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3D Locating System for Pests' Laser Control Based on Multi-Constraint Stereo Matching

文献类型： 外文期刊

作者： Li, Yajun 1 ; Feng, Qingchun 2 ; Lin, Jiewen 3 ; Hu, Zhengfang 1 ; Lei, Xiangming 1 ; Xiang, Yang 1 ;

作者机构： 1.Hunan Agr Univ, Coll Mech & Elect Engn, Changsha 410128, Peoples R China

2.Beijing Acad Agr & Forestry Sci, Intelligent Equipment Res Ctr, Beijing 100097, Peoples R China

3.China Agr Univ, Coll Engn, Beijing 100083, Peoples R China

关键词： robotic pest control; Mask R-CNN; skeleton extraction; binocular vision; stereo matching

期刊名称：AGRICULTURE-BASEL （ 影响因子：3.408； 五年影响因子：3.459 ）

ISSN：

年卷期： 2022 年 12 卷 6 期

页码：

收录情况： SCI

摘要： To achieve pest elimination on leaves with laser power, it is essential to locate the laser strike point on the pest accurately. In this paper, Pieris rapae (L.) (Lepidoptera: Pieridae), similar in color to the host plant, was taken as the object and the method for identifying and locating the target point was researched. A binocular camera unit with an optical filter of 850 nm wavelength was designed to capture the pest image. The segmentation of the pests' pixel area was performed based on Mask R-CNN. The laser strike points were located by extracting the skeleton through an improved ZS thinning algorithm. To obtain the 3D coordinates of the target point precisely, a multi-constrained matching method was adopted on the stereo rectification images and the subpixel target points in the images on the left and right were optimally matched through fitting the optimal parallax value. As the results of the field test showed, the average precision of the ResNet50-based Mask R-CNN was 94.24%. The maximum errors in the X-axis, the Y-axis, and the Z-axis were 0.98, 0.68, and 1.16 mm, respectively, when the working depth ranged between 400 and 600 mm. The research was supposed to provide technical support for robotic pest control in vegetables.

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