1321 results about "Fruit tree" patented technology

The invention relates to the technical field of intelligent agriculture, and particularly discloses an orchard intelligent water and fertilizer integration-based edge end fruit tree fertilizer demand prediction method, which comprises the following steps of: constructing each fruit tree as a graph node, and fusing canopy spatial characteristics extracted by unmanned aerial vehicle multispectral remote sensing and nutrient time sequence characteristics monitored by a soil sensor; space influence weights among nodes are calculated according to the terrain, the soil texture and the space distance, and a fruit tree individual relation graph is established; then, through a space-time diagram convolutional network, aggregating space neighborhood features and capturing time dynamic changes, and outputting target state features subjected to multi-scale enhancement; when the canopy conflicts with the soil characteristic indication, combined diagnosis is carried out based on a neighborhood consistency index and an adjacent node state, systematic nutrient stress and local non-nutrient factors are distinguished, and final fertilizer demand prediction is generated after the conflict is eliminated; a digital fertilization prescription map is generated through spatial interpolation, soil characteristics and slope correction, and the water and fertilizer integrated equipment is driven to execute precise operation.

The invention discloses a juicy peach yield prediction method based on comprehensive data analysis, and particularly relates to the technical field of agricultural intelligent perception. The method comprises the following steps: collecting multi-source data of an orchard, and constructing a data set containing meteorological, physiological, remote sensing and soil information; fruit tree physiological response parameters are extracted, and a bimodal diagram structure fusing the spatial adjacency relation and the physiological state similarity is established in combination with the dynamic climate anomaly index; inputting the graph structure into a graph neural network model, extracting spatial-temporal characteristics, dynamically adjusting an edge weight and a propagation layer number, and constructing an adaptive model; performing region division and weighted summarization according to a model output result, and finally obtaining a predicted value of the total yield of the orchard; the method improves the prediction accuracy under the conditions of complex climate and unstable data, and is suitable for refined orchard management.

The invention discloses a UWB navigation system and method based on visual feature fusion, the system comprises a UWB positioning module, a visual perception module, a data fusion processing module and a navigation control module, the UWB positioning module adaptively generates UWB anchor point layout, calculates UWB coordinates in real time, and then obtains UWB positioning data according to fruit tree coverage rate and soil humidity calibration; the visual perception module collects orchard images to recognize fruit trees and obstacles, obtains visual coordinates and corrects the visual coordinates to obtain visual positioning data; the data fusion processing module calculates weights of the UWB positioning data and the visual positioning data, fuses the UWB positioning data and the visual positioning data according to the weights to obtain fusion coordinates, and performs error correction to obtain optimal coordinates; and the navigation control module calculates a target path point according to the optimal coordinate, the obstacle recognition result and the weeding operation path, and controls the weeding robot to run to the target path point. According to the invention, high-precision navigation of the weeding robot in a complex orchard environment is realized.

The invention relates to the technical field of image processing, and discloses a pitaya fruit pose estimation method based on point cloud three-dimensional reconstruction. The pitaya fruit pose estimation method comprises the steps that RGB color images and depth images of pitaya fruits are collected, expanded and marked; the DeepLabV3 + network model is improved and trained, and then an RGB color image is segmented; segmenting the depth image by using the semantic segmentation mask image, then matching the depth image with the RGB color image to obtain a pitaya tree point cloud, and preprocessing the pitaya tree point cloud; registering the pitaya fruit tree point cloud by using an improved point cloud registration algorithm to obtain a fruit tree three-dimensional point cloud model, and segmenting fruit local point clouds from the fruit tree three-dimensional point cloud model; establishing a pitaya fruit point cloud coordinate system by using a PCA principal component analysis method; and performing spherical fitting and ellipsoid fitting on the pitaya fruit point cloud coordinate system to obtain an ellipsoid model with unique pose parameters. According to the invention, a fruit tree three-dimensional point cloud model and accurate fruit three-dimensional space pose information can be provided for a pitaya fruit picking system.

The invention relates to the technical field of agricultural intellectualization, and discloses a fruit tree growth monitoring system based on multi-sensor fusion, which comprises a multi-mode sensor array, an integrated soil humidity sensor, a three-dimensional ultrasonic ranging sensor, a hyperspectral imaging sensor and a microenvironment meteorological station, and realizes multi-parameter synchronous acquisition; a nonlinear data calibration model adopts a layered architecture, and cross interference between sensors is eliminated; a dynamic weight distribution algorithm is built in the edge computing node, multi-source heterogeneous data are fused in real time, a fruit tree growth situation map is generated, and a low-power-consumption processor is adopted to support lightweight AI model deployment; the self-adaptive power supply module adopts a photovoltaic-temperature difference composite power generation structure to realize cable-free deployment; the wireless ad hoc network communication unit constructs an inter-tree relay network based on a LoRa protocol, supports low-power-consumption remote data return, and integrates a relay node health degree evaluation mechanism. The real-time performance of fruit tree growth monitoring, the data reliability and the situation analysis accuracy are improved.

The invention relates to a fruit tree growth phenotype dynamic acquisition method and system based on multi-modal perception fusion. Belongs to the field of fruit tree growth detection, and establishes a fruit tree whole growth period growth dynamic knowledge graph by fusing structure and growth phenotype data of fruit tree individuals and groups collected by laser radar, machine vision, remote sensing and other multi-source sensors to realize space-time modeling and automatic identification of tree body structures, growth states and key growth periods. Knowledge reasoning and decision-making algorithms are further combined, and intelligent management services such as fruit tree nutrition diagnosis, pruning suggestion and yield prediction are provided. The fruit tree phenotype data acquisition, analysis and utilization efficiency is improved, refined, intelligent and digital management of fruit trees is realized, and the method can be widely applied to the field of modern orchard digital twinning and intelligent agriculture.

The invention relates to the technical field of fruit tree disease detection, in particular to a fruit tree disease detection method based on image recognition, and the method comprises the steps: collecting images of leaves, fruits and branches of a fruit tree, and corresponding environment and physiological data; image features are extracted through a convolutional neural network, and time sequence modeling is carried out on environment and physiological data; inputting the multi-source features into a fusion network for weighted fusion to generate a fusion feature vector; inputting a disease recognition model, and outputting a multi-disease recognition result; when the confidence coefficient is low or feature conflicts exist, auxiliary judgment and correction are carried out in combination with environment and physiological data; outputting the corrected disease type, the disease spot position and the confidence coefficient, and generating a distribution diagram and a detection report; and marking a low-confidence or unidentified sample as an incremental sample, checking and storing the incremental sample, and performing online fine adjustment or transfer learning on the model based on the incremental sample to realize adaptive optimization of the model.

A picking robot, a fruit positioning method and apparatus therefor, an electronic device, and a medium are provided. The robot includes a robot body including a processor and a plurality of robotic arms. A plurality of first image collection modules and one second image collection module are mounted on the robot body. Each robotic arm has one corresponding first image collection module mounted nearby. Each first image collection module does not interfere with the corresponding robotic arm. The second image collection module is mounted at a position of a base of the robot body. The processor is configured to determine, based on fruit tree images of respective sub-areas in an operation area that are collected by respective first image collection modules and the base coordinate system, global fruit positioning distribution information of the operation area, and control the robotic arms to perform collaborative operation.

The invention discloses beneficial fusarium oxysporum and application thereof in relieving apple continuous cropping obstacles, and belongs to the technical field of agricultural microorganisms. The biological preservation number of the fusarium oxysporum FoB1 disclosed by the invention is CGMCC (China General Microbiological Culture Collection Center) NO.42195. The fusarium oxysporum FoB1 disclosed by the invention is beneficial fusarium oxysporum, and has the advantages of excellent biocontrol function, strong environmental adaptability and high affinity with a host. By optimizing the preparation process of the microbial inoculant, the activity and stability of the inoculant are remarkably improved, and a high-quality bacterium source is provided for large-scale production. On the basis, a simple and convenient bacterium-bearing nursery stock application technology is developed, a novel efficient biological prevention and control way is provided for relieving apple continuous cropping obstacles, and important technical support is provided for promoting green and sustainable development of the fruit tree industry.

The invention relates to an intelligent soil regulation and control method based on soil data and image processing. The method comprises the following steps: acquiring and standardizing soil data; orchard global multispectral image acquisition: acquiring and preprocessing an orchard image, and acquiring an orchard global multispectral image; vegetation region identification and parameter calculation: calculating NDVI based on red light and near infrared bands, distinguishing green manure and fruit tree regions through a threshold segmentation method, and calculating green manure coverage, a green manure normalized vegetation index and a fruit tree canopy area; carrying out soil-vegetation data fusion and parameter extraction; distributing weights based on the three types of core parameters, calculating the application amount and type ratio of nitrogen, phosphorus and potassium fertilizers, and generating an initial regulation and control scheme; and repeating the steps every specified time period to realize dynamic iterative optimization of the scheme. Through deep fusion of soil data and an image processing technology, intelligent soil regulation and control are realized, regulation and control accuracy and timeliness are remarkably improved, and fertilizer waste and environmental risks are reduced.

The invention relates to an intelligent fruit tree planting monitoring method and system, and belongs to the technical field of intelligent agriculture. According to the scheme, a multi-source sensor network is deployed to collect soil, crop and environment data, a salinity-moisture collaborative stress decision-making model is constructed, and parameters such as soil salinity, canopy temperature and weather forecast are deeply fused; dynamically generating a non-fixed precise irrigation instruction; meanwhile, a low-visibility robust vision algorithm is integrated, and it is ensured that fruits and diseases and pests can still be reliably recognized in severe weather; by establishing a collaborative scheduling mechanism, efficient linkage of water and fertilizer management, plant protection operation and farming operation is realized. According to the method, the technical span from single threshold judgment to multi-factor intelligent decision is realized, the utilization efficiency of water resources and fertilizers is effectively improved, the production cost is remarkably reduced, and the mode of fruit tree planting is promoted to be converted from traditional experience management to data-driven intelligent management.

The application relates to a plant protection unmanned aerial vehicle spraying control method, device, equipment and medium, the method comprising: acquiring pose transformation data of each trunk of a pose sensor in a fruit tree canopy in a preset time range, each flight parameter of a plant protection unmanned aerial vehicle and fruit tree canopy image data of a vision sensor in the plant protection unmanned aerial vehicle; determining a mist drop deposition amount in the fruit tree canopy under each flight parameter, constructing a plant protection unmanned aerial vehicle spraying control model according to the mist drop deposition amount and the canopy disturbance prediction model; inputting each flight parameter of the plant protection unmanned aerial vehicle into a pre-trained plant protection unmanned aerial vehicle spraying control model, determining a fruit tree canopy disturbance state corresponding to the flight parameter and a mist drop deposition amount under the fruit tree canopy disturbance state, so as to complete the control of the plant protection unmanned aerial vehicle spraying. The application can greatly avoid the great influence of the wind field generated by the unmanned aerial vehicle rotor on the deposition effect of the pesticide mist drop.

The invention relates to the technical field of fruit tree management, in particular to a digital fruit tree planting management system which comprises a branch main direction recognition module, a point position angular difference screening module, a planting posture correction module, a pesticide spraying path linkage module and a period regulation and control feedback module. According to the method, a main expansion direction angle index is established by analyzing a directional structure of a nursery stock branch, an angle matching mechanism is established in combination with screening of a direction difference value of a planting point position, the spatial adaptation degree of the nursery stock and the planting layout coordination can be improved, and an attitude reconstruction and adjustment mechanism is introduced by identifying an angle interference risk. The attitude adaptability and the angle correction capability of the planting operation are enhanced, the atomization spraying precision is improved by combining pesticide spraying direction deviation identification and path correction processing, feedback calculation is performed on a pesticide spraying path adjustment result, and the pesticide spraying operation frequency is dynamically controlled; the multiple control targets of enhancing the plant space direction consistency, reducing the planting posture interference, improving the pesticide spraying path coverage precision, optimizing and controlling the operation period and the like are achieved.

A fruit bagging device relates to the technical field of agricultural production machinery and comprises a box body, the interior of the box body is divided into a front part and a rear part through a baffle, the rear part is provided with a compression spring and a gland, and a bag is placed between the gland and the baffle. The front part is provided with a paper separating and opening mechanism and a sealing mechanism. The paper separating and opening mechanism comprises a roller assembly and a motor, the motor drives a sticky roller to rotate, and a notch allowing the roller to make contact with a bag and a notch facilitating bag output are formed in the baffle. The sealing mechanism comprises a sealing grabbing clamp, a motor, a bottom plate and a movable pressing rod, the grabbing clamp is connected with the motor through a connecting rod mechanism, and the plane part of the grabbing clamp is hinged to the connecting rod mechanism and connected with a spring. The device is further provided with a telescopic mechanism, a photoelectric switch and a proximity switch which are used for adapting to fruit trees of different heights, detecting the bagging position and controlling the motor to act. The fruit bagging machine is reasonable in structure, easy and convenient to operate and capable of effectively improving fruit bagging efficiency and reducing manual labor intensity, and has good application prospects.

The invention belongs to the technical field of fruit tree cultivation and plant growth regulation, and particularly relates to a plant growth regulator containing 5-ALA and application of the plant growth regulator in prunus humilis planting. According to the method disclosed by the invention, the nutritional quality of fruits is remarkably improved by spraying a 100 mg / L 5-ALA solution on the whole cerasus humilis plant. Compared with clear water, the sugar content of the cerasus humilis fruits treated by the 5-ALA in the full ripening stage is increased by 44.01%, the acidity is reduced by 23.75%, the soluble solids are increased by 60.22%, and the flavor of the fruits is remarkably improved; meanwhile, the total calcium content of the fruits is increased by 30.22%, the water-soluble calcium content is increased by 91.12%, the pectin calcium content is reduced by 30.04%, and the active calcium content is increased by 50.74%; the content of soluble protein is increased by 30.98%, so that the acidity is reduced, and sugar, calcium and protein are synergistically improved.

The invention provides an orchard building method and a pruning method of a double-layer dwarf open-center-shaped high-photosynthetic-efficiency cultivation pear orchard, and belongs to the technical field of fruit tree cultivation. According to the orchard building method for the high-photosynthetic-efficiency cultivation pear orchard, multiple factors such as the sun drift angle, the day photosynthetic efficiency change around pear trees, the geographic latitude of the orchard and the growth period of pear varieties are comprehensively considered, and the planting row direction and the high-photosynthetic-efficiency tree form are determined and pruned according to the latitude of the place where the orchard is located and the day photosynthetic efficiency change around the pear trees. By means of the orchard building method, by selecting a high-light-effect tree form and a scientific pruning method, controlling the height and size of a tree crown, thinning and removing over-dense branches on the upper portion and adjusting a fruiting branch group, the ventilation and light transmission conditions in the tree crown can be effectively improved, shielding of the tree crown to lower leaves is reduced, and illumination of the lower leaves is further improved. The method is simple and easy to implement, convenient to popularize and apply, and capable of remarkably improving the pear tree photosynthesis efficiency and improving the fruit yield and quality of pears.

The invention provides an orchard robot collision avoidance track method based on a multi-modal algorithm, and aims to solve the problem of high vehicle branch collision risk caused by narrow fruit tree walkway channel and lateral invasion of tree crowns and branches, and the orchard robot collision avoidance track method based on the multi-modal algorithm is provided. Fusing a front sensing trail rectification strategy to generate a branch collision risk value, a danger direction mark and an avoidance sequence, and setting a risk threshold value associated with a safety transverse margin; the method comprises the following steps of: expanding according to a sequence under traffic constraint, rejecting over-threshold actions, generating a candidate track fitting a side line, selecting a main track according to a fitting degree threshold value, performing transverse correction in combination with a crown edge distance threshold value, finally forming a track, and outputting a steering and speed instruction. According to the method, the track which is continuous in curvature, meets the safety transverse allowance and does not enter the dangerous direction can be generated in the short-distance front range, the branch collision risk is reduced, and the traffic safety and trafficability of the orchard robot in the walkway are improved.

The invention relates to the field of fruit tree disease and insect pest detection, in particular to a fruit tree disease and insect pest detection method and system based on machine vision, and the method comprises the steps: obtaining an image metabolome feature matrix and a preliminary difference pixel based on a preprocessed multispectral image of an original machine vision image obtained by a camera, carrying out the topological skeleton extraction, and carrying out the dimension fusion; outputting a core focus feature set; each discrete feature is used as a network node, a mutual information value between any two discrete features is calculated, and a focus area is obtained; and based on a lesion region containing lesion boundary coordinates, area and morphological parameters, extracting the ROI of the lesion region from the multispectral image, and carrying out disease and pest identification matching to obtain a detection result. According to the method, the essential attributes of the lesion are comprehensively captured by fusing the multi-dimensional features of the spectrum, the texture, the space coordinates and the morphological topology, a multi-dimensional fusion feature system is formed, and the problems that similar pest and disease damage forms are difficult to distinguish, and early lesion features are weak and difficult to recognize are effectively solved.

The invention discloses an SNP (Single Nucleotide Polymorphism) molecular marker for germplasm identification and breeding of armeniaca mume, and belongs to the technical field of fruit tree molecular marker-assisted breeding. On the basis of re-sequencing and selective clearance analysis of wild plum and armeniaca mume populations, a key gene remarkably related to the armeniaca mume cyanin deletion character is identified, and an SNP variation with a codon terminated in advance exists in a gene coding region; a specific primer is further designed according to the functional SNP variation, a target fragment corresponding to a plum genome is amplified through PCR, and the base type of an SNP site is detected through first-generation sequencing, so that whether the detected plant is the armeniaca mume germplasm or not can be quickly and accurately judged. The SNP molecular marker can be used for early screening of armeniaca mume germplasm, has important application value, and provides an efficient and reliable technical means for molecular marker-assisted breeding.

The invention discloses an orchard frost protection system based on meteorological monitoring, and the system comprises a sensor module, a main control module, a power supply module, a communication module, a monitoring module, a support, and a case. The power supply module provides power for the sensor module, the main control module, the communication module and the monitoring module, the main control module obtains data collected by the sensor module, abnormal values are removed through a DBSCAN algorithm, data continuity is guaranteed through a Lagrange interpolation algorithm, temperature change prediction results of different canopies of an orchard in a future preset time period are generated through a Bi-LSTM + Transformer algorithm, and the temperature change prediction results of the different canopies of the orchard in the future preset time period are obtained. And when the prediction result meets the frost judgment condition, early warning information is sent out through the communication module. Different frost judgment conditions are set for different fruit trees and growth stages, real-time monitoring and timely early warning are combined, fruit farmers are helped to take measures in advance, and yield reduction and quality decline caused by frost are remarkably reduced.

The application discloses a kind of crown layer inside view touch fusion safety movement positioning method and device of rigid-flexible hybrid manipulator, and multiple kinds of heterogeneous objects in fruit tree crown layer are divided into avoidance target and compliance target;For avoidance target, the dynamic characteristics of avoidance target are used as obstacles, and dynamic paths are planned, so that rigid-flexible hybrid manipulator strictly avoids such targets;For compliance target, rigid-flexible hybrid manipulator penetrates into fruit tree crown layer and contacts compliance target, and the integrated joint tension of each tension sensor on flexible arm is subtracted from the corresponding integrated joint theoretical tension, to generate error signal, and the error signal of driving rope is feedback adjusted, and then the rope length of driving rope is dynamically adjusted by controlling tension disc type motor, to drive flexible arm to generate dynamic bending deformation angle, to realize compliant and smooth movement when rigid-flexible hybrid manipulator contacts compliance target.The application is widely applicable to autonomous continuous planning of rigid-flexible hybrid manipulator in various fruit tree complex crown layer scenarios.

The invention relates to the technical field of microorganisms, in particular to burkholderia metallica BW17 with weight-losing, disease-resisting and growth-promoting functions as well as a fungicide and application thereof, and the strain has good capabilities of producing IAA, fixing nitrogen, dissolving phosphorus and broad-spectrum antagonizing pathogenic bacteria. Pot experiments prove that the strain can significantly promote growth of pyrus betulaefolia and tomato seedlings, improve root morphology, increase biomass, and significantly improve appearance and internal quality of tomato fruits. In addition, the BW17 has an obvious inhibition effect on various phytopathogens. The strain can be widely applied to planting of crops such as fruit trees and vegetables as a bio-organic fertilizer or a microbial agent, partially replaces chemical fertilizers, reduces environmental pollution, improves the quality and yield of agricultural products, and has good popularization and application values.

The utility model discloses a shading loquat heat preservation greenhouse structure, and aims to provide a shading loquat heat preservation greenhouse structure capable of improving heat preservation and temperature uniformity. The device comprises an inner light-transmitting film bracket, wherein the inner light-transmitting film bracket is connected with a side light-transmitting film; the outer sunshade net bracket is detachably connected with a side outer sunshade net; the top light-transmitting film bracket is connected with a light-transmitting film cover; the top sunshade net support is connected with the upper top of the top light-transmitting film support, and the top sunshade net support is detachably connected with a sunshade net cover; the inner heat preservation assembly is provided with a heat preservation curtain piece and an inner conveying pipe fitting, and the inner conveying pipe fitting is connected with the top light-transmitting film support. The heat preservation greenhouse has the advantages that the heat preservation effect of the heat preservation greenhouse is enhanced through the shading structure; fruit tree growth speed and early maturation are promoted; the soluble fixture and quality of the fruits are improved; the temperature stability and uniformity in the greenhouse are improved, and the labor input in the production link is saved.

The invention discloses an intelligent apple picking robot system with rigid and flexible heterogeneous mechanical arms cooperatively working, and solves the problems of missing picking of fruits on the inner side of a fruit tree, low single-arm picking efficiency and mechanical arm positioning drift caused by advancing vibration in the prior art through the cooperative design of a moving platform, a picking mechanism, a control system and a multi-sensor fusion system. The mobile platform adopts a crawler-type chassis, the front end is provided with an ultrasonic sensor to realize obstacle avoidance, and a middle collection box is provided with an infrared sensor to monitor a full-load state; two groups of rigid mechanical arms and two groups of flexible mechanical arms of the picking mechanism adopt a dynamic priority scheduling mechanism to realize labor division picking based on binocular camera and depth camera data, the rigid arms are responsible for picking low-shielding fruits on the periphery of a fruit tree, and the flexible arms go deep into a branch and leaf area to pick high-shielding fruits, so that full coverage of single fruit tree picking is realized; the multi-sensor tight coupling positioning system is mainly based on a laser radar, and integrates an IMU and a differential GNSS-RTK to realize centimeter-level positioning in a GPS denial environment. The actually measured target picking success rate of the rigid-flexible mechanical arm treatment score of the single fruit tree reaches 87.2%.

The utility model provides an automatic vibration fruit shaking machine, and relates to the technical field of fruit harvesting. The automatic vibration fruit shaking machine comprises a rack, a walking mechanism, a clamping mechanism, a vibration mechanism, a collecting mechanism, an environment information collecting mechanism and a control mechanism. The control mechanism comprises a first control assembly and a second control assembly. The second control assembly is used for identifying fruit tree trunks, obstacle identification and path planning. The clamping mechanism comprises a first lead screw sliding table module, a bus steering engine and a mechanical clamping jaw. The first lead screw sliding table module is used for longitudinally moving the mechanical clamping jaw. The bus steering engine is used for driving the mechanical clamping jaw to open and close. The vibration mechanism comprises a frequency converter electrically connected to the first control assembly and a vibration motor. The collecting mechanism comprises a second lead screw sliding table module connected to the rack, a telescopic support connected to the second lead screw sliding table module and a collecting net connected to the telescopic support. The second lead screw sliding table module is constructed to be capable of driving the telescopic support to be opened or closed so as to drive the collecting net to be opened or closed.

The invention discloses a yield prediction method and device in a fruit tree growth process and a storage medium. The method comprises the following steps: acquiring a binocular image and a multi-angle image of a fruit tree to be monitored and environment data of a growth environment of the fruit tree to be monitored; performing feature extraction on the binocular image, the multi-angle image and the environmental data to obtain multi-modal features of the fruit tree to be monitored; and inputting the multi-modal features into a fruit tree yield prediction model, and outputting a yield prediction result of the to-be-monitored fruit tree by using the fruit tree yield prediction model. Through the method and the device, the problem of relatively low accuracy of fruit tree yield prediction in related technologies is solved.

The invention relates to the technical field of intelligent irrigation, and discloses an intelligent irrigation system for a fruit tree planting greenhouse. The system comprises a multi-dimensional data acquisition module, a data fusion processing module, an irrigation decision module and an irrigation control execution module which are connected in sequence. The system obtains a root soil image, a leaf surface temperature distribution map and stem micro-deformation data, and performs multi-dimensional fusion calculation to generate a spatial water potential distribution map capable of representing the overall moisture condition of crops. And calculating specific regional water demand and preferential irrigation sites based on the map, and further driving an execution terminal to realize precise irrigation. According to the method, the physiological water demand signal of the crop can be responded, the spatial difference of water stress can be identified, the limitation that the traditional technology depends on single soil information is overcome, the crossing from environment monitoring to crop body sensing is realized, and the irrigation accuracy and the water resource utilization efficiency are improved.

The application discloses a UWB navigation system and method based on visual feature fusion, and the system comprises four modules of UWB positioning, visual perception, data fusion processing and navigation control. The UWB positioning module adaptively generates a UWB anchor point layout, and after calculating UWB coordinates in real time, UWB positioning data are obtained by calibration according to the coverage rate of fruit trees and soil humidity. The visual perception module collects orchard images, identifies fruit trees and obstacles, obtains visual coordinates and corrects visual positioning data. The data fusion processing module calculates the weight of UWB positioning data and visual positioning data, fuses UWB positioning data and visual positioning data according to the weight to obtain fusion coordinates, and corrects errors to obtain optimal coordinates. The navigation control module calculates target path points according to the optimal coordinates, obstacle recognition results and weeding operation paths, and controls the weeding robot to travel to the target path points. The application realizes high-precision navigation of the weeding robot in the complex environment of the orchard.

The invention relates to the technical field of fruit picking, and provides a picking machine with an image recognition function, the picking machine comprises a picking vehicle, tree surrounding mechanisms, a picking mechanism and an image recognition mechanism, the picking vehicle is provided with a supporting plate, the supporting plate is provided with a controller, the two tree surrounding mechanisms are arranged on the supporting plate, the picking mechanism is arranged on the tree surrounding mechanisms, and the image recognition mechanism is arranged on the picking mechanism. The two image recognition mechanisms are arranged on the picking mechanism, the tree surrounding mechanism comprises an adjusting shell, a first motor, a first threaded rod, an adjusting assembly and a tree surrounding assembly, the adjusting shell is arranged on one side of the supporting plate, the first motor is arranged on the adjusting shell, and the first threaded rod is arranged in the adjusting shell; the output end of the first motor penetrates through the adjusting shell to be connected with the first threaded rod, the two tree surrounding assemblies are arranged on the adjusting assembly, and the problems that in the related technology, the picking vehicle needs to be moved continuously for picking of one fruit tree, time and labor are wasted, and the picking efficiency is low are solved.

The utility model relates to the field of fruit tree branch pulling, in particular to a branch pulling auxiliary structure capable of avoiding damage to branches. The branch pulling auxiliary mechanism comprises a rod-shaped part, a plurality of groups of guide cylinders (8) are arranged along an arc shape and are welded together through arc-shaped side arc-shaped frameworks (9), and two groups of side arc-shaped frameworks (9) are arranged; a working hook (13) is welded on the side arc-shaped framework (9); the bottom of the rod-shaped part can be inserted into soil; the working hooks (13) can hook branches, and the multiple sets of guide cylinders (8) can bend and guide the branches so that the branches can be bent. An arc-shaped mode is adopted for guiding, branches cannot be damaged, and the branches cannot be split or damaged; according to the invention, manpower can be saved; the angle can be accurately controlled.