Research on Intelligent Decision-Making System of Variable Spraying for Mobile Robot in Greenhouse

Guo Qin Gao; Hai Yan Zhou; Xue Mei Niu; Zhi Ming Fang

doi:10.4028/www.scientific.net/AMM.241-244.1835

Paper Titles

Error Compensation of Stator Resistance Estimation in Sensorless Induction Motor Drives
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Control System Design for Tracked Trailing Mobile Robot
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Human Simulated Intelligent Control for Permanent Magnet Synchronous Motor
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Virtual Design and Test of Manipulator’s Clamping Mechanism for Carrying Cylindrical Lithium Battery
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Research on Intelligent Decision-Making System of Variable Spraying for Mobile Robot in Greenhouse
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Research on Statistical Process Control for Aluminium Electrolysis Reduction
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Dynamic Modeling and Analysis of a Fruit and Vegetable Picking Robot
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PID Control of Double-Loop Speed Control System Based on Bacteria-Particle Swarm Hybrid Optimization Algorithm
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Simulation Design of Visual Servo Based on Homography Matrix Decomposition
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 241-244Research on Intelligent Decision-Making System of...

Research on Intelligent Decision-Making System of Variable Spraying for Mobile Robot in Greenhouse

Abstract:

In order to improve the pesticide effective utilization rate and reduce the pesticide residues and the chemical pollution, an intelligent decision-making method for variable spraying of mobile robot based on a fuzzy neural network is proposed. The system is built by integrating the level of plant diseases and insect pests and the spraying target’s distance and area. The intelligent decision-making is achieved by self-learning and self-correcting the fuzzy rules of the fuzzy neural network. The simulation experiment results show that the intelligent decision-making method can realize real-time and quick decision. It has the greater decision accuracy than the fuzzy decision system on the samples not appearing in training and has a good fit for the uncertain work environment in greenhouse.

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Periodical:

Applied Mechanics and Materials (Volumes 241-244)

Pages:

1835-1838

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.241-244.1835

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Online since:

December 2012

Authors:

Guo Qin Gao, Hai Yan Zhou, Xue Mei Niu, Zhi Ming Fang

Keywords:

Fuzzy Neural Network (FNN), Intelligence Decision-Making, Mobile Robot, Variable Spraying

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References

[1] Nuyttens D, Windey S and Sonck B. Biosystems Engineering, 2004, 89 (4): 417-423.

DOI: 10.1016/j.biosystemseng.2004.08.016

Google Scholar

[2] Wenzhong Zheng and Xiafan Ying. Journal of Agricultural Mechanization Research, 2008, (5): 219－221. (in Chinese)

Google Scholar

[3] Gil E, Escola A and Rosell J R. Crop Protection, 2007, 26(8): 1287-1297.

Google Scholar

[4] Lushou Shao, Zhixiang Dai and Huailei Cui. Transactions of The Chinese Society of Agricultural Machinery, 2005, 36(11): 110－11. (in Chinese)

Google Scholar

[5] Shuren Chen, Dongfu Yin and Xinhua Wei. Journal of Drainage and Irrigation Machinery Engineering, 2011, 29(3): 272-276. (in Chinese)

Google Scholar

[6] Wei Deng and Weimin Ding. Transactions of the Chinese Society for Agricultural Machinery, 2008, 39(6): 77-80. (in Chinese).

Google Scholar

[7] Wu S Q and Er M J. Dynamic Fuzzy Neural Networks: A Novel Approach to Function Approximation. IEEE Trans Syst, Man, Cybern. Part B. 2000, 30: 358-364.

DOI: 10.1109/3477.836384

Google Scholar