This topic I *** collated 9 articles from Beijing Agricultural Intelligent Equipment Technology Research Center, Huazhong Agricultural University, China Agricultural University, China Rural Technology Development Center, Shanghai Agricultural Machinery Research Institute, Shanghai Jiao Tong University, Shanghai Academy of Agricultural Sciences, Shihezi University, Shandong Agricultural University and other units.
The article contains the integration of agricultural machinery and information technology development, fruit and vegetable picking robot design, automatic navigation and measurement and control technology applications, natural rubber cutting robot, white asparagus harvesting robot, livestock and poultry house epidemic prevention and disinfection robots, wheeled grain combine harvester, China's intelligent agricultural machinery and equipment standard system, hybrid oil-electric orchard automatic navigation vehicle controller hardware design and application, and other content. For your reading and reference.
Topic--Agricultural Robot and Intelligent Equipment
Topic--Agricultural Robot and Intelligent Equipment
[1]Xuegeng Chen, Haojun Wen, Weirong Zhang , PAN Fo-Yi, ZHAO Yan. Development Status and Direction of Agricultural Machinery and Information Technology Integration[J]. Intelligent Agriculture (in Chinese and English), 2020, 2(4): 1-16.
CHEN Xuegeng, WEN Haojun, ZHANG Weirong, PAN Fochu, ZHAO Yan. Advances and progress of agricultural machinery and Advances and progress of agricultural machinery and sensing technology fusion[J]. Advances and progress of agricultural machinery and sensing technology fusion[J]. Smart Agriculture, 2020, 2(4): 1-16. This paper first analyzes the status quo of the integration of foreign agricultural machinery and information technology development, and summarizes the five characteristics of its development. This paper firstly analyzes the current situation of the development of agricultural machinery and information technology in foreign countries and summarizes the five characteristics of its development. After that, it points out that although the development of agricultural mechanization in China has achieved remarkable results, there still exists the imbalance in the regional and structural development of the integration of information technology in agricultural machinery, the acceptance of the enterprises and farmers to the information technology of agricultural machinery is not high, the research on the basic research and the key technology is weak, and the management of information system of agricultural machinery operation is not at a high level and lacks the unified standard. Finally, it puts forward the direction of the integration of Chinese agricultural machinery and information technology, including promoting the development of intelligent perception technology and navigation technology research, advancing the intelligentization of agricultural machinery and equipment, constructing the intelligent operation system of agricultural machinery, advancing the research of autonomous operation technology of agricultural machinery and the construction of unmanned farms, and strengthening the formulation of technical standards for information technology of agricultural machinery and the cultivation of composite talents. The integration of agricultural machinery and information technology is an inevitable trend in the development of China's modern agricultural machinery, the use of information technology to promote the development of agricultural machinery, can maximize the use of information technology to guide the effect of improving the efficiency of agricultural production, and for the promotion of China's high quality and efficient development of agricultural machinery is of great significance.
Internet Reading
[2] Cambridge Wu, Shengzhe Fan, Liang Gong, Yuan Jin, Qiang Zhou, Chengliang Liu. Research status and development trend of fruit and vegetable picking robot system design and control technology[J]. Intelligent Agriculture (in Chinese and English), 2020, 2(4): 17-40.
WU Jianqiao, FAN Shengzhe, GONG Liang, YUAN Jin, ZHOU Qiang, LIU Chengliang. Research status and development Research status and development direction of design and control technology of fruit and vegetable picking robot system[J]. Smart Agriculture, 2020, 2(4): 17-40.
Abstract: Fresh fruit and vegetable harvesting is a difficult production process to realize mechanization, and efficient and low-loss picking is also a difficult problem in the field of agricultural robotics research and development, which has led to the current market of automated fruit and vegetable harvesting equipment production and application of the almost blank. For fresh fruit and vegetable picking needs, in order to improve the manual picking time-consuming and laborious, inefficient, low degree of automation, in the past 30 years, scholars at home and abroad designed a series of automated picking equipment, promoting the development of agricultural robotics. In the development of fresh fruit and vegetable picking equipment, the first step is to determine the harvesting object and harvesting scene, and to clarify the design requirements of agricultural robots through complexity estimation, mechanical characterization, and attitude modeling for the growth position, shape and weight of the crop, the complexity of the scene, and the required degree of automation. Secondly, as the core executor of the whole picking action, the design of the end-effector of the picking robot is particularly important. This paper classifies the structure of the end-effector of the picking robot, summarizes the design process and method of the end-effector, describes the common end-effector drive mode, cutting scheme, and outlines the fruit collection mechanism. Again, this paper outlines the overall control scheme, identification and localization method, obstacle avoidance method and adaptive control scheme, quality classification method, as well as human-machine interaction and multi-machine collaboration scheme of the picking robot. In order to evaluate the performance of the picking robot in general, this paper also proposes the average picking efficiency, long-term picking efficiency, harvest quality, damage rate and leakage rate indicators. Finally, this paper provides an outlook on the overall development trend of automated picking machinery, indicating that the picking robotic system will develop in the direction of generalization of picking target scenarios, diversification of structural forms, full automation, intelligence, and clustering.
Informed Reading
[3] Chunlei Wang, Hongwen Li, Jin He, Qingjie Wang, Caiyun Lu, Liping Chen. Current status and outlook of the application of automatic navigation and measurement and control technology in conservation tillage[J]. Intelligent Agriculture (in Chinese and English), 2020, 2(4): 41-55.
WANG Chunlei, LI Hongwen, HE Jin, WANG Qingjie, LU Caiyun, CHEN Liping. State-of-the-art and prospect of automatic navigation and measurement techniques application in conservation tillage[J]. State-of-the-art and prospect of automatic navigation and measurement techniques application in conservation tillage[J]. Smart Agriculture, 2020, 2(4): 41-55.
Abstract: Achieving intelligence is an important way to improve the quality and efficiency of conservation tillage implements, and automatic navigation and measurement and control technology, as an important part of intelligent technology, has been rapidly developed for conservation tillage application in recent years. This paper firstly describes the current status of the application of automatic navigation technology in conservation tillage, starting from the contact type, machine vision type and GNSS type three kinds of no-tillage seeding automatic navigation technology; and then gives a detailed introduction to the development of the operational parameter monitoring technology, including the rapid detection technology of surface straw coverage, the monitoring technology of no-tillage seeding machine sowing parameter, and the monitoring technology of the operational area of conservation tillage implements; After that, the development status of operation control technology of protective tillage implements is elaborated, mainly introducing the leakage compensation control technology of no-few-tillage seeder and operation depth control technology. Finally, on the basis of summarizing the existing applications of automatic navigation and measurement and control technology in conservation tillage, it looks forward to the future research direction of automatic navigation technology of conservation tillage implements, operation parameter monitoring technology and operation control technology of conservation tillage implements.
Informed Reading
[4] Zhou Hang, Zhang Shunlu, Zhai Yihao, Wang Song, Zhang Chunlong, Zhang Junxiong, Li Wei. Visual servo control method and cutting test of natural rubber cutting robot[J]. Intelligent Agriculture (in Chinese and English), 2020, 2(4): 56-64.
ZHOU Hang, ZHANG Shunlu, ZHAI Yihao, WANG Song, ZHANG Chunlong, ZHANG Junxiong, LI Wei. Vision servo control method and tapping experiment of natural rubber tapping robot[J]. Smart Agriculture, 2020, 2(4): 56-64.
Abstract: Automated rubber cutting can not only liberate rubber workers from heavy physical labor and poor working environment, but also reduce the technical dependence on rubber workers and greatly improve the production efficiency. The realization of the non-structural environment of the work of autonomous information acquisition and cutting position servo control is the key technology of the rubber cutting robot. In view of the complexity and variability of the working environment, the superimposed interaction of operational information, the similarity of the target background characteristics, and the requirements of sub-millimeter operational accuracy and other technical difficulties, this study develops a rubber cutting robot with rubber trees in artificial rubber forests as the rubber cutting object, and plans the robot's movement path to quickly approach and move away from the operating space by establishing a spatial mathematical model of the rubber cutting trajectory; adopts the binocular stereo vision technology to obtain the structural parameters of the tree trunk and the cutting line The modularized prototype of the rubber cutting robot is developed by integrating robot kinematics, machine vision technology and multi-sensor feedback control technology. The rubber cutting robot is mainly composed of a rail-type robot mobile platform, multi-joint robotic arm, binocular stereo vision system and end-effector. In Hainan natural rubber forest cut rubber test results show that in the rubber cutting robot cutting 1 mm thick rubber bark, the error of the amount of skin consumption is about 0.28 mm, the cutting depth error is about 0.49 mm. this research can be used to explore the automation of natural rubber tree rubber cutting operations to provide technical reference.
Internet Reading
[5] Yang Li, Ping Zhang, Yuan Jin, Xuemei Liu. Optimization method of visual localization and harvesting path for white asparagus harvesting robot[J]. Intelligent Agriculture (in Chinese and English), 2020, 2(4): 65-78.
LI Yang, ZHANG Ping, YUAN Jin, LIU Xuemei. Visual positioning and harvesting path optimization of white asparagus harvesting robot[J]. Smart Agriculture, 2020, 2(4): 65-78.
Abstract: Selective harvesting based on shoot emergence status is currently recognized as the best harvesting method for white asparagus. In order to address the recognition problems of machine vision identification of shoot tips in the harvesting process, such as the similarity of shoot tips with the texture and color of the ridge surface, this study proposes a variable-scale region of interest (ROI) detection method, integrating image color gamut transformation, histogram averaging, morphology, texture filtering and other techniques, and researches the shoot tip identification and accurate positioning method; on the basis of locating the coordinates of multi-shoot tips, it proposes the optimization method of the harvest path of multi-sun shoots, which solves the problem of the harvest path due to the emergence status of white asparagus shoots. On the basis of locating the coordinates of multiple shoot tips, a method of optimizing the harvesting path of multiple shoots was proposed, which solved the problem of low harvesting efficiency caused by unreasonable harvesting path. First of all, the robot vision system collects images of the harvesting area in real time and performs RGB three-channel Gaussian filtering, HSV color domain transformation and histogram homogenization. On this basis, feature clustering analysis was performed on the shoot tips and soil, variable scale ROI detection method was studied according to the degree of shoot extraction, the morphology of the shoot tips and the texture of the shoot tips and soil in the collected images were statistically analyzed, the roundness threshold of the shoot tips was set, and with reference to the texture feature parameter, the location of the shoot tips was determined, and the geometrical centers of the shoots were calculated to obtain the center coordinate of the shoot tips' contour. Secondly, in order to achieve efficient harvesting of white asparagus, according to the location distribution of multi-target points and collection points, this study designs a harvesting path optimization algorithm based on the traversal of multinomial trees, in order to obtain the optimal harvesting paths of multiple target shoot tips. Finally, a harvesting robot test platform was built to carry out the validation test of shoot tip localization and harvesting. The results show that the recognition rate of the vision system for white asparagus can reach 98.04%, the maximum error in the positioning of the center coordinates of the shoot tip contour is 0.879 mm in the X direction and 0.882 mm in the Y direction, and the end-effector movement distance can be saved by an average of 43.89% with the optimized path under different conditions for the number of harvested shoots, and the success rate of end-effector positioning can reach 100%, and the harvesting rate of white asparagus under the laboratory environment can reach 100%. The harvesting rate of white asparagus under laboratory environment reaches 88.13%, which verifies the feasibility of selective harvesting of white asparagus harvesting robot using visual localization.
Internet Reading
[6] Feng, Z., Wang, X., Qiu, Q., Zhang, C., Li, B., Xu, R., Chen, L.. Design and test of a robot for epidemic prevention and disinfection of livestock and poultry houses[J]. Intelligent Agriculture (in Chinese and English), 2020, 2(4): 79-88.
FENG Qingchun, WANG Xiu, QIU Quan, ZHANG Chunfeng, LI Bin, XU Ruifeng, CHEN Liping. Design and test of disinfection Design and test of disinfection robot for livestock and poultry house[J]. Design and test of disinfection robot for livestock and poultry house[J]. Smart Agriculture, 2020, 2(4): 79-88.
Abstract: Aiming at the problems of high labor intensity and poor safety of livestock and poultry breeding, a disinfection robot system is designed to realize the intelligent operation of disinfection spraying in livestock and poultry house. The robot system consists of four parts, including a mobile carrying platform, epidemic prevention and spraying parts, environmental monitoring sensors and controllers, and supports two working modes, namely fully automatic operation and remote control operation. For the working conditions of low light and low stress in the livestock and poultry house, a navigation path detection method combining "magnetic tag and radio frequency identification" is proposed to realize autonomous movement between breeding cages in the livestock and poultry house. A wind-assisted liquid nozzle was designed to simultaneously atomize and diffuse the disinfectant liquid. Through the hydrodynamic simulation of the wind field in the nozzle cavity, the structural parameters of the nozzle gas deflector and liquid atomization components were optimized, and the inclination angles of the conical deflector pads and the atomization grill plate were determined to be 75 and 90, respectively. Finally, the robot navigation and spraying performance were tested in the poultry house. The test results showed that the robot's mobile platform could meet the speed range of 0.1~0.5 m/s for automatic line navigation, and the maximum offset of its actual trajectory relative to the magnetic peg markers was 50.8 mm; the wind-assisted nozzle could be applied to the spraying of the liquid solution with a flow rate of 200~400 mL/min, and the diameter of the fog droplets formed (DV.9) ranged from 51.82~137.23 μm, and the density of the fog droplet deposition was 116~149 droplets/cm2, which was the same as that of the spraying of the liquid solution. 116~149 droplets/cm2, the disinfection robot can realize the intelligent spraying operation of disinfection and immunization liquid in the breeding house.
Intellectual reading
[7] Youchun Ding, Xuping Wang, Jingye Peng, Zhongzhou Xia. Design and test of visual navigation system for wheeled grain combine harvester[J]. Intelligent Agriculture (in Chinese and English), 2020, 2(4): 89-102.
DING Youchun, WANG Xuping, PENG Jingye, XIA Zhongzhou. Visual navigation system for wheel-type grain combine Visual navigation system for wheel-type grain combine harvester[J]. Smart Agriculture, 2020, 2(4): 89-102.
Abstract: In order to improve the harvesting quality and efficiency of the combine harvester, a visual navigation control system for wheel-type grain combine harvester was constructed, and a grain harvesting boundary straight line detection algorithm was designed to recognize the boundary of harvested and non-harvested areas in the rice field by combining OpenCV. area and unharvested area boundary, through preprocessing, secondary edge segmentation and straight line detection to get the combine harvester visual navigation operation forward-looking target path, and according to the forward-looking path relative position information for the dynamic calibration of the field to obtain the combine harvester harvesting full width operating state; put forward a straight line path tracking control method based on the forward-looking point, and realize the maintenance of the full width of the crop at the same time to prevent crop leakage by the pre-corrective control. The relative position deviation value and real-time steering rear wheel angle are used as inputs to the visual navigation controller, and the steering wheel control voltage size is output according to the deviation correction strategy. The results of the paddy field test show that the navigation system realizes the reliable acquisition of the relative position attitude of the wheeled combine harvester in the field and the stable execution of the target straight-line path tracking control, and the detection accuracy of the harvest boundary recognition algorithm is not less than 96.28% and the single-frame detection time is less than 50 ms under the condition that the illumination level in the field is in line with the normal operation of the human eye; the average cutting width rate of the visual navigation with the premise of not producing missed cuts is 94.16%, and the consistency of cutting width increases with the number of operating rows. This study can provide technical support for combine harvester automatic navigation full cut operation.
Internet Reading
[8] Hu Xiaolu, Liang Xuexiu, Zhang Junning, Mei Shijun, Lu Program. Framework construction and development proposal of China's intelligent agricultural machinery and equipment standard system[J]. Intelligent Agriculture (in Chinese and English), 2020, 2(4): 116-123.
HU Xiaolu, LIANG Xuexiu, ZHANG Junning, MEI Anjun, LYU Chengxu. Construction of standard system framework for intelligent agricultural machinery in China[J]. Smart Agriculture, 2020, 2(4): 116-123.
Abstract: Aiming at the lack of systematic standard system guidance in the standardization of intelligent agricultural machinery and equipment in China, this study constructs a standard system framework for intelligent agricultural machinery and equipment in China. First of all, from the standard system, specific standards, internationalization level and other aspects of the analysis of China's intelligent agricultural machinery and equipment standardization status and problems; relying on the intelligent agricultural machinery and equipment standard system framework construction goals and principles, summed up the level, binding force, universality, nature, object, standard categories, reference model, industry classification, industry links, and other dimensions that constitute the framework of the standard system. After that, the three-dimensional framework structure of China's intelligent agricultural machinery and equipment standard system is constructed by utilizing the level, category, and industrial link, and its two-dimensional decomposition is divided into the basic layer, the *** generality layer, and the application field layer. Finally, recommendations for the research and preparation of China's intelligent agricultural machinery and equipment standards are proposed. This study can provide systematic guidance for the preparation, revision, implementation and service of China's intelligent agricultural machinery and equipment standards, and lead the rapid development of China's intelligent agricultural machinery and equipment industry.
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[9] Yingxin Wu, Cambridge Wu, Yuhang Yang, Mutong Li, Ling Gan, Liang Gong, Chengliang Liu. Design and application of hardware-in-the-loop simulation platform for hybrid orchard automatic navigation vehicle controller[J]. Intelligent Agriculture (in Chinese and English), 2020, 2(4): 149-164.
WU Yingxin, WU Jianqiao, YANG Yuhang, LI Mutong, GAN Ling, GONG Liang, LIU Chengliang. Design and application of hardware-in-the-loop simulation platform for AGV controller in hybrid orchard[J]. Smart Agriculture, 2020, 2(4): 149-164.
Abstract: Due to the wide range of area, complex terrain, many trenches, overgrown weeds, high soil moisture and loose soil, the design of the mechanical structure, control system, and energy power system of the automated guided vehicle (AGV) has put forward a higher standard. The design of the system has put forward higher standards and requirements. Hybrid AGVs can meet the needs of long-distance movement in orchards. In order to explore suitable hybrid AGV control system algorithms and energy management strategies, and to reduce the manpower, material resources, and time costs caused by the complexity of the orchard terrain during the design process, which results in the iteration of the controller design verification and the diversification of the demand, this study selects the series-connected oil-electric hybrid system for the construction of the AGV power system model for the characteristics of the orchard with a wide area. In addition, for the orchard AGV needs to adapt to the characteristics of a wide range of terrain, the tracked vehicle model structure is adopted, the hardware in the loop simulation technology is utilized, the Raspberry Pi is used as the control system to piggyback on the physical object of the control algorithm, and the real-time simulation model of the system that contains the energy power system, the motor drive system, the model of the driving part of the tracked vehicle, and the model of the road surface is built using the software Matlab and RecurDyn, and the final realization is achieved. hardware-in-the-loop simulation function of series hybrid AGV controller. The simulation validation based on the serial proportional-integral-derivative (PID) and fuzzy controller control algorithms shows that the fuzzy controller control algorithm is able to reduce the time cost of parameter adjustment, accelerate the response speed by 50% when the steering angle is small, and produce 10% overshooting of the serial PID controller when the steering angle is large, while the fuzzy controller is free of overshooting and has a smoother steering. The results show that the hardware-in-the-loop simulation platform can be effectively applied to the development of orchard AGV controllers, avoiding the control of physical tests, and accelerating the development process of the orchard auto-navigation vehicle while reducing costs.
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