|
|
|
Research on self-adaptive decision-making mechanism for competition strategies in robot soccer |
Haobin SHI1,2,*( ),Lincheng XU3,Lin ZHANG1,Wei PAN1,Genjiu XU4 |
1. School of Computer Science, Northwestern Polytechnical University, Xi’an 710129, China
2. Information Technology Research Base of Civil Aviation Administration of China, Civil Aviation University of China, Tianjin 300300, China
3. School of Aeronautics, Northwestern Polytechnical University, Xi’an 710129, China
4. School of Science, Northwestern Polytechnical University, Xi’an 710129, China |
|
|
|
|
Abstract In the robot soccer competition platform, the current confrontation decision-making system suffers from difficulties in optimization and adaptability. Therefore, we propose a new self-adaptive decision-making (SADM) strategy. SADM compensates for the restrictions of robot physical movement control by updating the task assignment and role assignment module using situation assessment techniques. It designs a self-adaptive role assignment model that assists the soccer robot in adapting to competition situations similar to how humans adapt in real time. Moreover, it also builds an accurate motion model for the robot in order to improve the competition ability of individual robot soccer. Experimental results show that SADM can adapt quickly and positively to new competition situations and has excellent performance in actual competition.
|
| Keywords
robot soccer
self-adaptive mechanism
decision-making
confrontation system
|
|
Corresponding Author(s):
Haobin SHI
|
|
Issue Date: 18 May 2015
|
|
| 1 |
Ros R, Arcos, J L, Lopez deMantaras R. A case-based approach for coordinated action selection in robot soccer. Artificial Intelligence, 2009, 173: 1014-1039
https://doi.org/10.1016/j.artint.2009.02.004
|
| 2 |
Ahmadi M, Stone P, Instance-based action models for fast action planning. In: Visser U, Ribeiro F, Ohashi T, Dellaert F, eds. RoboCup 2007: robot soccer world cup XI. Heidelberg: Springer Verlag, 2008: 1-16
https://doi.org/10.1007/978-3-540-68847-1_1
|
| 3 |
Zhang L, Shi H B, Wu J B. Applying intelligent confrontation decisionmaking system to robot soccer based on improved cbr(case-based reasoning). Journal of Northwestern Polytechnic University, 2013(6): 991-996
|
| 4 |
Hwang K S, Jiang W C, Yu H H, Lin S Y. Reinforcement learning in zero-sum markov games of robot soccer systems. Mobile Robots, 2011: 289-308
|
| 5 |
Kleiner A, Dietl M, Nebel B. Towards a life-long learning soccer agent. RoboCup 2002: robot soccer world cup VI. Springer, 2003: 126-134
https://doi.org/10.1007/978-3-540-45135-8_10
|
| 6 |
Jolly K, Ravindran K, Vijayakumar R, Sreerama Kumar R. Intelligent decision making in multi-agent robot soccer system through compounded articial neural networks. Robotics Autonomous System, 2007, 55(7): 589-596
https://doi.org/10.1016/j.robot.2006.12.011
|
| 7 |
Nakashima T, Takatani M, Udo M, Ishibuchi H, Nii M. Performance evaluation of an evolutionary method for robocup soccer strategies. RoboCup 2005: robot soccer world cup IX. Springer, 2005: 616-623
|
| 8 |
Konur S, Ferrein A, Ferrein E, Lakemeyer G. Learning decision trees for action selection in soccer agents. In: Proceedings of the Workshop on agents in dynamic and real-time environments. Valencia: IOS Press, 2004
|
| 9 |
Aamir A, Lima P. Multi-robot cooperative spherical-object tracking in 3D space based on particle filters. Robotics and Autonomous Systems, 2013, 61(10): 1084-1093
https://doi.org/10.1016/j.robot.2012.12.008
|
| 10 |
Wu J, Sna?el V, Ochodkova E, Martinovi? J, Svatoň V, Abraham A. Analysis of strategy in robot soccer game. Neurocomputing, 2013, 109: 66-75
https://doi.org/10.1016/j.neucom.2012.03.021
|
| 11 |
Berger R, G. L mel, Exploiting past experience-case-based decision support for soccer agents. In: Proceedings of KI 2007: Advances in artificial intelligence (German National AI Conference, KI). 2007(4667): 440-443
|
| 12 |
Ahmad A. An integrated bayesian approach to multi-robot cooperative perception. 2013
|
| 13 |
Lau N, Lopes L S, Corrente G, Fillpe N. Multi-robot team coordination through roles, positionings and coordinated procedures Intelligent, In: Proceedings of IEEE/RSJ International Conference on Robots and Systems. 2009: 5841-5848.
|
| 14 |
Nadarajah S, Sundaraj K. A survey on team strategies in robot soccer: team strategies and role description. Artificial Intelligence Review, 2013, 40(3): 271-304
https://doi.org/10.1007/s10462-011-9284-0
|
| 15 |
Song D L, Wu B W, Li X F, Chen L P, Liu C J. Research on distancefirst based role assignment strategy of soccer robot//Robot intelligence technology and applications 2012. Springer Berlin Heidelberg, 2013: 793-800
https://doi.org/10.1007/978-3-642-37374-9_76
|
| 16 |
Mota L, Reis L P, Lau N. Multi-robot coordination using setplays in the middle-size and simulation leagues. Mechatronics, 2011, 21(2): 434-444
https://doi.org/10.1016/j.mechatronics.2010.05.005
|
| 17 |
De Cooman G, Hermans F. Imprecise probability trees: bridging two theories of imprecise probability. Artificial Intelligence, 2008, 172: 1400-1427
https://doi.org/10.1016/j.artint.2008.03.001
|
| 18 |
Lin F J, Hung Y C, Tsai M T. Fault-tolerant control for six-phase PMSM drive system via intelligent complementary sliding-mode control using TSKFNN-AMF. IEEE Transactions on Industrial Electronics, 2013, 60: 5747-5762
https://doi.org/10.1109/TIE.2013.2238877
|
| 19 |
Geramifard A; Redding J, How J P. Intelligent cooperative control architecture: a framework for performance improvement using safe learning. Journal of Intelligent & Robotic Systems, 2013, 72: 83-103
https://doi.org/10.1007/s10846-013-9826-6
|
| 20 |
Juan C N, Penya A E, Yoseba K. Intelligence distribution for data processing in smart grids: a semantic approach. Engineering Applications of Artificial Intelligence, 2013(26): 18<?Pub Caret?>41-1853
|
| 21 |
Li S A, Hsieh M H, Ho C Y, Chen K H, Lin C Y, Wong C C. Task allocation design for autonomous soccer robot. In: Omar K, Nordin M J, Vadakkepat P, eds. Intelligent robotics systems: inspiring the NEXT. Berlin Springer, 2013: 297-308
https://doi.org/10.1007/978-3-642-40409-2_26
|
| [1] |
Supplementary Material-Highlights in 3-page ppt
|
Download
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
