I have compiled 9 articles from this topic, from the Beijing Agricultural Intelligence Equipment Technology Research Center, Huazhong Agricultural University, China Agricultural University, China Rural Technology Development Center, Shanghai Agricultural Machinery Research Institute, Shanghai Jiaotong University, Shanghai Academy of Agricultural Sciences, Shihezi Shizi University, Shandong Agricultural University and other units. The article includes the integration and development of agricultural machinery and information technology, the application of the hand design of the fruit and vegetable picking machine, the application of automatic navigation and measurement and control technology, natural rubber cutting robot, white asparagus harvesting robot, livestock and poultry anti -epidemic, disinfection robot, wheeled grain combination The design and application of the hardware of the harvesting machine, the standard system of China’s intelligent agricultural machinery equipment, the design and application of the hardware of the automatic navigation vehicle controller controller of the oil and electricity. For everyone reading and reference. Topic-Agricultural robot and intelligent equipment topic-Robot and equipment [1] Chen Xuegeng, Wen Haojun, Zhang Weirong, Pan Fochin, Zhao Yan. Direction [J]. Smart Agriculture (Chinese and English), 2020, 2 (4): 1-16. Chen Xuegeng, wen haojun, zhang weired, Pan Fochu, zhao yan. Advances and Progress of Machinery and Sensing Fusion Fusion Fusion [J]. Smart, 2020, 2 (4): 1-16. Abstract: In order to clarify the development status of the integration of agricultural machinery and information technology at home and abroad, find a key development direction to vigorously promote China’s agricultural machinery intelligence For development, this article first analyzes the current situation of the integration of foreign agricultural machinery and information technology, and summarizes the five major characteristics of its development. Later, although the development of China’s agricultural mechanization has achieved remarkable results, there are still unbalanced development of agricultural machinery informatization, and the recognition of agricultural machinery informatization is not high, enterprises and farmers have not high recognition of agricultural machinery informatization, weak basic research and key technologies, agricultural machinery operations operations, agricultural machinery operations The management level of information system is not high and lack of unified standards. Finally, the direction of the integration of China’s agricultural machinery and information technology, including promoting the development of intelligent perception technology and navigation technology research, promoting the intelligentization of agricultural machinery and equipment, building an agricultural machinery smart operating system, promoting the research of independent operations of agricultural machinery and the construction of unmanned farms, Strengthen the formulation of agricultural machinery information technology standards and compound talent training. The integration of agricultural machinery and information technology is an inevitable trend of the development of modern agricultural machinery in China. The use of information technology to promote the development of agricultural machinery can maximize the guidance effect of information technology and improve agricultural production efficiency. important meaning. This network reading [2] Wu Cambridge, Fan Shengzhe, Gongliang, Yuanjin, Zhou Qiang, Liu Chengliang, fruit and vegetable picking machine system design and control technology research trend and development trend [J]. Smart agriculture. (Chinese and English), 2020, 2 (4): 17-40. wu jianqiao, fan shengzhe, gong liang, yuan jin, zhou qiang, liu. Research status and direction of design and constrol from vegetable picked ROBOT SYSTEM [J]. Smart, 2020, 2 (4): 17-40. Abstract: Fresh fruit and vegetable harvesting is difficult to achieve mechanized operations. High-efficiency and low-loss picking is also a difficult problem in the research and development field of agricultural robots. As a result, the current market -oriented automatic fruit and vegetable pickup equipment is almost blank. In response to the needs of fresh fruits and vegetables, in order to improve the problem of time, labor and efficiency, low efficiency, and low degree of automation, domestic and foreign scholars have designed a series of automated picking equipment to promote the development of agricultural robotics technology. When developing fresh fruit and vegetable picking equipment, we must first determine the harvesting objects and harvesting scenarios. For the growth position, shape and weight of the crops, the complexity of the scene, the degree of automation required, the analysis of the complexity, the analysis of the mechanical characteristics, and the analysis of the characteristics of the mechanical characteristics, and the analysis of the characteristics of the mechanical characteristics, and Press model modeling and other methods to clarify the design needs of agricultural robots. Secondly, as the core executor of the entire picking action, the design of the end actuator of the robot is particularly important. This article classifies the structure of the terminal of the picking robot’s end actuator, summarizes the design process and methods of the end actuator, explains the common end actuator driving method and cutting scheme, and summarizes the fruit collection mechanism. Again, this article outlines the overall control scheme, identification and positioning method, obstacle avoidance method and adaptive control scheme, quality classification method, and human -computer interaction and multi -machine collaboration scheme of picking robots. In order to overall evaluation of the performance of picking robots, this article also proposes an average picking efficiency, long -term picking efficiency, harvesting quality, damage rate, and leakage rate indicators. Finally, this article has a look at the overall development trend of automated picking machinery, indicating the trend of the development of the picking machine manual system, diversified structure, fully automated, intelligent, and cluster development trend towards picking target scenarios. This network reading [3] Wang Chunlei, Li Hongwen, He Jin, Wang Qingjie, Lu Caiyun, Chen Liping. Automatic navigation and measurement and control technology in protective farming [J]. Smart agriculture (smart agriculture (smart agriculture ( Chinese and English), 2020, 2 (4): 41-55. Wang Chunlei, Li Hongwen, He Jin, Wangqingjie, Lu CaiYun, Chen Liping. State-OF-The-EROSPECT of Automatic and In tillage [j]. Smart, 2020, 2 (4): 41-55. Abstract: Realizing intelligence is an important way to improve the quality and efficiency of protective farming machinery operations. Automatic navigation and measurement and control technology as intelligent technology The important part of the important component has developed rapidly in protective farming in recent years. This article first starts from the three types of automatic navigation technology of contact type, machine vision and GNSS -free seedlings, explaining the current status of automatic navigation technology in protective farming; , Including the rapid detection technology of the surface straw coverage, the monitoring technology of the sowing parameter of the seedling sowing machine, and the monitoring technology of the protective farming machine operation area; after that, the development status of the protection of protective farming machinery operation control technology is mainly introduced. Sowing machine leakage compensation control technology and operation depth control technology. Finally, on the basis of the existing application of automatic navigation and measurement and control technology, it is based on the research direction of the three protective cultivation equipment, operating parameter monitoring technology, and protective farming machinery operation control technology in the future. This network reading [4] Zhou Hang, Zhang Shun Road, Zhai Yihao, Wang Song, Zhang Chunlong, Zhang Junxiong, Li Wei. Natural rubber cutting robot visual servo control method and glue cutting test [J]. Smart agriculture (medium英文), 2020, 2(4): 56-64.rn ZHOU Hang, ZHANG Shunlu, ZHAI Yihao, WANG Song, ZHANG Chunlong, ZHANG Junxiong, LI Wei. Vision servo control method and tapping of natural rubber tapping robot [J]. Smart, 2020, 2 (4): 56-64. Abstract: Automated glue can not only liberate the rubber from the heavy physical labor and the harsh working environment, but also reduce the glue worker Technical dependence has greatly improved production efficiency. Realizing the independent acquisition of operating information in the non -structural environment and the positioning of the rubber position servo control are the key technologies of glue robots. For technical difficulties such as complex and changeable working environment, superimposed work information, similar target background characteristics, Asian millimeter -level operating accuracy requirements, and other technical difficulties, this study uses rubber trees in artificial rubber forests as a glue -cutting robot. , Planning robots to quickly approach and stay away from the movement path of the operation space; use the two -dimensional visual technology of the two -dimensional eye to obtain the trunk and cutting structure parameters, and integrate the robot sports science, machine vision technology, and multi -sensor feedback control technology to develop glue -cutting robotic prototypes. The rubber -cutting robot is mainly composed of rail -type robotic mobile platform, multi -joint robotic arm, two -dimensional stereo visual system, and end actuator. The results of the cutting test conducted in the natural rubber forest in Hainan show that when the rubber bark cuts 1 mm thick in rubber cutting robots, the skin consumption error is about 0.28 mm, and the cutting depth error is about 0.49 mm. The study can provide technical reference for exploring the automated rubber cutting operation of natural rubber trees. This network reading [5] Li Yang, Zhang Ping, Yuanjin, Liu Xuemei. White asparagus harvesting robot visual positioning and harvest path optimization method [J]. Smart agriculture (Chinese and English), 2020, 2020 , 2 (4): 65-78. Li Yang, zhang Ping, Yuan Jin, liu Xuemei. Visual and PATH of White Asparagus Robot [J]. Smart, 2020, 2 (4): 65-78. Abstract: The selective harvest of the unearthed state of bamboo shoots is currently recognized by white asparagus. Aiming at the identification difficulties such as bamboo tip of the bamboo tip of the bamboo shoots during the harvesting process, the bamboo tip of the bamboo shoots is similar to the monopoly surface texture and color, and this study proposes a variable -scale interest area (ROI) detection method. The technologies such asization, morphology, and texture filtering have studied the method of identification and accurate positioning of bamboo shoots; based on the positioning of multiple bamboo shoots, the method of harvesting path optimization of multiple bamboo shoots is proposed to solve the unreasonable harvesting path. The problem of low harvesting efficiency. First of all, real -time collection of harvested area images through the robot vision system and the RGB triple -channel Gaussian filtering, using HSV color gamut transformation and the average value of the histogram. Based on this, analyze the characteristics of bamboo tips and soil, and study the variable -scale ROI detection method based on the degree of bamboo shoot buds. Set the circular threshold of the bamboo shoot tip, and refer to the texture feature parameters to determine the position of the bamboo shoot tip, calculate its geometric center, and obtain the coordinates of the basement center of the bamboo tip. Secondly, in order to achieve the efficient harvest of white asparagus, according to the location of the multi -target point and the set point, this study has designed a harvesting path optimization algorithm based on multi -fork trees to obtain the most target bamboo shoot tip of the most target bamboo shoot tips. You can close the road. Finally, the establishment of the harvesting robot test platform was set up to conduct a test of bamboo shoot tip positioning and harvest verification test. The results show that the recognition rate of white asparagus in the visual system can reach 98.04%, and the maximum error of the positioning center coordinates of the tip of the bamboo shoots is 0.879 mm and the Y direction is 0.882 mm. The average movement distance of the end actuator can save 43.89%, the success rate of the positioning of the end actuator reached 100%, and the white asparagus harvesting in the laboratory environment reached 88.13%. Feasibility of sexual harvest. This network reading [6] Feng Youth, Wang Xiu, Qiu Quan, Zhang Chunfeng, Li Bin, Xu Ruifeng, Chen Liping. ), 2020, 2 (4): 79-88. feng Qingchun, Wang Xiu, qiu Quan, zhang Chunfeng, Li Bin, xu ruifeng, chenling. Design and test of robotstock and public ]. Smart, 2020, 2 (4): 79-88. Abstract: Aiming at the problem of high intensity and poor safety of livestock and poultry breeding, poultry breeding, and disinfection. Intelligent operation of spray. The robot system is composed of four parts: mobile carrying platform, epidemic -proof spray component, environmental monitoring sensor, and controller. It supports two working modes: fully automatic operation and remote control operation. Aiming at the conditional conditions of weak light and low stress in livestock and poultry houses, the navigation path detection method of the combination of “magnetic tag-radio frequency recognition” is proposed to realize the autonomous movement between the breeding cage in the livestock and poultry house. The wind -assisted medicinal nozzle is designed to simultaneously achieve the atomization and diffusion of the disinfection solution. By simulating the fluid dynamics of the inner cavity of the nozzle, the spray gas diversion and the structure parameters of the liquid liquid liquid liquid liquid were optimized. 90. Finally, the robot navigation and spray performance were performed on the spot in the poultry house. The test results show that the robotic mobile platform can meet the automatic line navigation of the 0.1 ~ 0.5 m/s speed range. The actual trajectory is relatively off the maximum displacement of the magnetic nail. /MIN’s medicinal liquid spray, the fogd drop diameter (DV.9) formed is 51.82 ~ 137.23 μm, and the density of the fog drops is 116 ~ 149/cm2. This livestock and poultry cottage and divertal disinfection robot can realize the intelligent spray operation of disinfection and immune medicinal solution in the breeding house. This network reading [7] Ding Youchun, Wang Xuping, Peng Jingye, Xiazhongzhou. The design and test of the visual navigation system of wheeled grain harvesting machine [J]. Smart agriculture (Chinese and English), 2020, 2 (2 (2020, 2 (2 (2020, 2 (2 (2020, 2 (2 4): 89-102. ding youchun, wang xuping, peng jingye, xia zhongzhou. Visual system for whenl-type grain condest [j]. Smart, 2020, 2 (4): 89-102. Abstract: In order to improve the quality and efficiency of the harvesting machine’s harvesting machine, the visual navigation control system of wheeled grain joint harvesting machine has been constructed, and the border detection algorithm of grain harvesting border detection algorithm is designed in combination with OPENCV. After pre -processing, secondary edge segmentation, and linear detection, the target path of the visual navigation operation of the joint harvest machine was obtained, and the field dynamic calibration of the field of the field of vision was obtained in accordance with the relative position information of the front vision path; The straight line tracking control method based on the front viewpoint is to maintain the full cut amplitude through pre -correction control to prevent crop leakage. Use relative position deviation values and real -time steering corners as the input of the visual navigation controller. The output steering wheel controls voltage. The results of the rice field test show that the navigation system realizes the reliable collection of the relative position of the field and the stable position of the target direct line path tracking control. In the case of the normal work of the human eye, the detection of the harvest boundary recognition algorithm is accurate The rate is not less than 96.28%, and the single -frame detection time is within 50 ms; the average cutting rate of visual navigation with the premise of leakage is 94.16%. As the number of operations increases, the consistency of the cutting is increasing. This study can provide technical support for the full cutting operation of the joint harvest machine. This network reading [8] Hu Xiaolu, Liang Xuexiu, Zhang Junning, Mei Anjun, Lu Program. China Smart Agricultural Machinery Equipment Standard System Framework Construction and Development Suggestions [J]. Smart agriculture (Chinese and English) , 2020, 2 (4): 116-123. Hu xiaolu, liang xuexiu, zhang junning, mei anjun, lyu chengxu. Of Standard System Framework in China ): 116-123. Abstract: In response to the lack of systemic standard system guidance in the standardization of China’s intelligent agricultural machinery equipment, this study has established a framework for the standard system of China’s intelligent agricultural machinery equipment. First analyze the status and existing problems of the standardization and existence of China’s smart agricultural machinery equipment from the aspects of standard system, specific standards, and internationalization. Objects, standard categories, reference models, industry classifications, industrial links, etc. constitute the dimensions of the standard system framework. Later, the three -dimensional framework structure of China’s intelligent agricultural machinery equipment standard system was constructed by the level, category, and industrial links, and the two -dimensional decomposition of its two -dimensional layer, common general layer and application field layer. Finally, the recommendations and preparation of China’s smart agricultural machinery equipment standards. This study can provide systematic guidance for the revision, implementation and service of China’s smart agricultural machinery equipment standards, and lead the rapid development of China’s smart agricultural machinery equipment industry. This.com read [9] Wu Yingxin, Wu Cambridge, Yang Yutong, Li Mutong, Gan Ling, Gongliang, Liu Chengliang. J]. Smart Agriculture (Chinese and English), 2020, 2 (4): 149-164. Wu yingxin, wu jianqiao, yang Yuhang, Li Mutong, GAN LING, Gong LIANG, LIU. Design and of Hardware- In-looop platform for Agv in hybrid orchard [J]. Smart, 2020, 2 (4): 149-164. The soil humidity is high and the soil is loose. It puts forward higher standards and requirements for the mechanical structure, control system, and the design of the energy power system. The hybrid AGV car can meet the needs of long -distance movement in the orchard. In order to explore the appropriate hybrid AGV control system algorithm and energy management strategies, at the same time, reduce the controller design verification iteration of controller design, the human resources, and time cost caused by the complexity of the orchard terrain. The characteristics of the orchard area are selected to build a series of oil and electric hybrid systems for the establishment of the AGV power energy system model. In addition, in response to the characteristics of the orchard AGV, it needs to adapt to the characteristics of a wide range of terrain, adopt the crawler model structure, use hardware in ring simulation technology, use the raspberry school as the control system to carry the control algorithm, use Matlab and RecurDyn software The real -time simulation model of the driving system, the tracked vehicle driving model, and the system of the pavement model finally realized the hardware of the series mixed power AGV controller in the ring simulation function. The simulation verification verification of the string -level proportional integration (PID) and the fuzzy controller control algorithm shows that the fuzzy controller control algorithm can reduce the time cost brought by the parameter adjustment. Time -grade PID controller generates 10%of the superconducting, while the fuzzy controller is not over -transfer, and the steering is smoother. The results show that the hardware on the ring simulation platform can effectively apply it to the development of the AGV controller of the orchard, avoiding the control of physical tests. While reducing costs, it can speed up the development process of automatic navigation cars in the orchard. This network reading WeChat communication service group It academic exchanges for readers, authors and review experts in the field of agricultural science, promote the development of smart agriculture, and serve the majority of readers, authors and trials to better serve the majority of readers, authors and trials. The manuscript and the editorial department established the WeChat exchange service group, and issues related to the discussions and submission of issues in the professional field can be consulted in the group. This group method: Add WeChat 331760296, remarks: name, unit, research direction, I pull you into the group, institutional marketing advertisers do not disturb. In information release The introduction of scientific research team introduction and recruitment information, academic conferences and related activities
I have compiled 9 articles from this topic, from the Beijing Agricultural Intelligence Equipment Technology Research Center, Huazhong Agricultural University, China Agricultural University, China Rural Technology Development Center, Shanghai Agricultural Machinery Research Institute, Shanghai Jiaotong University, Shanghai Academy of Agricultural Sciences, Shihezi Shizi University, Shandong Agricultural University and other units.
The article includes the integration and development of agricultural machinery and information technology, the application of the hand design of the fruit and vegetable picking machine, the application of automatic navigation and measurement and control technology, natural rubber cutting robot, white asparagus harvesting robot, livestock and poultry anti -epidemic, disinfection robot, wheeled grain combination The design and application of the hardware of the harvesting machine, the standard system of China’s intelligent agricultural machinery equipment, the design and application of the hardware of the automatic navigation vehicle controller controller of the oil and electricity. For everyone reading and reference.
Topic-Agricultural robot and intelligent equipment
topic-Robot and equipment
[1] Chen Xuegeng, Wen Haojun, Zhang Weirong, Pan Fochin, Zhao Yan. Direction [J]. Smart Agriculture (Chinese and English), 2020, 2 (4): 1-16.
Chen Xuegeng, wen haojun, zhang weired, Pan Fochu, zhao yan. Advances and Progress of Machinery and Sensing Fusion Fusion Fusion [J]. Smart, 2020, 2 (4): 1-16.
Abstract: In order to clarify the development status of the integration of agricultural machinery and information technology at home and abroad, find a key development direction to vigorously promote China’s agricultural machinery intelligence For development, this article first analyzes the current situation of the integration of foreign agricultural machinery and information technology, and summarizes the five major characteristics of its development. Later, although the development of China’s agricultural mechanization has achieved remarkable results, there are still unbalanced development of agricultural machinery informatization, and the recognition of agricultural machinery informatization is not high, enterprises and farmers have not high recognition of agricultural machinery informatization, weak basic research and key technologies, agricultural machinery operations operations, agricultural machinery operations The management level of information system is not high and lack of unified standards. Finally, the direction of the integration of China’s agricultural machinery and information technology, including promoting the development of intelligent perception technology and navigation technology research, promoting the intelligentization of agricultural machinery and equipment, building an agricultural machinery smart operating system, promoting the research of independent operations of agricultural machinery and the construction of unmanned farms, Strengthen the formulation of agricultural machinery information technology standards and compound talent training. The integration of agricultural machinery and information technology is an inevitable trend of the development of modern agricultural machinery in China. The use of information technology to promote the development of agricultural machinery can maximize the guidance effect of information technology and improve agricultural production efficiency. important meaning.
This network reading
[2] Wu Cambridge, Fan Shengzhe, Gongliang, Yuanjin, Zhou Qiang, Liu Chengliang, fruit and vegetable picking machine system design and control technology research trend and development trend [J]. Smart agriculture. (Chinese and English), 2020, 2 (4): 17-40.
wu jianqiao, fan shengzhe, gong liang, yuan jin, zhou qiang, liu. Research status and direction of design and constrol from vegetable picked ROBOT SYSTEM [J]. Smart, 2020, 2 (4): 17-40.
Abstract: Fresh fruit and vegetable harvesting is difficult to achieve mechanized operations. High-efficiency and low-loss picking is also a difficult problem in the research and development field of agricultural robots. As a result, the current market -oriented automatic fruit and vegetable pickup equipment is almost blank. In response to the needs of fresh fruits and vegetables, in order to improve the problem of time, labor and efficiency, low efficiency, and low degree of automation, domestic and foreign scholars have designed a series of automated picking equipment to promote the development of agricultural robotics technology. When developing fresh fruit and vegetable picking equipment, we must first determine the harvesting objects and harvesting scenarios. For the growth position, shape and weight of the crops, the complexity of the scene, the degree of automation required, the analysis of the complexity, the analysis of the mechanical characteristics, and the analysis of the characteristics of the mechanical characteristics, and the analysis of the characteristics of the mechanical characteristics, and Press model modeling and other methods to clarify the design needs of agricultural robots. Secondly, as the core executor of the entire picking action, the design of the end actuator of the robot is particularly important. This article classifies the structure of the terminal of the picking robot’s end actuator, summarizes the design process and methods of the end actuator, explains the common end actuator driving method and cutting scheme, and summarizes the fruit collection mechanism. Again, this article outlines the overall control scheme, identification and positioning method, obstacle avoidance method and adaptive control scheme, quality classification method, and human -computer interaction and multi -machine collaboration scheme of picking robots. In order to overall evaluation of the performance of picking robots, this article also proposes an average picking efficiency, long -term picking efficiency, harvesting quality, damage rate, and leakage rate indicators. Finally, this article has a look at the overall development trend of automated picking machinery, indicating the trend of the development of the picking machine manual system, diversified structure, fully automated, intelligent, and cluster development trend towards picking target scenarios.
This network reading
[3] Wang Chunlei, Li Hongwen, He Jin, Wang Qingjie, Lu Caiyun, Chen Liping. Automatic navigation and measurement and control technology in protective farming [J]. Smart agriculture (smart agriculture (smart agriculture ( Chinese and English), 2020, 2 (4): 41-55.
Wang Chunlei, Li Hongwen, He Jin, Wangqingjie, Lu CaiYun, Chen Liping. State-OF-The-EROSPECT of Automatic and In tillage [j]. Smart, 2020, 2 (4): 41-55.
Abstract: Realizing intelligence is an important way to improve the quality and efficiency of protective farming machinery operations. Automatic navigation and measurement and control technology as intelligent technology The important part of the important component has developed rapidly in protective farming in recent years. This article first starts from the three types of automatic navigation technology of contact type, machine vision and GNSS -free seedlings, explaining the current status of automatic navigation technology in protective farming; , Including the rapid detection technology of the surface straw coverage, the monitoring technology of the sowing parameter of the seedling sowing machine, and the monitoring technology of the protective farming machine operation area; after that, the development status of the protection of protective farming machinery operation control technology is mainly introduced. Sowing machine leakage compensation control technology and operation depth control technology. Finally, on the basis of the existing application of automatic navigation and measurement and control technology, it is based on the research direction of the three protective cultivation equipment, operating parameter monitoring technology, and protective farming machinery operation control technology in the future.
This network reading
[4] Zhou Hang, Zhang Shun Road, Zhai Yihao, Wang Song, Zhang Chunlong, Zhang Junxiong, Li Wei. Natural rubber cutting robot visual servo control method and glue cutting test [J]. Smart agriculture (medium英文), 2020, 2(4): 56-64.rn ZHOU Hang, ZHANG Shunlu, ZHAI Yihao, WANG Song, ZHANG Chunlong, ZHANG Junxiong, LI Wei. Vision servo control method and tapping of natural rubber tapping robot [J]. Smart, 2020, 2 (4): 56-64.
Abstract: Automated glue can not only liberate the rubber from the heavy physical labor and the harsh working environment, but also reduce the glue worker Technical dependence has greatly improved production efficiency. Realizing the independent acquisition of operating information in the non -structural environment and the positioning of the rubber position servo control are the key technologies of glue robots. For technical difficulties such as complex and changeable working environment, superimposed work information, similar target background characteristics, Asian millimeter -level operating accuracy requirements, and other technical difficulties, this study uses rubber trees in artificial rubber forests as a glue -cutting robot. , Planning robots to quickly approach and stay away from the movement path of the operation space; use the two -dimensional visual technology of the two -dimensional eye to obtain the trunk and cutting structure parameters, and integrate the robot sports science, machine vision technology, and multi -sensor feedback control technology to develop glue -cutting robotic prototypes. The rubber -cutting robot is mainly composed of rail -type robotic mobile platform, multi -joint robotic arm, two -dimensional stereo visual system, and end actuator. The results of the cutting test conducted in the natural rubber forest in Hainan show that when the rubber bark cuts 1 mm thick in rubber cutting robots, the skin consumption error is about 0.28 mm, and the cutting depth error is about 0.49 mm. The study can provide technical reference for exploring the automated rubber cutting operation of natural rubber trees.
This network reading
[5] Li Yang, Zhang Ping, Yuanjin, Liu Xuemei. White asparagus harvesting robot visual positioning and harvest path optimization method [J]. Smart agriculture (Chinese and English), 2020, 2020 , 2 (4): 65-78.
Li Yang, zhang Ping, Yuan Jin, liu Xuemei. Visual and PATH of White Asparagus Robot [J]. Smart, 2020, 2 (4): 65-78.
Abstract: The selective harvest of the unearthed state of bamboo shoots is currently recognized by white asparagus. Aiming at the identification difficulties such as bamboo tip of the bamboo tip of the bamboo shoots during the harvesting process, the bamboo tip of the bamboo shoots is similar to the monopoly surface texture and color, and this study proposes a variable -scale interest area (ROI) detection method. The technologies such asization, morphology, and texture filtering have studied the method of identification and accurate positioning of bamboo shoots; based on the positioning of multiple bamboo shoots, the method of harvesting path optimization of multiple bamboo shoots is proposed to solve the unreasonable harvesting path. The problem of low harvesting efficiency. First of all, real -time collection of harvested area images through the robot vision system and the RGB triple -channel Gaussian filtering, using HSV color gamut transformation and the average value of the histogram. Based on this, analyze the characteristics of bamboo tips and soil, and study the variable -scale ROI detection method based on the degree of bamboo shoot buds. Set the circular threshold of the bamboo shoot tip, and refer to the texture feature parameters to determine the position of the bamboo shoot tip, calculate its geometric center, and obtain the coordinates of the basement center of the bamboo tip. Secondly, in order to achieve the efficient harvest of white asparagus, according to the location of the multi -target point and the set point, this study has designed a harvesting path optimization algorithm based on multi -fork trees to obtain the most target bamboo shoot tip of the most target bamboo shoot tips. You can close the road. Finally, the establishment of the harvesting robot test platform was set up to conduct a test of bamboo shoot tip positioning and harvest verification test. The results show that the recognition rate of white asparagus in the visual system can reach 98.04%, and the maximum error of the positioning center coordinates of the tip of the bamboo shoots is 0.879 mm and the Y direction is 0.882 mm. The average movement distance of the end actuator can save 43.89%, the success rate of the positioning of the end actuator reached 100%, and the white asparagus harvesting in the laboratory environment reached 88.13%. Feasibility of sexual harvest.
This network reading
[6] Feng Youth, Wang Xiu, Qiu Quan, Zhang Chunfeng, Li Bin, Xu Ruifeng, Chen Liping. ), 2020, 2 (4): 79-88.
feng Qingchun, Wang Xiu, qiu Quan, zhang Chunfeng, Li Bin, xu ruifeng, chenling. Design and test of robotstock and public ]. Smart, 2020, 2 (4): 79-88.
Abstract: Aiming at the problem of high intensity and poor safety of livestock and poultry breeding, poultry breeding, and disinfection. Intelligent operation of spray. The robot system is composed of four parts: mobile carrying platform, epidemic -proof spray component, environmental monitoring sensor, and controller. It supports two working modes: fully automatic operation and remote control operation. Aiming at the conditional conditions of weak light and low stress in livestock and poultry houses, the navigation path detection method of the combination of “magnetic tag-radio frequency recognition” is proposed to realize the autonomous movement between the breeding cage in the livestock and poultry house. The wind -assisted medicinal nozzle is designed to simultaneously achieve the atomization and diffusion of the disinfection solution. By simulating the fluid dynamics of the inner cavity of the nozzle, the spray gas diversion and the structure parameters of the liquid liquid liquid liquid liquid were optimized. 90. Finally, the robot navigation and spray performance were performed on the spot in the poultry house. The test results show that the robotic mobile platform can meet the automatic line navigation of the 0.1 ~ 0.5 m/s speed range. The actual trajectory is relatively off the maximum displacement of the magnetic nail. /MIN’s medicinal liquid spray, the fogd drop diameter (DV.9) formed is 51.82 ~ 137.23 μm, and the density of the fog drops is 116 ~ 149/cm2. This livestock and poultry cottage and divertal disinfection robot can realize the intelligent spray operation of disinfection and immune medicinal solution in the breeding house.
This network reading
[7] Ding Youchun, Wang Xuping, Peng Jingye, Xiazhongzhou. The design and test of the visual navigation system of wheeled grain harvesting machine [J]. Smart agriculture (Chinese and English), 2020, 2 (2 (2020, 2 (2 (2020, 2 (2 (2020, 2 (2 4): 89-102.
ding youchun, wang xuping, peng jingye, xia zhongzhou. Visual system for whenl-type grain condest [j]. Smart, 2020, 2 (4): 89-102.
Abstract: In order to improve the quality and efficiency of the harvesting machine’s harvesting machine, the visual navigation control system of wheeled grain joint harvesting machine has been constructed, and the border detection algorithm of grain harvesting border detection algorithm is designed in combination with OPENCV. After pre -processing, secondary edge segmentation, and linear detection, the target path of the visual navigation operation of the joint harvest machine was obtained, and the field dynamic calibration of the field of the field of vision was obtained in accordance with the relative position information of the front vision path; The straight line tracking control method based on the front viewpoint is to maintain the full cut amplitude through pre -correction control to prevent crop leakage. Use relative position deviation values and real -time steering corners as the input of the visual navigation controller. The output steering wheel controls voltage. The results of the rice field test show that the navigation system realizes the reliable collection of the relative position of the field and the stable position of the target direct line path tracking control. In the case of the normal work of the human eye, the detection of the harvest boundary recognition algorithm is accurate The rate is not less than 96.28%, and the single -frame detection time is within 50 ms; the average cutting rate of visual navigation with the premise of leakage is 94.16%. As the number of operations increases, the consistency of the cutting is increasing. This study can provide technical support for the full cutting operation of the joint harvest machine.
This network reading
[8] Hu Xiaolu, Liang Xuexiu, Zhang Junning, Mei Anjun, Lu Program. China Smart Agricultural Machinery Equipment Standard System Framework Construction and Development Suggestions [J]. Smart agriculture (Chinese and English) , 2020, 2 (4): 116-123.
Hu xiaolu, liang xuexiu, zhang junning, mei anjun, lyu chengxu. Of Standard System Framework in China ): 116-123.
Abstract: In response to the lack of systemic standard system guidance in the standardization of China’s intelligent agricultural machinery equipment, this study has established a framework for the standard system of China’s intelligent agricultural machinery equipment. First analyze the status and existing problems of the standardization and existence of China’s smart agricultural machinery equipment from the aspects of standard system, specific standards, and internationalization. Objects, standard categories, reference models, industry classifications, industrial links, etc. constitute the dimensions of the standard system framework. Later, the three -dimensional framework structure of China’s intelligent agricultural machinery equipment standard system was constructed by the level, category, and industrial links, and the two -dimensional decomposition of its two -dimensional layer, common general layer and application field layer. Finally, the recommendations and preparation of China’s smart agricultural machinery equipment standards. This study can provide systematic guidance for the revision, implementation and service of China’s smart agricultural machinery equipment standards, and lead the rapid development of China’s smart agricultural machinery equipment industry.
This.com read
[9] Wu Yingxin, Wu Cambridge, Yang Yutong, Li Mutong, Gan Ling, Gongliang, Liu Chengliang. J]. Smart Agriculture (Chinese and English), 2020, 2 (4): 149-164.
Wu yingxin, wu jianqiao, yang Yuhang, Li Mutong, GAN LING, Gong LIANG, LIU. Design and of Hardware- In-looop platform for Agv in hybrid orchard [J]. Smart, 2020, 2 (4): 149-164.
The soil humidity is high and the soil is loose. It puts forward higher standards and requirements for the mechanical structure, control system, and the design of the energy power system. The hybrid AGV car can meet the needs of long -distance movement in the orchard. In order to explore the appropriate hybrid AGV control system algorithm and energy management strategies, at the same time, reduce the controller design verification iteration of controller design, the human resources, and time cost caused by the complexity of the orchard terrain. The characteristics of the orchard area are selected to build a series of oil and electric hybrid systems for the establishment of the AGV power energy system model. In addition, in response to the characteristics of the orchard AGV, it needs to adapt to the characteristics of a wide range of terrain, adopt the crawler model structure, use hardware in ring simulation technology, use the raspberry school as the control system to carry the control algorithm, use Matlab and RecurDyn software The real -time simulation model of the driving system, the tracked vehicle driving model, and the system of the pavement model finally realized the hardware of the series mixed power AGV controller in the ring simulation function. The simulation verification verification of the string -level proportional integration (PID) and the fuzzy controller control algorithm shows that the fuzzy controller control algorithm can reduce the time cost brought by the parameter adjustment. Time -grade PID controller generates 10%of the superconducting, while the fuzzy controller is not over -transfer, and the steering is smoother. The results show that the hardware on the ring simulation platform can effectively apply it to the development of the AGV controller of the orchard, avoiding the control of physical tests. While reducing costs, it can speed up the development process of automatic navigation cars in the orchard.
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