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公开(公告)号：US20230136427A1
公开(公告)日：2023-05-04
申请号：US17720841
申请日：2022-04-14
发明人： Yu TANG , Yiqing FU , Jiahao LI , Jiepeng YANG , Jinfei ZHAO , Weizhao CHEN , Xiaodi ZHANG , Zhiping TAN , Qiwei GUO , Xincai ZHUANG , Huasheng HUANG , Chaojun HOU , Jiajun ZHUANG , Aimin MIAO , Shaoming LUO
摘要： Disclosed is a fruit picking method based on a visual servo control robot, comprising: placing a throwing apparatus and a fixed photosensitive device at a first position to obtain a fixed photosensitive image; generating a first throwing path, a second throwing path, and a third throwing path; arranging recovery apparatuses; performing simultaneous rotational throwing processing to throw a first wireless photosensitive device, a second wireless photosensitive device, and a third wireless photosensitive device; receiving a first photosensitive image sequence and a second photosensitive image sequence of the first wireless photosensitive device and the second wireless photosensitive device; receiving a third photosensitive image sequence of the third wireless photosensitive device; generating a spatial position of a fruit on a to-be-picked fruit tree; and performing fruit picking processing using the visual servo control robot according to the spatial position of the fruit.
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2.发明申请公开(公告)号：US20230133055A1
公开(公告)日：2023-05-04
申请号：US17710918
申请日：2022-03-31
发明人： Yu TANG , Shaoming LUO , Jiepeng YANG , Yiqing FU , Jinfei ZHAO , Jiahao LI , Zhiping TAN , Huasheng HUANG , Qiwei GUO , Weizhao CHEN
IPC分类号： G06T7/00
摘要： Disclosed is a method for detecting an infection stage of anthracnose pathogen with pre-analysis capacity, comprising: obtaining a plurality of sample sensing data sequences; obtaining a sample citrus leaf image; obtaining a first prediction result; if the first prediction result is that the sample citrus crop is not infected by anthracnose, obtaining sample Raman spectral data and sample hyperspectral data; obtaining a first judgment result, and obtaining a second judgment result; performing labeling to obtain second training data; training a neural network model to obtain a second anthracnose prediction model; obtaining a plurality of to-be-analyzed sensing data sequences; obtaining a to-be-analyzed citrus leaf image; obtaining a second prediction result; if the second prediction result is that the to-be-analyzed citrus crop is not infected by anthracnose, obtaining a third prediction result.
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公开(公告)号：US20220377980A1
公开(公告)日：2022-12-01
申请号：US17744053
申请日：2022-05-13
发明人： Yu TANG , Shaoming LUO , Weizhao CHEN , Jiahao LI , Jiepeng YANG , Yiqing FU , Jinfei ZHAO , Xiaodi ZHANG , Qiwei GUO , Xincai ZHUANG , Huasheng HUANG , Chaojun HOU , Jiajun ZHUANG , Aimin MIAO
摘要： The application discloses a fruit picking method based on a three-dimensional parameter prediction model for a fruit. The method comprises: performing first-time image acquisition processing on a to-be-picked fruit to obtain a first image; determining a first range; controlling a manipulator to perform first-time moving processing; performing intermittent gas injection treatment to lead to forced vibration of the to-be-picked fruit; performing second-time image acquisition processing many times to obtain a plurality of second images; screening out, by taking the first image as an reference object, two appointed second images deviating from an equilibrium position to the maximum extent; jointly inputting the images into a preset three-dimensional parameter prediction model for the fruit so as to obtain predicted three-dimensional parameters; controlling the manipulator to perform second-time moving processing; and performing cutting processing on a fruit stem position to make the to-be-picked fruit fall onto the manipulator.
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公开(公告)号：US20230132580A1
公开(公告)日：2023-05-04
申请号：US17710938
申请日：2022-03-31
发明人： Yu TANG , Yiqing FU , Jiahao LI , Jiepeng YANG , Jinfei ZHAO , Weizhao CHEN , Xiaodi ZHANG , Zhiping TAN , Qiwei GUO , Xincai ZHUANG , Huasheng HUANG , Chaojun HOU , Jiajun ZHUANG , Aimin MIAO , Shaoming LUO
摘要： Disclosed is a fruit picking method based on a visual servo control robot, comprising: placing a throwing apparatus and a fixed photosensitive device at a first position to obtain a fixed photosensitive image; generating a first throwing path, a second throwing path, and a third throwing path; arranging recovery apparatuses; performing simultaneous rotational throwing processing to throw a first wireless photosensitive device, a second wireless photosensitive device, and a third wireless photosensitive device; receiving a first photosensitive image sequence and a second photosensitive image sequence of the first wireless photosensitive device and the second wireless photosensitive device; receiving a third photosensitive image sequence of the third wireless photosensitive device; generating a spatial position of a fruit on a to-be-picked fruit tree; and performing fruit picking processing using the visual servo control robot according to the spatial position of the fruit.
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公开(公告)号：US20230214997A1
公开(公告)日：2023-07-06
申请号：US17816246
申请日：2022-07-29
发明人： Zhiping TAN , Yu TANG , Jiepeng YANG , Yiqing FU , Jinfei ZHAO , Jiahao LI , Qiwei GUO , Huasheng HUANG
CPC分类号： G06T7/0012 , G06V10/82 , G06V10/774 , G06V20/188 , A01G22/05 , A01B79/005 , G06T2207/10028 , G06T2207/10036 , G06T2207/20081 , G06T2207/20084 , G06T2207/30188
摘要： The present invention relates to the technical field of field crop cultivation, more particularly to a training method, an evaluation method, an electronic device and a storage medium. According to the present invention, a multispectral three-dimensional point cloud map is obtained through depth information and multispectral information, and the multispectral three-dimensional point cloud map is analyzed by utilizing an FVNet three-dimensional target detection algorithm, thereby acquiring crop feature information. Thus, more comprehensive crop information can be obtained, and a crop state evaluation model constructed based on an artificial neural network can be further trained with the crop feature information.
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公开(公告)号：US20220383610A1
公开(公告)日：2022-12-01
申请号：US17742701
申请日：2022-05-12
发明人： Yu TANG , Shaoming LUO , Weizhao CHEN , Jiahao LI , Jiepeng YANG , Yiqing FU , Jinfei ZHAO , Xiaodi ZHANG , Qiwei GUO , Xincai ZHUANG , Huasheng HUANG , Chaojun HOU , Jiajun ZHUANG , Aimin MIAO
摘要： A citrus identification method comprises: performing first-time image acquisition processing on a target citrus tree to obtain a first image; inputting the first image into a first citrus fruit identification model to be processed to obtain a first identification result sequence; performing area interception processing on the first image to obtain a citrus fruit area; obtaining roundness integrity numerical values; selecting an appointed roundness integrity numerical value, and acquiring a defect position of an appointed citrus fruit in the first image; determining a first spatial range and a second spatial range; performing both first spray injection treatment and second spray injection treatment; performing second-time image acquisition processing to obtain a second image; inputting the second image into a second citrus fruit identification model to be processed to obtain a second identification result; and generating a citrus fruit identification result.
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