TY - JOUR
T1 - Cooperative control through objective achievement
AU - Farinelli, Alessandro
AU - Fujii, Hikari
AU - Tomoyasu, Nanase
AU - Takahashi, Masaki
AU - D'Angelo, Antonio
AU - Pagello, Enrico
N1 - Funding Information:
In this paper we have presented an approach to cooperative control based on objective achievement. The approach is explicitly designed for dynamic uncertain environments, and it solves a distributed coalition formation problem. This is done by aggregating the information that each agent acquires from the environment and the information communicated from the teammates. We have applied this approach to the RoboCup Soccer domain, and we show how the aggregated information required by the algorithm is extracted from the sensor readings of the robotic platforms. When specialised to the RoboCup soccer domain, our method is able to optimise the allocation of robot coalitions to tasks in a distributed and efficient way. The approach has been empirically evaluated both in a simulated environment and during RoboCup middle-size league competitions by the EIGEN team. The results obtained show that the approach is able to balance the effort of the robotic platform on different tasks, providing an efficient and effective coordination mechanism. Alessandro Farinelli has been a researcher in the University of Verona Faculty of Mathematical, Physical and Natural Science, Department of Computer Science, since December 2008. He received his PhD in Computer Science in 2005 from the Department of Computer Science of Rome University “La Sapienza”, where he was a post-doctoral fellow until 2007. From 2007 to 2009 he was a research fellow and a research visitor at the ECS department of Southampton University. His research interests comprise theoretical and practical issues related to the development of artificial intelligent systems applied to robotics. In particular, he focuses on coordination, decentralised optimisation and information integration for multiagent and multirobot systems, and control and evaluation of autonomous mobile robots. Hikari Fujii received her B.E. and M.E. degrees from the Department of System Design Engineering at Keio University, Yokohama, Japan, in 2002 and 2004, respectively. In 2004, she started working as a Research Assistant in the 21st Century COE Program: “System Design: Paradigm shift from Intelligence to Life”. From 2005 to 2007, she worked as a Research Assistant in the Department of System Design Engineering, Keio University, Yokohama, Japan. Her primary research interests include autonomous mobile robot and cooperative control. She is a member of The Robotics Society of Japan. Nanase Tomoyasu received her B.E. degree from the Department of System Design Engineering, Keio University, Yokohama, Japan, in 2008. She is currently a second-year master’s degree student at Keio University. Her research interest is in the cooperative behavior of multirobots. Masaki Takahashi (Member, IEEE) received his B.E. and M.E. degrees from the Department of System Design Engineering of Keio University, Yokohama, Japan, in 2000 and 2002, respectively. He received his D.Eng. degree from Keio University in 2004. In 2004, he started working as a Research Assistant in the 21st Century COE Program: “System Design: Paradigm shift from Intelligence to Life”. From 2005 to 2008, he worked as a Research Assistant in the Department of System Design Engineering, Keio University, Yokohama, Japan, and he became an Associate Professor in 2009. His primary research interests include human–robot interaction, motion and vibration control, and sensor fusion. He is a member of American Institute of Aeronautics and Astronautics, The Japan Society of Mechanical Engineers and The Robotics Society of Japan. Antonio D’Angelo has been Assistant Professor of Operating Systems and Robotics, since 2000, at the University of Udine. He received his M.S. in Electrical Engineering from Padua University in 1981 and since 1984 he has been working at the Laboratory of Artificial Intelligence and Robotics at the Department of Mathematics and Computer Science at the University of Udine. He also actively cooperates with Prof. E. Pagello of Padua University in many research projects. His main research interests cover multiagent autonomous system coordination and behaviour-based robot control including complex dynamical system models for autonomous robots. In this framework he developed the roboticle model to gain insight over coordination without explicit communication. The current investigation is oriented to the motion control of dense robot colonies through thermodynamics. Enrico Pagello received his “Laurea” degree in Electronic Engineering from the University. of Padua, Italy, in 1972. From 1976 to 1983, he was a Research Associate at the Institute of Biomedical Engineering of the National Research Council of Italy, where he is now a part-time Senior Associated Researcher. Since 1983 he has been with the Faculty of Engineering, University of Padua, where he is a Professor of Computer Science. During 1977 and 1978, he was a Visiting Scholar at the Laboratory of Artificial Intelligence of Stanford University, California. Since 1994, he has regularly visited the Department of Precision Engineering, University of Tokyo, Japan, where he has been a JSPS Fellow. In 2005 and 2008 he was an Invited Professor at Keio University, Japan. His current research interests include the application of artificial intelligence to robotics with particular regard to the multirobot systems domain. He was a General Chair of the Sixth IAS Conference in July 2000, of RoboCup-2003, and of SIMPAR-2008 Conference. He has been a member of the Editorial Board of the IEEE/TRA, and he is currently a member of the Editorial. Board of RAS International Journal. He is President of the International Society for Intelligent Autonomous Systems.
PY - 2010/7/31
Y1 - 2010/7/31
N2 - Cooperative control is a key issue for multirobot systems in many practical applications. In this paper, we address the problem of coordinating a set of mobile robots in the RoboCup soccer middle-size league. We show how the coordination problem that we face can be cast as a specific coalition formation problem, and we propose a distributed algorithm to efficiently solve it. Our approach is based on the distributed computation of a measure of satisfaction (called Agent Satisfaction) that each agent computes for each task. We detail how each agent computes the Agent Satisfaction by acquiring sensor perceptions through an omnidirectional vision system, extracting aggregated information from the acquired perception, and integrating such information with that communicated by the teammates. We empirically validate our approach in a simulated scenario and within RoboCup competitions. The experiments in the simulated scenario allow us to analyse the behaviour of the algorithm in different situations, while the use of the algorithm in real competitions validates the applicability of our approach to robotic platforms involved in a dynamic and complex scenario.
AB - Cooperative control is a key issue for multirobot systems in many practical applications. In this paper, we address the problem of coordinating a set of mobile robots in the RoboCup soccer middle-size league. We show how the coordination problem that we face can be cast as a specific coalition formation problem, and we propose a distributed algorithm to efficiently solve it. Our approach is based on the distributed computation of a measure of satisfaction (called Agent Satisfaction) that each agent computes for each task. We detail how each agent computes the Agent Satisfaction by acquiring sensor perceptions through an omnidirectional vision system, extracting aggregated information from the acquired perception, and integrating such information with that communicated by the teammates. We empirically validate our approach in a simulated scenario and within RoboCup competitions. The experiments in the simulated scenario allow us to analyse the behaviour of the algorithm in different situations, while the use of the algorithm in real competitions validates the applicability of our approach to robotic platforms involved in a dynamic and complex scenario.
KW - Coordination
KW - Multirobot system
KW - RoboCup
KW - Task assignment
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UR - http://www.scopus.com/inward/citedby.url?scp=78049422723&partnerID=8YFLogxK
U2 - 10.1016/j.robot.2010.03.012
DO - 10.1016/j.robot.2010.03.012
M3 - Article
AN - SCOPUS:78049422723
SN - 0921-8890
VL - 58
SP - 910
EP - 920
JO - Robotics and Autonomous Systems
JF - Robotics and Autonomous Systems
IS - 7
ER -