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Appl. Sci. 2016, 6(6), 182; doi:10.3390/app6060182

RBF-Based Monocular Vision Navigation for Small Vehicles in Narrow Space below Maize Canopy

Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
Hefei Institute of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
College of Engineering, Anhui Agricultural University, Hefei 230036, China
Author to whom correspondence should be addressed.
Academic Editors: Antonio Fernández-Caballero and Takayoshi Kobayashi
Received: 19 April 2016 / Revised: 10 June 2016 / Accepted: 14 June 2016 / Published: 21 June 2016
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Maize is one of the major food crops in China. Traditionally, field operations are done by manual labor, where the farmers are threatened by the harsh environment and pesticides. On the other hand, it is difficult for large machinery to maneuver in the field due to limited space, particularly in the middle and late growth stage of maize. Unmanned, compact agricultural machines, therefore, are ideal for such field work. This paper describes a method of monocular visual recognition to navigate small vehicles between narrow crop rows. Edge detection and noise elimination were used for image segmentation to extract the stalks in the image. The stalk coordinates define passable boundaries, and a simplified radial basis function (RBF)-based algorithm was adapted for path planning to improve the fault tolerance of stalk coordinate extraction. The average image processing time, including network latency, is 220 ms. The average time consumption for path planning is 30 ms. The fast processing ensures a top speed of 2 m/s for our prototype vehicle. When operating at the normal speed (0.7 m/s), the rate of collision with stalks is under 6.4%. Additional simulations and field tests further proved the feasibility and fault tolerance of our method. View Full-Text
Keywords: inter-row mobile vehicle; monocular vision; path identification; radial basis function (RBF) inter-row mobile vehicle; monocular vision; path identification; radial basis function (RBF)

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Liu, L.; Mei, T.; Niu, R.; Wang, J.; Liu, Y.; Chu, S. RBF-Based Monocular Vision Navigation for Small Vehicles in Narrow Space below Maize Canopy. Appl. Sci. 2016, 6, 182.

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