Vision-based adaptive variable rate spraying approach for unmanned aerial vehicles

Authors

  • Linhui Wang 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 2. College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China;
  • Yubin Lan 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 3. College of Engineering, South China Agricultural University, Guangzhou 510642, China;
  • Xuejun Yue 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 2. College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China;
  • Kangjie Ling 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 2. College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China;
  • Zhenzhao Cen 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 2. College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China;
  • Ziyao Cheng 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 2. College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China;
  • Yongxin Liu 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 4. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China
  • Jian Wang 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 2. College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China;

Keywords:

vision sensor, UAV, adaptive spray, variable rate spraying, fuzzy control, empty area, precision agriculture aviation

Abstract

The rapid developments of unmanned aerial vehicles (UAV) and vision sensor are contributing a great reformation in precision agriculture. Farmers can fly their UAV spraying pesticides around their crop fields while staying at their remote control room or any place that is separated from their farm land. However, there is a common phenomenon in rice planting management stage that some empty areas are randomly located in farmland. Therefore, a critical problem is that the waste of pesticides that occurs when spraying pesticides over rice fields with empty areas by using the common UAV, because it is difficult to control the flow accuracy based on the empty areas changing. To tackle this problem, a novel vision-based spraying system was proposed that can identify empty areas automatically while spraying a precise amount of pesticides on the target regions. By this approach, the image was preprocessed with the Lucy-Richardson algorithm, then the target area was split from the background with k-means and the feature parameters were extracted, finally the feature parameters were filtered out with a positive contribution which would serve as the input parameters of the support vector machine (SVM) to identify the target area. Also a fuzzy control model was analyzed and exerted to compensate the nonlinearity and hysteresis of the variable rate spraying system. Experimental results proved that the approach was applicable to reducing the amount of pesticides during UAV spraying, which can provide a reference for precision agriculture aviation in the future. Keywords: vision sensor, UAV, adaptive spray, variable rate spraying, fuzzy control, empty area, precision agriculture aviation DOI: 10.25165/j.ijabe.20191203.4358 Citation: Wang L H, Lan Y B, Yue X J, Ling K J, Cen Z Z, Cheng Z Y, et al. Vision-based adaptive variable rate spraying approach for unmanned aerial vehicles. Int J Agric & Biol Eng, 2019; 12(3): 18–26.

Author Biographies

Linhui Wang, 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 2. College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China;

South China Agricultural University

Yubin Lan, 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 3. College of Engineering, South China Agricultural University, Guangzhou 510642, China;

South China Agricultural University

Xuejun Yue, 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 2. College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China;

South China Agricultural University

Kangjie Ling, 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 2. College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China;

South China Agricultural University

Zhenzhao Cen, 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 2. College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China;

South China Agricultural University

Ziyao Cheng, 1. International Laboratory of Agricultural Aviation Pesticide Spraying Technology (ILAAPST), Guangzhou 510642, China; 2. College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China;

South China Agricultural University

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Published

2019-06-05

How to Cite

Wang, L., Lan, Y., Yue, X., Ling, K., Cen, Z., Cheng, Z., … Wang, J. (2019). Vision-based adaptive variable rate spraying approach for unmanned aerial vehicles. International Journal of Agricultural and Biological Engineering, 12(3), 18–26. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/4358

Issue

Vol. 12 No. 3 (2019): IJABE

Section

Power and Machinery Systems

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