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
The Sixth Beijing Forum on Human Rights was held on September 12 and 13 with the theme being＂construction of an environment for sustainable human rights development.＂The forum attracted more than100officialsandhuman...The Sixth Beijing Forum on Human Rights was held on September 12 and 13 with the theme being＂construction of an environment for sustainable human rights development.＂The forum attracted more than100officialsandhumanrightsexpertsfromthe United Nations and 33 countries and regions.展开更多
One-dimensional synthetic aperture microwave radiometers have higher spatial resolution and record measurements at multiple incidence angles.In this paper,we propose a multiple linear regression method to retrieve sea...One-dimensional synthetic aperture microwave radiometers have higher spatial resolution and record measurements at multiple incidence angles.In this paper,we propose a multiple linear regression method to retrieve sea surface wind speed at an incidence angle between 0°65°.We assume that a one-dimensional synthetic aperture microwave radiometer operates at frequencies of 6.9,10.65,18.7,23.8 and 36.5 GHz.Then,the microwave radiative transfer forward model is used to simulate the measured brightness temperatures.The sensitivity of the brightness temperatures at 0°65°to the sea surface wind speed is calculated.Then,vertical polarization channels(VR),horizontal polarization channels(HR)and all channels(AR)are used to retrieve the sea surface wind speed via a multiple linear regression algorithm at 0°65°,and the relationship between the retrieval error and incidence angle is obtained.The results are as follows:(1)The sensitivity of the vertical polarization brightness temperature to the sea surface wind speed is smaller than that of the horizontal polarization.(2)The retrieval error increases with Gaussian noise.The retrieval error of VR first increases and then decreases with increasing incidence angle,the retrieval error of HR gradually decreases with increasing incidence angle,and the retrieval error of AR first decreases and then increases with increasing incidence angle.(3)The retrieval error of AR is the lowest and it is necessary to retrieve the sea surface wind speed at a larger incidence angle for AR.展开更多
An intelligent flow control on the flow separation over an airfoil under weak turbulent conditions is investigated and solved by deep reinforcement learning(DRL)method.Both single and synthetic jet control at the airf...An intelligent flow control on the flow separation over an airfoil under weak turbulent conditions is investigated and solved by deep reinforcement learning(DRL)method.Both single and synthetic jet control at the airfoil angles of attack of 10°,13°,15°are compared by training a neural network for closed-loop active flow control strategy based on the soft actor-critic(SAC)algorithm.The training results demonstrate the effectiveness of the deep reinforcement learning-based active flow control method in suppressing the flow separation at high angles of attack,validating its potential in complex flow environments.To improve the stability of the shedding vortex alley over airfoil,a novel reward function considering the vorticity statistics in terms of both vortex and asymmetric shear intensity is first proposed in this work.This vorticity driven reward is demonstrated to perform better in suppressing the rotation and shear intensity and the aerodynamic optimization than the traditional one.Moreover,it can accelerate the convergence speed during the exploration phase.Moreover,it can accelerate the convergence speed during the exploration phase.This study provides valuable insights for future applications of DRL in active flow control under more complex flow conditions.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The Sixth Beijing Forum on Human Rights was held on September 12 and 13 with the theme being＂construction of an environment for sustainable human rights development.＂The forum attracted more than100officialsandhumanrightsexpertsfromthe United Nations and 33 countries and regions.
基金National Natural Science Foundation of China(41475019,41631072)
文摘One-dimensional synthetic aperture microwave radiometers have higher spatial resolution and record measurements at multiple incidence angles.In this paper,we propose a multiple linear regression method to retrieve sea surface wind speed at an incidence angle between 0°65°.We assume that a one-dimensional synthetic aperture microwave radiometer operates at frequencies of 6.9,10.65,18.7,23.8 and 36.5 GHz.Then,the microwave radiative transfer forward model is used to simulate the measured brightness temperatures.The sensitivity of the brightness temperatures at 0°65°to the sea surface wind speed is calculated.Then,vertical polarization channels(VR),horizontal polarization channels(HR)and all channels(AR)are used to retrieve the sea surface wind speed via a multiple linear regression algorithm at 0°65°,and the relationship between the retrieval error and incidence angle is obtained.The results are as follows:(1)The sensitivity of the vertical polarization brightness temperature to the sea surface wind speed is smaller than that of the horizontal polarization.(2)The retrieval error increases with Gaussian noise.The retrieval error of VR first increases and then decreases with increasing incidence angle,the retrieval error of HR gradually decreases with increasing incidence angle,and the retrieval error of AR first decreases and then increases with increasing incidence angle.(3)The retrieval error of AR is the lowest and it is necessary to retrieve the sea surface wind speed at a larger incidence angle for AR.
基金Project supported by the National Natural Science Foundation of China(Grant No.52476033),the 2021 Shanghai Chenguang Program(Grant No.21CGA54).
文摘An intelligent flow control on the flow separation over an airfoil under weak turbulent conditions is investigated and solved by deep reinforcement learning(DRL)method.Both single and synthetic jet control at the airfoil angles of attack of 10°,13°,15°are compared by training a neural network for closed-loop active flow control strategy based on the soft actor-critic(SAC)algorithm.The training results demonstrate the effectiveness of the deep reinforcement learning-based active flow control method in suppressing the flow separation at high angles of attack,validating its potential in complex flow environments.To improve the stability of the shedding vortex alley over airfoil,a novel reward function considering the vorticity statistics in terms of both vortex and asymmetric shear intensity is first proposed in this work.This vorticity driven reward is demonstrated to perform better in suppressing the rotation and shear intensity and the aerodynamic optimization than the traditional one.Moreover,it can accelerate the convergence speed during the exploration phase.Moreover,it can accelerate the convergence speed during the exploration phase.This study provides valuable insights for future applications of DRL in active flow control under more complex flow conditions.
