The orchards usually have rough terrain,dense tree canopy and weeds.It is hard to use GNSS for autonomous navigation in orchard due to signal occlusion,multipath effect,and radio frequency interference.To achieve auto...The orchards usually have rough terrain,dense tree canopy and weeds.It is hard to use GNSS for autonomous navigation in orchard due to signal occlusion,multipath effect,and radio frequency interference.To achieve autonomous navigation in orchard,a visual navigation method based on multiple images at different shooting angles is proposed in this paper.A dynamic image capturing device is designed for camera installation and multiple images can be shot at different angles.Firstly,the obtained orchard images are classified into sky and soil detection stage.Each image is transformed to HSV space and initially segmented into sky,canopy and soil regions by median filtering and morphological processing.Secondly,the sky and soil regions are extracted by the maximum connected region algorithm,and the region edges are detected and filtered by the Canny operator.Thirdly,the navigation line in the current frame is extracted by fitting the region coordinate points.Then the dynamic weighted filtering algorithm is used to extract the navigation line for the soil and sky detection stage,respectively,and the navigation line for the sky detection stage is mirrored to the soil region.Finally,the Kalman filter algorithm is used to fuse and extract the final navigation path.The test results on 200 images show that the accuracy of visual navigation path fitting is 95.5%,and single frame image processing costs 60 ms,which meets the real-time and robustness requirements of navigation.The visual navigation experiments in Camellia oleifera orchard show that when the driving speed is 0.6 m/s,the maximum tracking offset of visual navigation in weed-free and weedy environments is 0.14 m and 0.24 m,respectively,and the RMSE is 30 mm and 55 mm,respectively.展开更多
In the contemporary artistic circle,it is not rare for a person at the age of knowing his destiny to start learning painting and be a professional.It is also not at all surprising that one close to 60 years old starts...In the contemporary artistic circle,it is not rare for a person at the age of knowing his destiny to start learning painting and be a professional.It is also not at all surprising that one close to 60 years old starts to study painting art in a professional art school.Yet,we will consider the idea and action too naive like The Arabian Nights or a fool's paradise,if one of our friends just starts learning painting for only three or four years,abandons his family and career,goes to Beijing alone to find展开更多
A machine-vision-based method of locating crops is described in this research.This method was used to provide real-time positional information of crop plants for a mechanical intra-row weeding robot.Within the normali...A machine-vision-based method of locating crops is described in this research.This method was used to provide real-time positional information of crop plants for a mechanical intra-row weeding robot.Within the normalized red,green,and blue chromatic coordinates(rgb),a modified excess green feature(g-r>T&g-b>T)was used to segment plant material from back ground in color images.The threshold T was automatically selected by the maximum variance(OTSU)algorithm to cope with variable natural light.Taking into account the geometry of the camera arrangement and the crop row spacing,the target regions covering the crop rows were defined based on a pinhole camera model.According to the statistical variation in the pixel histogram in each target region,locations of the crop plants were initially estimated.To obtain the accurate locations of crops,median filtering was conducted locally in the bounding boxes of the crops close to the bottom of the images.For the lateral guidance of the robot,a novel method of calculating lateral offset was proposed based on a simplified match between a template and the detected crops.Field experiments were conducted under three different illumination conditions.The results showed that the accurate identification rates on lettuce,cauliflower and maize were all above 95%.The positional error as within±15 mm,and the average processing time for a 640×480 image was 31 ms.The method was adequate to meet the technical requirement of the weeding robot,and laid a foundation for robotic weeding in commercial production system.展开更多
Following the previous work,in this paper,the antireflective films thicknesses,refractive indexes and reflectance spectra of different color categories of the polycrystalline silicon cells are tested and compared.It i...Following the previous work,in this paper,the antireflective films thicknesses,refractive indexes and reflectance spectra of different color categories of the polycrystalline silicon cells are tested and compared.It is found that the color difference of polycrystalline silicon cells is mainly caused by the antireflective film.Then the matrix transfer method is used to simulate the reflection spectra according to the actual tested parameters of the samples,and the effectiveness of the simulation is verified.Finally,according to the distribution of the spectral solar irradiance,the total solar absorption of the polycrystalline silicon cells with different antireflective film thicknesses is simulated.The optimal value of the antireflective film thickness of the polycrystalline silicon cell is calculated.This study has important guiding significance for photovoltaic(PV)enterprises to realize the optimal production of plasma enhanced chemical vapor deposition(PECVD)process in production.展开更多
基金National Key Research and Development Program of China(2022YFD2202103)National Natural Science Foundation of China(31971798)+2 种基金Zhejiang Provincial Key Research&Development Plan(2023C02049、2023C02053)SNJF Science and Technology Collaborative Program of Zhejiang Province(2022SNJF017)Hangzhou Agricultural and Social Development Research Project(202203A03)。
文摘The orchards usually have rough terrain,dense tree canopy and weeds.It is hard to use GNSS for autonomous navigation in orchard due to signal occlusion,multipath effect,and radio frequency interference.To achieve autonomous navigation in orchard,a visual navigation method based on multiple images at different shooting angles is proposed in this paper.A dynamic image capturing device is designed for camera installation and multiple images can be shot at different angles.Firstly,the obtained orchard images are classified into sky and soil detection stage.Each image is transformed to HSV space and initially segmented into sky,canopy and soil regions by median filtering and morphological processing.Secondly,the sky and soil regions are extracted by the maximum connected region algorithm,and the region edges are detected and filtered by the Canny operator.Thirdly,the navigation line in the current frame is extracted by fitting the region coordinate points.Then the dynamic weighted filtering algorithm is used to extract the navigation line for the soil and sky detection stage,respectively,and the navigation line for the sky detection stage is mirrored to the soil region.Finally,the Kalman filter algorithm is used to fuse and extract the final navigation path.The test results on 200 images show that the accuracy of visual navigation path fitting is 95.5%,and single frame image processing costs 60 ms,which meets the real-time and robustness requirements of navigation.The visual navigation experiments in Camellia oleifera orchard show that when the driving speed is 0.6 m/s,the maximum tracking offset of visual navigation in weed-free and weedy environments is 0.14 m and 0.24 m,respectively,and the RMSE is 30 mm and 55 mm,respectively.
文摘In the contemporary artistic circle,it is not rare for a person at the age of knowing his destiny to start learning painting and be a professional.It is also not at all surprising that one close to 60 years old starts to study painting art in a professional art school.Yet,we will consider the idea and action too naive like The Arabian Nights or a fool's paradise,if one of our friends just starts learning painting for only three or four years,abandons his family and career,goes to Beijing alone to find
基金The authors acknowledge that this research was financially supported by the National“863 Plan”of China(2013AA102406)National Natural Science Foundation of China(31301232)+1 种基金Chinese Universities Scientific Fund(2015QC004)Beijing Higher Education Young Elite Teacher Project(31056101).
文摘A machine-vision-based method of locating crops is described in this research.This method was used to provide real-time positional information of crop plants for a mechanical intra-row weeding robot.Within the normalized red,green,and blue chromatic coordinates(rgb),a modified excess green feature(g-r>T&g-b>T)was used to segment plant material from back ground in color images.The threshold T was automatically selected by the maximum variance(OTSU)algorithm to cope with variable natural light.Taking into account the geometry of the camera arrangement and the crop row spacing,the target regions covering the crop rows were defined based on a pinhole camera model.According to the statistical variation in the pixel histogram in each target region,locations of the crop plants were initially estimated.To obtain the accurate locations of crops,median filtering was conducted locally in the bounding boxes of the crops close to the bottom of the images.For the lateral guidance of the robot,a novel method of calculating lateral offset was proposed based on a simplified match between a template and the detected crops.Field experiments were conducted under three different illumination conditions.The results showed that the accurate identification rates on lettuce,cauliflower and maize were all above 95%.The positional error as within±15 mm,and the average processing time for a 640×480 image was 31 ms.The method was adequate to meet the technical requirement of the weeding robot,and laid a foundation for robotic weeding in commercial production system.
基金supported by the Research Project of Tianjin Municipal Education Commission(No.2020KJ088)
文摘Following the previous work,in this paper,the antireflective films thicknesses,refractive indexes and reflectance spectra of different color categories of the polycrystalline silicon cells are tested and compared.It is found that the color difference of polycrystalline silicon cells is mainly caused by the antireflective film.Then the matrix transfer method is used to simulate the reflection spectra according to the actual tested parameters of the samples,and the effectiveness of the simulation is verified.Finally,according to the distribution of the spectral solar irradiance,the total solar absorption of the polycrystalline silicon cells with different antireflective film thicknesses is simulated.The optimal value of the antireflective film thickness of the polycrystalline silicon cell is calculated.This study has important guiding significance for photovoltaic(PV)enterprises to realize the optimal production of plasma enhanced chemical vapor deposition(PECVD)process in production.
