An efficacious method to assemble a modern multi-modal robotic team: dilemmas, challenges, possibilities and solutions

A modern multiagent robotic platform consists of a cooperative team of humans which develop a collaborative team of robots. The multi-modal nature of both the system and the team causes a complex problem which needs to be solved for optimum performance. Both the management and the technical aspect of a modern robotic team are explored in this Chapter in the platform of the RoboCup Competition. RoboCup is an example of such an environment where researchers from different disciplines join to develop a robotic team for completion as an evaluation challenge (Robocup, 2011). RoboCup competitions were first proposed by Mackworth in 1993. The main goal of this scientific competition is to exploit, improve and integrate the methods and techniques from robotics, machine vision and artificial intelligence disciplines to create an autonomous team of soccer playing robots(Kitano, 1997a; Kitano, 1997b; Kitano et al., 1997). Such experiment includes several challenges, from inviting an expert of specific field to the team to choosing bolts and nuts for each part of the robots. Usually each challenge has several possible solutions and choosing the best one is often challenging. We have participated in several world wide RoboCup competitions (Abdollahi, Samani et al. 2002, 2003 & 2004) and share our experience as an extensive instruction for setting up a modern robotic team including management and technical issues.

[1]  John A. Wagner,et al.  Structural contingency theory and individual differences: examination of external and internal person-team fit. , 2002 .

[2]  Hiroaki Kitano,et al.  RoboCup: The Robot World Cup Initiative , 1997, AGENTS '97.

[3]  Li-Chun Lai,et al.  Time-Optimal Control of an Omni-Directional Mobile Robot , 2006, 2006 1ST IEEE Conference on Industrial Electronics and Applications.

[4]  Hobart R. Everett,et al.  Mobile robot positioning: Sensors and techniques , 1997, J. Field Robotics.

[5]  Akihiro Matsumoto,et al.  Development of an omni-directional mobile robot with 3 DOF decoupling drive mechanism , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[6]  Tucker R. Balch,et al.  Constraint-Based Landmark Localization , 2002, RoboCup.

[7]  Clark F. Olson,et al.  Probabilistic self-localization for mobile robots , 2000, IEEE Trans. Robotics Autom..

[8]  Reid G. Simmons,et al.  Probabilistic Robot Navigation in Partially Observable Environments , 1995, IJCAI.

[9]  Wolfram Burgard,et al.  Active Markov localization for mobile robots , 1998, Robotics Auton. Syst..

[10]  Hiroaki Kitano,et al.  RoboCup-97: Robot Soccer World Cup I , 1998, Lecture Notes in Computer Science.

[11]  Daniel R. Ilgen,et al.  Structural contingency theory and individual differences: examination of external and internal person-team fit. , 2002, The Journal of applied psychology.

[12]  Piotr Skrzypczynski Planning Positioning Actions of a Mobile Robot Cooperating with Distributed Sensors , 2005, CORES.

[13]  N. Munro,et al.  PID controllers: recent tuning methods and design to specification , 2002 .

[14]  Hiroaki Kitano,et al.  RoboCup: A Challenge Problem for AI , 1997, AI Mag..

[15]  Roland Siegwart,et al.  A relative map approach to SLAM based on shift and rotation invariants , 2007, Robotics Auton. Syst..

[16]  Joan C. Woodward Industrial Organization: Theory and Practice , 1966 .

[17]  Robin R. Murphy,et al.  Introduction to AI Robotics , 2000 .

[18]  Amir Abdollahi,et al.  Design and Development of a Comprehensive Omni directional Soccer Player Robot , 2004 .

[19]  Jake K. Aggarwal,et al.  Position estimation Techniques for an Autonomous Mobile robot - a Review , 1993, Handbook of Pattern Recognition and Computer Vision.

[20]  北野 宏明,et al.  RoboCup-97 : robot soccer World Cup I , 1998 .

[21]  Jong-Hwan Kim,et al.  Fault tolerant control strategy for OmniKity-III , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[22]  Wolfram Burgard,et al.  A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots , 1998, Auton. Robots.

[23]  Igor E. Paromtchik,et al.  A practical approach to motion generation and control for an omnidirectional mobile robot , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[24]  C. H. Chen,et al.  Handbook of Pattern Recognition and Computer Vision , 1993 .

[25]  Joan C. Woodward Management and technology , 1958 .

[26]  R. Simmons,et al.  Probabilistic Navigation in Partially Observable Environments , 1995 .