[1]XIA Linlin,MIAO Guijuan,CHU Yan,et al.Determination of shooting point for soccer robot based upon adaptive neuro-fuzzy in ference system[J].CAAI Transactions on Intelligent Systems,2013,8(2):143-148.[doi:10.3969/j.issn.1673-4785.201203015]
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
8
Number of periods:
2013 2
Page number:
143-148
Column:
学术论文—智能系统
Public date:
2013-04-25
- Title:
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Determination of shooting point for soccer robot based upon adaptive neuro-fuzzy in ference system
- Author(s):
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XIA Linlin1; 2; MIAO Guijuan1; CHU Yan2; LIU Huimin3; JIAO Shengxi1
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1. School of Automation Engineering, Northeast Dianli University, Jilin 132012, China;
2. College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China;
3. College of Electromechanical Engineering, Qingdao Agricultural University, Qingdao 266109, China
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- Keywords:
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Gaussian-type function; neuro-fuzzy inference system; self-adaptiveness; shooting point; soccer robot
- CLC:
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TP301.6
- DOI:
-
10.3969/j.issn.1673-4785.201203015
- Abstract:
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In order to solve the limitation of the high computational complexity and delayed reaction in the shooting behavior of soccer robots, an adaptive neuro-fuzzy inference system (ANFIS) was proposed. The proposal invokes the Gaussian-type function technology to determine the optimal shoot point. The entire system was composed of the antecedent network and consequent one. The system integrated the fuzzy logic theory, which, lead to the establishment of the behavior model described by human language. Moreover, the training samples were derived from the shoot data of actual medium competitions, along with the implementation of off-line training methods to describe the mapping relationships between inputs and outputs. Once the training process was completed, the system is able to automatically adjust the shape of antecedent membership functions, as well as the consequent weights adaptively. The simulation results demonstrate that the high shooting success rate and reaction speed can be achieved as expected, proving the effectiveness of the proposed approach.