduction to Kalman Filter , 1995, SIGGRAPH 2001.

[6]  T. Blaffert,et al.  The Laplace integral for a watershed segmentation , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[7]  Bin Liu,et al.  Color Edge Detection Based on Morphology , 2006, 2006 First International Conference on Communications and Electronics.

[8]  Luís Seabra Lopes,et al.  Self-configuration of an adaptive TDMA wireless communication protocol for teams of mobile robots , 2008, 2008 IEEE International Conference on Emerging Technologies and Factory Automation.

[9]  Yuan Zou,et al.  Edge detection using generalized root signals of 2-D median filtering , 1997, Proceedings of International Conference on Image Processing.

[10]  Bernardo Cunha,et al.  Hierarchical distributed architectures for autonomous mobile robots: A case study , 2007, 2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007).

[11]  L. Almeida,et al.  Implementing a distributed sensing and actuation system: The CAMBADA robots case study , 2005, 2005 IEEE Conference on Emerging Technologies and Factory Automation.

[12]  Pedro U. Lima,et al.  IMPROVING OBJECT LOCALIZATION THROUGH SENSOR FUSION APPLIED TO SOCCER ROBOTS , 2003 .

[13]  Thi Thi Zin,et al.  Robust Person Detection using Far Infrared Camera for Image Fusion , 2007, Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007).

[14]  Martin Lauer,et al.  Modeling Moving Objects in a Dynamically Changing Robot Application , 2005, KI.

[15]  Manuela M. Veloso,et al.  Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork , 1999, Artif. Intell..

[16]  Armando J. Pinho,et al.  Real-time generic ball recognition in RoboCup domain , 2008 .

[17]  Zhi-Qiang Liu,et al.  Curve detection using a new clustering approach in the Hough space , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[18]  Alexander Ferrein,et al.  Comparing Sensor Fusion Techniques for Ball Position Estimation , 2005, RoboCup.

[19]  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.

[20]  Armando J. Pinho,et al.  A hybrid vision system for soccer robots using radial search lines , 2007 .

[21]  Wan-Chi Siu,et al.  Invariant Hough transform with matching technique for the recognition of non-analytic objects , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[22]  Armando J. Pinho,et al.  Color-spaces and color segmentation for real-time object recognition in robotic applications , 2007 .

[23]  Roberto Maass-Moreno,et al.  Fitting Models to Biological Data Using Linear and Nonlinear Regression: A Practical Guide to Curve Fitting.ByHarvey Motulskyand, Arthur Christopoulos.Oxford and New York: Oxford University Press. $65.00 (hardcover); $29.95 (paper). 351 p; ill.; index. ISBN: 0–19–517179–9 (hc); 0–19–517180–2 (pb). 2 , 2005 .

[24]  Luís Seabra Lopes,et al.  Coordinating Distributed Autonomous Agents with a Real-Time Database: The CAMBADA Project , 2004, ISCIS.

[25]  José Alberto Fonseca,et al.  The FTT-CAN protocol: why and how , 2002, IEEE Trans. Ind. Electron..

[26]  Martin Lauer,et al.  Calculating the Perfect Match: An Efficient and Accurate Approach for Robot Self-localization , 2005, RoboCup.

[27]  F. Von Hundelshausen An omnidirectional vision system for soccer robots , 2001 .

[28]  António J. R. Neves,et al.  Sensor and Information Fusion Applied to a Robotic Soccer Team , 2009, RoboCup.

[29]  J. Canny A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.