Pepper variety quality recognition, agricultural pest control, and picking path planning system and method

Abstract

The application discloses a pepper category quality identification, agricultural pest control and picking path planning system and method, belongs to the field of agricultural machinery and artificial intelligence technology, first acquires pepper information, obstacle information, pest information and weed information; and obtains spatial position information of peppers, pests and weeds that need to be picked according to the information; detects and analyzes the obstacle information; plans a route for picking peppers and processing weeds according to the information, removes weeds in turn and bypasses obstacles to proceed to the target pepper for picking; according to the obtained picking execution program, pest catching program and pesticide spraying program, the pepper picking, weed processing, pest catching and pesticide spraying work are completed. In the process of picking peppers, the weeds and pests can be treated to the maximum extent without pollution. Different types of peppers can be picked in different environments, pesticides can be sprayed more scientifically and normatively, and pests can be controlled more greenly and efficiently, so that the pepper planting and maintenance work is well completed, and a large amount of manpower and material resources are saved.

Description

Technical Field

[0001] This invention belongs to the field of agricultural machinery and artificial intelligence technology, specifically involving a system and method for identifying chili pepper varieties and quality, agricultural pest control, and harvesting path planning. Background Technology

[0002] With increasing public concern about food safety and a growing demand for efficient agriculture, intelligent chili harvesting machines have emerged. This is because traditional methods of harvesting and sorting chilies are inefficient, requiring manual labor such as weeding and pesticide spraying, which can negatively impact both the quality and yield of the chilies.

[0003] Currently, there are not many chili harvesting machines available on the market, and most of them have numerous shortcomings. For example, due to significant differences in chili growing conditions and varieties across different regions, a single harvesting machine may not be suitable for all growing environments and chili varieties, thus limiting its applicability. Moreover, chili harvesting machines employ advanced sensing, navigation, and mechanical technologies, resulting in relatively high manufacturing costs. Since they only perform the single function of harvesting, they are not practical or affordable for users, making them unacceptable to many.

[0004] To address the technical problems of low harvesting efficiency and accuracy, as well as poor applicability of existing chili harvesting machines, there is a need to find a new system and method for chili variety quality identification, agricultural pest control, and harvesting path planning. This system should be able to combine chili variety quality identification and agricultural pest control functions to improve chili harvesting efficiency and accuracy, reduce labor intensity, and be applicable to chili harvesting in different environments and for different varieties. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, the present invention aims to provide a system and method for identifying chili varieties and quality, agricultural pest control, and harvesting path planning, so as to solve the technical problems of low harvesting efficiency and accuracy, and poor applicability of existing chili harvesting machines.

[0006] To achieve the above objectives, the present invention employs the following technical solution:

[0007] The present invention discloses a method for identifying chili pepper varieties and qualities, agricultural pest control, and harvesting route planning, comprising:

[0008] Obtain information on chili pepper location, shape, size, obstacles, pests, and weeds;

[0009] Based on the location information, shape information, size information, pest information, and weed information of the chili peppers, we can obtain the spatial location information of the mature chili peppers that need to be harvested, the pests, and the nearby weeds.

[0010] The system detects obstacles encountered during chili pepper harvesting and performs image analysis to obtain obstacle information.

[0011] Based on the spatial location information of the chili peppers that need to be harvested, pests, and nearby weeds, as well as the analyzed obstacle information, the route for harvesting chili peppers and clearing weeds is planned. Weeds are pulled out in sequence and obstacles are bypassed to reach the target chili peppers for harvesting.

[0012] By processing the spatial location information of chili peppers and analyzing the obstacle information, a harvesting execution program, a pest capture program, and a pesticide spraying program are obtained.

[0013] The harvesting, pest control, and pesticide spraying procedures were followed to complete the chili pepper harvesting, weed control, pest capture, and pesticide spraying.

[0014] Preferably, the information obtained includes the location, shape, and size of the chili peppers, as well as information on obstacles, pests, and weeds. Specifically:

[0015] The NVIDIA Jetson Nano development board was used to identify chili pepper varieties, quality, pests on chili peppers, and weeds near chili pepper trees, obtaining corresponding image information. The identified image information was then processed using computer vision algorithms for image preprocessing, feature extraction, feature matching, classification and recognition, threshold determination, and identification.

[0016] More preferably, the NVIDIA Jetson Nano development board includes a high-definition image acquisition system, an information feedback system, a chili pepper target recognition system, a chili pepper variety quality analysis system, a pest and weed recognition system, and a deep learning model;

[0017] The high-definition image acquisition system is used to acquire high-definition images of chili peppers and surrounding objects. The high-definition image information of chili peppers and surrounding objects is transmitted to the chili pepper target recognition system, chili pepper variety quality analysis system, and pest and weed recognition system through the information feedback system. The chili pepper target recognition system, chili pepper variety quality analysis system, and pest and weed recognition system use deep learning models to identify the appearance of chili peppers, pests, and weeds.

[0018] Preferably, the spatial location information of the mature chili peppers, pests, and nearby weeds that need to be harvested is obtained based on the chili pepper location information, chili pepper shape information, chili pepper size information, pest information, and weed information. Specifically, this includes obtaining the spatial location information of the mature chili peppers, pests, and nearby weeds that need to be harvested by combining an image recognition device, an image analysis system, a photosensitive sensor, a light emitter, an ultrasonic positioning system, a dynamic positioning system, a real-time data transmission unit, and an automatic correction function unit.

[0019] The image analysis system converts the information transmitted by the image recognition device into a two-dimensional planar image through sensors for processing and analysis.

[0020] A photosensitive sensor is used to measure the light conditions in the chili-picking environment, generate a light signal, and transmit it to a light emitter.

[0021] Ultrasonic positioning systems are used to determine the spatial location of chili peppers;

[0022] The dynamic positioning system is used to obtain the precise location information of the chili harvester in the field;

[0023] The real-time data transmission unit transmits the collected location information to the control unit;

[0024] The automatic correction function unit detects errors or uncertainties and adjusts or repositions the device accordingly.

[0025] Preferably, obstacles encountered during the chili pepper harvesting process are detected and image analysis is performed to obtain the analyzed obstacle information, specifically:

[0026] The analyzed obstacle information is obtained by combining lidar, optical receiver, obstacle information extraction and output system and information feedback system.

[0027] The laser transmitter converts electrical pulses into light pulses and sends detection signals along the harvesting route. After receiving the signals reflected back from obstacles, the optical receiver converts the reflected light pulses back into electrical pulses and sends them to the display. The information processing system then processes the electrical pulses related to obstacles on the display into data information such as the distance, orientation, attitude, and shape of the obstacles, and displays it on the display. The obstacle information extraction and output system extracts the information displayed by the laser radar and outputs it to the information feedback system. The information feedback system then feeds back the relevant information such as the distance, orientation, attitude, and shape of the obstacles to the data processing unit.

[0028] Preferably, after the chili peppers are harvested, if the density of weeds per unit area in the harvesting path is lower than the threshold set by the system, weeding is carried out; if the density of weeds is higher than the threshold set by the system, weeding is not carried out, and pesticides are sprayed in the area.

[0029] Preferably, if the pest density on the chili pepper tree is less than the threshold set by the system, the pests on the chili pepper tree are sucked into the capture bag through a vacuum tube; if the pest density on the chili pepper tree is greater than the threshold set by the system, pesticides are sprayed on the chili pepper tree.

[0030] Preferably, during pesticide spraying, based on the information transmitted by the data processing unit, corresponding pesticides are prepared for different types of pests or weeds, and the dosage of pesticide spraying is adjusted according to the severity of the pests or weeds.

[0031] Preferably, when catching pests, the suction force is adjusted according to the pest situation to catch different types of pests.

[0032] This invention also discloses a system for identifying chili pepper varieties and quality, agricultural pest control, and harvesting route planning, including:

[0033] The image acquisition module is used to acquire information such as the location, shape, and size of the chili peppers, as well as information about obstacles, pests, and weeds.

[0034] The chili pepper positioning module is used to receive chili pepper location information, chili pepper shape information, chili pepper size information, obstacle information, pest information, and weed information from the image acquisition module, and obtain the spatial location of mature chili peppers that need to be harvested, pests, and nearby weeds.

[0035] The obstacle detection module is used to receive obstacle information from the image acquisition module, perform image analysis, detect obstacles encountered during the chili picking process, and obtain the analyzed obstacle information.

[0036] The harvesting route planning module receives the spatial location information of the chili peppers from the chili pepper positioning module and the analyzed obstacle information obtained from the obstacle detection module, and plans the chili pepper harvesting route.

[0037] The data processing module is used to receive chili pepper location information, chili pepper shape information, chili pepper size information, obstacle information, pest information and weed information obtained by the image acquisition module, chili pepper spatial location information from the chili pepper positioning module, obstacle information after analysis from the obstacle detection module, and chili pepper harvesting route from the harvesting route planning module, and to process them to obtain the harvesting execution program, pest capture program and pesticide spraying program.

[0038] The control system is used to receive and execute the harvesting program, pest capture program, and pesticide spraying program transmitted by the data processing module.

[0039] The chili harvesting module harvests chilies according to the harvesting execution program of the control system;

[0040] The pest-catching module catches pests according to the pest-catching program of the control system.

[0041] The pesticide spraying module sprays pesticides according to the pesticide spraying program of the control system.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] This invention discloses methods for identifying chili pepper varieties and quality, controlling agricultural pests, and planning harvesting paths. It employs advanced sensing technology to pinpoint the location of chili peppers and weeds. Equipped with a navigation and positioning system, it ensures the machine moves accurately to the target chili pepper plants. Utilizing visual recognition technology, it accurately identifies chili pepper varieties, pests, and weeds near the chili pepper plants. A precise positioning system ensures that damage to plants or fruits is avoided during harvesting and weeding. During chili pepper harvesting, weeds and pests can be treated to the greatest extent possible in a pollution-free manner. The machine can harvest different types of chili peppers in different environments, enabling more scientific and standardized pesticide spraying and more environmentally friendly and efficient pest control. It effectively removes pests and weeds from chili pepper fields, significantly improving chili pepper cultivation and maintenance while saving considerable manpower and resources. This invention aims to improve the efficiency and accuracy of chili pepper harvesting, is applicable to different environments and varieties, reduces labor intensity, and possesses other functions such as weed removal, pesticide spraying for pest control, scientific maintenance of chili pepper fields, and ensuring the quality of the chili peppers. Automated operations reduce the physical labor burden on farmers and improve production efficiency. Machines integrate the harvesting and sorting of chilies with field maintenance. The use of intelligent technology minimizes human intervention, making chili harvesting more efficient and economical, and pesticide spraying and other maintenance processes more labor-saving and safer.

[0044] Furthermore, the NVIDIA Jetson Nano development board is used to identify the types of chili peppers (bird's eye chili, ghost pepper, horn pepper, bell pepper, sweet pepper, etc.), the quality of the chili peppers, pests on the chili peppers (such as aphids, tobacco budworms, silkworms, mole crickets, snails, grasshoppers, etc.), and weeds near the chili pepper plants (foxtail grass, goosegrass, purslane, etc.). The identified image information is processed using computer vision algorithms for image preprocessing, feature extraction, feature matching, classification and recognition, threshold determination, and output of the threshold determination results. The relevant image information is then transmitted to the data processing unit, the chili pepper positioning device, and the obstacle (branches and leaves next to the chili peppers, tall weeds, etc.) detection device. The chili pepper positioning device, using information obtained from the NVIDIA Jetson Nano development board, determines the spatial location of mature, harvestable chili peppers and nearby weeds before the chili pepper harvesting device harvests the peppers, and then transmits the location information to the harvesting route planning device. The obstacle (branches and leaves next to the chili peppers, tall weeds, etc.) detection device uses the NVIDIA Jetson Nano development board to detect obstacles. The Nano development board performs image analysis on the information it receives, detects obstacles that the chili-picking device may encounter during the chili-picking process, and then transmits the information to the picking route planning device. It also uses information from the chili-positioning device and the obstacle detection device (branches and leaves next to the chili, tall weeds, etc.) to take into account obstacles on the picking path and performs route planning through the route planning system.

[0045] Furthermore, it features adjustable harvesting force to accommodate different varieties and ripeness levels of chili peppers. Through an intelligent control system, the force is adjusted rationally based on the characteristics of the chili peppers, preserving the integrity of the fruit to the greatest extent possible. The force is further adjusted when handling weeds to ensure their removal. The chili pepper harvesting equipment is designed with a highly efficient, multi-degree-of-freedom robotic arm, enabling rapid and precise harvesting of chili peppers and removal of weeds. The robotic claws are designed with flexible materials to avoid damage to the plants.

[0046] Furthermore, based on the information transmitted by the data processing unit, the pesticide spraying device will apply corresponding pesticides to different types of pests or weeds, and will also adjust the dosage of pesticide spraying according to the severity of the infestation, so as to achieve the goal of saving resources and being green and healthy; the pest trapping device adjusts the suction force according to the pest situation to trap different types of pests. In addition, the method of trapping pests by suction force achieves the goal of being green and efficient.

[0047] Furthermore, it is equipped with data recording capabilities to record relevant information for each harvest, such as variety, quantity, and quality. Data analysis tools are provided to help farmers better understand yield and plant condition, enabling them to make informed decisions and optimize planting management.

[0048] This invention also discloses a chili pepper variety and quality identification, agricultural pest control, and harvesting path planning system, used to plan the shortest operating path with minimal damage to chili pepper trees. It achieves multi-functionality by adding a pesticide spraying module and an insect capture module to the chili pepper harvester. During the chili pepper harvesting process, the module can also perform maximum pollution-free treatment of weeds and pests. The chili pepper harvesting module allows the machine to harvest different types of chili peppers in different environments, enabling more scientific and standardized pesticide spraying and more environmentally friendly and efficient pest control, effectively removing pests and weeds from chili pepper fields and completing chili pepper planting and maintenance work, saving significant manpower and resources. The pesticide spraying module, based on information from the data processing module, will apply corresponding pesticides to different types of pests or weeds, and will also adjust the pesticide dosage according to the severity of the infestation to achieve resource conservation and environmental health goals. The insect capture module will adjust different suction levels according to the pest situation to capture different types of pests; furthermore, the use of suction to capture pests achieves environmentally friendly and efficient results. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of the device for identifying chili pepper varieties and quality, controlling agricultural pests, and planning harvesting routes according to the present invention.

[0050] Figure 2 This is a schematic diagram of the connection structure between the device and control system for chili pepper variety and quality identification, agricultural pest control, and harvesting path planning of the present invention.

[0051] Figure 3This is a flowchart of the chili pepper variety quality identification, agricultural pest control, and harvesting route planning method of the present invention;

[0052] Figure 4 This is a flowchart of the pest capture and pesticide spraying process of the present invention;

[0053] Figure 5 This is a flowchart illustrating the vehicle control process of the present invention.

[0054] The components are: 1-Camera; 2-Pesticide storage container; 3-Pesticide spraying device; 4-Pest trapping device; 5-Chili pepper harvesting device; 6-Chili pepper storage box; 7-NVIDIA Jetson Nano development board; 8-Data processing unit; 9-Obstacle detection device. Detailed Implementation

[0055] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0056] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0057] The present invention will now be described in further detail with reference to the accompanying drawings:

[0058] See Figure 1 This is a schematic diagram of the device for chili pepper variety and quality identification, agricultural pest control, and harvesting route planning according to the present invention; see also Figure 2This is a schematic diagram of the connection structure between the device and control system for chili pepper variety quality identification, agricultural pest control, and harvesting path planning of the present invention. As shown in the diagram, the device includes a chili pepper harvesting machine body, a camera 1 mounted on the harvesting machine body, a control unit, a harvesting route planning device, a chili pepper harvesting device 5, a pesticide spraying device 3, and a pest trapping device 4. The camera 1 is used to acquire image information of chili peppers, weeds, and pests. The control unit is used to receive, process, and analyze the image information captured by the camera 1, and to process, extract features, and classify the image information. The harvesting route planning device is used to receive instructions from the control unit and plan the shortest operating path for chili pepper harvesting. The chili pepper harvesting device 5 is used to receive instructions from the control unit and harvest chili peppers according to the shortest operating path planned by the harvesting route planning device. The pesticide spraying device 3 is used to receive instructions from the control unit to spray pesticides for pest control or weed control. The pest trapping device 4 is used to receive instructions from the control unit to trap pests on the chili peppers. The control unit includes an NVIDIA Jetson Nano development board 7, a data processing unit 8, and a control system. Under the instructions of the control system, the NVIDIA Jetson Nano development board 7 processes, extracts features from, and classifies the image information acquired by the camera 1. This includes identifying the type, quality, pests, and weeds of the chili peppers, and transmitting the analysis results to the data processing unit 8. The data processing unit 8 receives the analysis results from the NVIDIA Jetson Nano development board 7, configures the parameters, and sends them to the control system. The control system then controls the chili pepper harvesting device 5 and the pest trapping device 4. A pesticide storage container 2 is installed above the main body of the chili pepper harvester, and a chili pepper storage box 6 is installed below the main body. A chili pepper positioning device and an obstacle detection device 9 are also installed on the main body of the chili pepper harvester. The chili pepper positioning device determines the spatial location of mature, harvestable chili peppers and transmits the information to the control unit. The obstacle detection device 9 detects obstacles during the harvesting process and transmits the information to the control unit.

[0059] See Figure 3This is a flowchart of the chili pepper variety quality identification, agricultural pest control, and harvesting route planning method of the present invention. As shown in the diagram, the NVIDIA Jetson Nano development board 7 identifies and determines thresholds for the chili pepper variety, appearance, pests on the chili pepper, and weeds near the chili pepper plant, and transmits the obtained relevant information to the data processing unit 8, the chili pepper positioning device, and the obstacle detection device 9. The chili pepper positioning device, referring to the information obtained from the NVIDIA Jetson Nano development board 7, determines the spatial location of mature chili peppers to be harvested, pests, and nearby weeds, and then transmits the location information to the harvesting route planning device. The obstacle detection device 9 uses the NVIDIA Jetson Nano development board 7... The Nano development board 7 transmits information to perform image analysis, detects obstacles encountered by the chili harvesting device 5 during chili harvesting, and then transmits this information to the harvesting route planning device. The harvesting route planning device plans the route for the chili harvesting device 5 to harvest chilies and remove weeds. Based on information from the chili positioning device and obstacle detection device 9, it plans the harvesting order of the target chilies and the order of weed removal. Taking into account obstacles on the harvesting path, a route simulation system is used for simulation. The chili harvesting device 5 will sequentially remove weeds and bypass obstacles to reach the target chilies for harvesting. The harvesting and retrieval will also follow the original route to avoid damaging the chili trees. The data processing unit 8 summarizes and processes the information and data obtained from each part. Regarding pesticide spraying, the data processing unit 8 will use NVIDIA Jetson... The information data transmitted by the Nano development board 7 determines the types and severity of pests and weeds in a certain area based on the set relevant thresholds. Finally, the processed execution program is submitted to the control system connected to the chili harvesting device 5 and the pesticide spraying device 3. The control system executes the corresponding program according to the final judgment result. If the weed density is lower than the system-set threshold, the chili harvesting device 5 will perform weeding operation; if the weed density is higher than the system-set threshold, the chili harvesting device 5 will not perform weeding operation. At this time, the pesticide spraying device 3 will work to spray pesticides in the area. In terms of pest capture, the data processing unit 8 will determine the pest situation around the chili pepper tree based on the information data transmitted by the NVIDIA Jetson Nano development board 7 and the threshold set by the system. Finally, the processed execution program will be submitted to the control system connected to the pest capture device. The control system will execute the corresponding program according to the final judgment result. If the pest density is less than the threshold set by the system, the pest capture device will work and suck the pests on the chili pepper tree into the capture bag through the vacuum tube. If the pest density is greater than the threshold set by the system, the pest capture device will not work. At this time, the pesticide spraying device 3 will work to spray pesticides on the chili pepper tree with high pest density.Finally, the control system controls the chili harvesting device 5, the pest trapping device, and the pesticide spraying device 3 to complete the chili harvesting, weeding, pest trapping, and pesticide spraying.

[0060] See Figure 4 This is a flowchart of the pest capture and pesticide spraying process of the present invention. As shown in the diagram, in terms of pest control, the data processing unit 8 first determines the pest situation around the chili pepper tree based on the information data transmitted by the NVIDIA Jetson Nano development board 7 and the system-set threshold. Finally, the processed execution program is submitted to the control system connected to the pest capture device. The control system executes the corresponding program based on the final judgment result. If no pests are found, neither the pest capture device 4 nor the pesticide spraying device 3 operates. If pests are found and their density is less than the system-set threshold, the pest capture device 4 operates, sucking the pests from the chili pepper tree into a capture bag through a vacuum tube. If pests are found and their density is greater than the system-set threshold, the suction device does not operate, and the pesticide spraying device 3 operates to spray pesticides on the chili pepper trees with high pest density. Finally, the control system controls the chili pepper harvesting device 5, the pest capture device, and the pesticide spraying device 3 to complete the chili pepper harvesting, weed control, pest capture, and pesticide spraying.

[0061] See Figure 5 This is a flowchart of the vehicle driving control process of the present invention. As can be seen from the figure, after the device is started, the data processing unit 8 will identify and locate the chili peppers based on the information data transmitted by the NVIDIA Jetson Nano development board 7, and then establish a road network map. At this time, Dijkstra is applied to plan the vehicle's driving path, select the best path, and transmit the program to the control system to control the vehicle's movement.

[0062] This invention discloses a chili pepper variety quality identification, agricultural pest control, and harvesting path planning device. The device includes a chili pepper harvesting device 5, a pesticide spraying device 3, a pest trapping device, a camera 1 installed on the main body of the chili pepper harvesting machine, a data processing unit 8, an NVIDIA Jetson Nano development board 7, a chili pepper positioning device, an obstacle detection device (branches and leaves next to the chili pepper, tall weeds, etc.), a harvesting route planning device, and a control system. The NVIDIA Jetson Nano development board 7 is used to identify the types of chili peppers (bird's eye chili, ghost pepper, horn pepper, bell pepper, sweet pepper, etc.), the quality of the chili peppers, pests on the chili peppers (such as aphids, tobacco budworms, silkworms, mole crickets, snails, grasshoppers, etc.), and weeds near the chili pepper plants (foxtail grass, goosegrass, purslane, etc.). The identified image information is processed using computer vision algorithms for image preprocessing, feature extraction, feature matching, classification and recognition, threshold determination, and output of the threshold determination results. The relevant image information is then transmitted to the data processing unit 8, the chili pepper positioning device, and the obstacle (branches and leaves next to the chili peppers, tall weeds, etc.) detection device. The chili pepper positioning device, used by the chili pepper harvesting device 5, determines the spatial location of mature, harvestable chili peppers and nearby weeds based on information obtained from the NVIDIA Jetson Nano development board 7 before harvesting the chili peppers, and then transmits the location information to the harvesting route planning device. The obstacle (branches and leaves next to the chili peppers, tall weeds, etc.) detection device detects the NVIDIA Jetson... The Nano development board 7 performs image analysis on the information transmitted, detecting obstacles encountered by the chili harvesting device 5 during the chili harvesting process. This information is then transmitted to the harvesting route planning device, which plans the shortest operating path for the chili harvesting device 5 while minimizing damage to the chili trees. The route planning system utilizes information from the chili positioning device and obstacle detection devices (branches and leaves near the chilies, tall weeds, etc.), taking into account obstacles along the harvesting path. The chili harvesting device 5 prioritizes harvesting chilies along the path planned by the route planning system and then places the harvested chilies into the chili collection box 6. After harvesting, if the weed density per unit area along the harvesting path is lower than the system-set threshold, the chili harvesting device 5 will perform weeding; if the weed density is higher than the system-set threshold, the chili harvesting device 5 will not perform weeding, and the pesticide spraying device 3 will then spray pesticides on the area.In terms of pest control, the NVIDIA Jetson Nano development board 7 transmits image information to the data processing unit 8 to determine the severity of pests on the chili pepper trees. If the pest density is less than the system-set threshold, the pest trapping device will activate, sucking the pests from the chili pepper trees into a trapping bag via a vacuum tube. If the pest density is greater than the system-set threshold, the pest trapping device will not activate, and the pesticide spraying device 3 will activate to spray pesticides on the chili pepper trees with high pest density. The pesticide spraying device 3 will use the information transmitted by the data processing unit 8 to select the appropriate pesticide for different types of pests or weeds, and will also adjust the pesticide dosage according to the severity of the infestation to achieve resource conservation and environmental health goals. The pest trapping device will adjust the suction power according to the pest situation to trap different types of pests. Furthermore, the method of trapping pests using suction achieves a green and efficient goal. This invention achieves multiple uses in one machine. A pesticide spraying device 3 and a pest trapping device 4 are added to the chili harvester. During the chili harvesting process, the chili harvesting device 5 can also perform maximum pollution-free treatment of weeds and pests. The chili harvesting device 5 allows the machine to harvest different types of chilies in different environments, enabling more scientific and standardized pesticide spraying and more green and efficient pest control. It removes pests and weeds from chili fields, effectively completing the chili planting and maintenance work while saving significant manpower and resources.

[0063] The NVIDIA Jetson Nano development board 7 connects to camera 1 on the main body of the chili harvester to identify chili varieties (bird's eye chili, ghost pepper, horn pepper, bell pepper, sweet pepper, etc.), chili quality, pests on the chilies (such as aphids, tobacco budworms, silkworms, mole crickets, snails, grasshoppers, etc.), and weeds near the chili plants (foxtail grass, goosegrass, purslane, etc.) and obtain relevant information. The NVIDIA Jetson Nano development board 7 includes a high-definition image acquisition system, an information feedback system, a chili target recognition system, a chili variety and quality analysis system, and a pest and weed recognition system, as well as a deep learning model. The high-definition image acquisition system captures high-definition images of the chilies and surrounding objects and transmits this image information to the chili target recognition system, the chili variety and quality analysis system, and the pest and weed recognition system. These systems use computer vision algorithms to identify the appearance of the chilies, pests, and weeds.

[0064] The main steps for identifying the types of chili peppers, their quality, pests on the peppers, and weeds near the chili pepper trees are as follows: (1) Image preprocessing: Denoising, enhancing, scaling, and other operations are performed on the collected images to better extract the features of chili peppers, pests, and weeds; (2) Feature extraction: Meaningful features of chili peppers, pests, and weeds are extracted from the preprocessed images. The methods used include edge detection, corner detection, and feature description; (3) Feature matching: The extracted features of chili peppers, pests, and weeds are matched with the known feature database to determine the matching features of chili peppers, pests, and weeds in the image with respect to the known feature data; (4) Classification and recognition: The images are classified according to the matching results. Classification: Identify the types of chili peppers (such as chili peppers, ghost peppers, horn peppers, bell peppers, sweet peppers, etc.) and their quality, as well as the types of pests (such as aphids, tobacco budworms, silkworms, mole crickets, etc.) and the types of weeds (such as foxtail grass, goosegrass, purslane, etc.); (5) Threshold determination: Extract information data about the density of weeds and the density of pests from the preprocessed image and compare it with the relevant thresholds set by the system to obtain execution information data that meets the threshold requirements; (6) Output of identification and threshold determination results: Based on the classification results of the types and quality of chili peppers, the types of pests and weeds, and the determination results of weeds and pests regarding the thresholds set by the system, output the identification results and threshold determination results of chili peppers, pests and weeds. Then the information feedback system collects and stores the relevant information of chili peppers, pests and weeds in the form of data and transmits it to the data processing unit 8. Deep learning models can be trained and learned based on the recognition process of computer vision algorithms, thereby improving the accuracy of identifying chili peppers, pests, and weeds, and enabling them to adapt to changes in the degree of pests, the degree of weed coverage, and the variety of chili peppers in different planting environments.

[0065] The chili pepper positioning device uses information transmitted by an image recognition device to determine the spatial location of chili peppers before harvesting by the chili pepper harvesting device 5. The chili pepper positioning device includes an image analysis system, a photosensor, a lighting device, an ultrasonic positioning system, a dynamic positioning system (BeiDou satellite positioning system), and also includes real-time data transmission, automatic correction functions, and multi-sensor fusion technology. The image analysis system in the chili pepper positioning device converts relevant information from the image recognition device into a two-dimensional planar image for processing and analysis. It uses image segmentation methods to segment the constituent objects in the relevant image, classifies and identifies these objects to determine if they are chili peppers. If they are chili peppers, they are further classified and given corresponding names based on their maturity and growth condition (such as the vibrancy of the color, the wrinkles on the skin, and the fullness of the shape), such as mature high-quality chili peppers, mature general-quality chili peppers, etc., and marked as targets for positioning. The photosensor is used to measure the lighting conditions of the chili pepper harvesting environment to ensure that the location identification is performed in a well-lit environment, guaranteeing the accuracy of the location identification and reducing errors. If the ambient light conditions are poor before the chili harvesting device 5 harvests the chilies, falling below the light sensitivity threshold of the photosensitive sensor, the photosensitive sensor will generate a light signal and transmit it to the lighting unit. The lighting unit converts the received light signal into an electrical signal and transmits it to the processing unit within the lighting unit for processing and judgment, ultimately outputting a measurement value. The lighting unit then applies different levels of lighting to the harvesting area based on the measurement value, ensuring sufficient ambient light while reducing energy consumption. An ultrasonic positioning system is used to determine the spatial location of the chilies. When determining the chili's location, the ultrasonic transmitter in the ultrasonic positioning system sends ultrasonic pulses towards the chili at regular time intervals, determining the chili's spatial location by comparing the time sequence of received signals. The location identification device also includes a dynamic positioning system (BeiDou satellite positioning system) to obtain the precise location information of the chili harvester in the field. The real-time data function transmits the collected location information to the data processing unit 8 and the control system for real-time monitoring and adjustment of the harvesting device's operation. The automatic correction function can adjust the device when errors or uncertainties are detected, allowing for repositioning and improving identification accuracy. Furthermore, the device is designed to withstand various environments, giving it dustproof, waterproof, and shockproof properties (e.g., the device is sealed to achieve waterproof and dustproof effects; an inlay groove is provided at the installation location, the device base is fixed to the inlay groove with screws, and flexible cushioning materials such as rubber are used to achieve shock resistance). This ensures stable operation under various conditions and accurate determination of the chili pepper's location.

[0066] The pesticide spraying device 3 and pest trapping device are mounted on the main frame of the harvester. The pesticide spraying device 3 is equipped with various types of spraying nozzles, such as centrifugal nozzles, pressure nozzles, or mist sprayers. Different types of nozzles can be selected to suit different pesticides and crops. It offers various capacity options to meet the needs of fields of different sizes. The device also features a detachable spray tank for easy movement and operation. To ensure uniform spraying and improve efficiency, the pesticide spraying device 3 is equipped with a spray control system, such as an automatic flow regulation system and a timer control system. To protect the environment and the health of the chili peppers, the pesticide spraying device 3 can also perform localized spraying. The spraying device is compatible with various types of pesticides to ensure effective control of various pests and diseases. Users can select different types of pesticides and adjust spray parameters to suit different varieties of chili peppers and environmental conditions. To meet environmental protection requirements, the pesticide spraying device 3 is equipped with various environmentally friendly technologies, such as low-flow spraying technology and spray deposition control technology, to reduce pesticide pollution. The pest trapping device is equipped with a suction motor, speed controller, direction controller, vacuum tube, and pest trapping bag. Furthermore, the device is connected to a data processing unit 8 and a control system. An image recognition device determines the pest situation, which in turn drives the device via the control system. When the device starts working, the impeller in the suction motor rotates at high speed, creating a pressure difference with the outside environment, thus generating suction. This suction draws pests around the chili pepper plant (such as aphids, tobacco budworms, silkworms, mole crickets, snails, and grasshoppers) through the vacuum tube into the trapping bag. The speed controller adjusts the rotational speed of the impeller in the suction motor to change the suction strength. This adjustment in suction strength is beneficial for pest trapping: a medium speed is used for smaller pests (such as aphids, tobacco budworms, silkworms, and mole crickets), while a higher speed is used for larger pests (such as snails and grasshoppers). The direction controller controls the direction of the pest-catching device. It includes an information receiving module that receives relevant information from the data processing unit 8. Based on this information, the direction controller controls the direction of the pest-catching device when catching pests. The pest-catching device is a green and efficient pest control device: by using suction to catch pests, it not only protects the chili pepper trees from damage but also improves catching efficiency; by changing the suction strength, different types of pests can be caught. When the image recognition device detects that there are no pests or weeds in a certain area, the pesticide spraying device 3 and the pest-catching device do not operate.When pests are detected in a certain area, and the pest density is less than the system-set threshold, the pest trapping device will activate, sucking the pests from the chili pepper trees into a trapping bag via a vacuum tube. If the pest density is greater than the system-set threshold, the pest trapping device will not activate, and the pesticide spraying device 3 will activate to spray pesticides on the chili pepper trees with high pest density. For weed control, after the chili peppers are harvested, if the weed density per unit area along the harvesting path is less than the system-set threshold, the chili pepper harvesting device 5 will perform weeding. If the weed density is greater than the system-set threshold, the chili pepper harvesting device 5 will not perform weeding, and the pesticide spraying device 3 will activate to spray pesticides on the area. Pesticide compatibility: The device is compatible with various types of pesticides to ensure effective control of various pests and diseases. Users can select different types of pesticides as needed and adjust the spraying parameters to suit different varieties of chili peppers and environmental conditions; Environmental friendliness: In order to meet environmental protection requirements, the pesticide spraying device 3 is equipped with various environmental protection technologies, such as low flow spraying technology and spray deposition control technology, to reduce pesticide pollution to the environment.

[0067] An obstacle detection device (such as branches and leaves next to chili peppers, tall weeds, etc.) is included. The obstacle detection device 9 is used to detect obstacles such as branches and leaves along the working route when the chili pepper harvesting device 5 is harvesting chili peppers and removing weeds. The obstacle detection device 9 includes a lidar, a light receiver, an obstacle information extraction and output system, and an information feedback system. The lidar is used to determine obstacle-related information, such as the distance, orientation, attitude, and shape of the obstacle. Its workflow is as follows: the laser transmitter converts electrical pulses into light pulses and emits detection signals along the harvesting route. The light receiver receives the signals reflected back from the obstacle, restores the reflected light pulses to electrical pulses, and sends them to the display. The information processing system then processes the electrical pulses related to the obstacle into data information such as the obstacle's distance, orientation, attitude, and shape, and displays this data. The obstacle information extraction and output system extracts the information displayed by the lidar and outputs it to the information feedback system. The information feedback system then feeds back the relevant information about the obstacle's distance, orientation, attitude, and shape to the data processing unit 8.

[0068] A harvesting route planning device is used to plan the shortest operating path for the chili harvesting device 5 while minimizing damage to the chili trees. This device is connected to the data processing unit 8. The harvesting route planning device includes an information receiving and processing system, an information output system, an information feedback system, and a route planning system. The information receiving and processing system receives and processes information data from the chili positioning device and obstacle height detection device in the data processing unit 8, and transmits this information to the route planning system through the information output system. The route planning system determines the spatial location of the target chili relative to the chili harvesting device 5 using the relevant information from the chili positioning device, and determines the location information of obstacles (branches and leaves next to the chili, tall weeds, etc.) on the harvesting route using the obstacle detection device. After determining the relevant information, the harvesting route information is fed back to the data processing unit 8 through the information feedback system.

[0069] The chili harvesting device 5, equipped with a multi-degree-of-freedom robotic arm, is mounted on the main frame of the intelligent chili harvesting machine for harvesting chilies. Rubber inserts on the harvesting claws prevent chili loss. The chili harvesting device 5 is connected to a camera 1 mounted on the intelligent chili harvesting machine. The image recognition device, chili positioning device, and obstacle detection device (such as branches and leaves near the chilies, tall weeds, etc.) in the camera 1 identify and judge relevant information data about the chilies (such as the spatial location of the chilies, the spatial location of obstacles along the harvesting path, and the shape and size of the chilies), and feed this information back to the data processing unit 8 in the chili harvesting device 5. The data processing unit 8 then summarizes and processes the relevant information data before submitting it to the harvesting route planning device in the chili harvesting device 5. The harvesting route planning device then determines the route for the chili harvesting device 5 based on the relevant information data and finally feeds this route information back to the data processing unit 8. The data processing unit 8 then summarizes the information, generates a corresponding execution program, and submits it to the control system on the chili harvesting device 5 for execution. Camera 1, mounted on the main body of the intelligent chili-harvesting machine, is located on both sides of the machine. It features high resolution and captures high-definition images of various conditions in the field. Camera 1 works in conjunction with the NVIDIA Jetson Nano development board 7, the chili-positioning device, and the obstacle detection device (branches and leaves near the chilies, tall weeds, etc.) to quickly acquire information such as the location, shape, size of the chilies, pests, and weeds near the chili plants. This information allows for the determination of the chili's type and quality, as well as pest and weed information. The acquired data is then submitted to the data processing unit 8. The control system executes the harvesting, pest-catching, and pesticide spraying procedures transmitted by the data processing unit 8.

[0070] This invention discloses a chili pepper variety and quality identification, agricultural pest control, and harvesting path planning device. The device includes a chili pepper harvesting device 5, a pesticide spraying device 3, a camera 1 mounted on the main body of the chili pepper harvester, a data processing unit 8, an NVIDIA Jetson Nano development board 7, a chili pepper positioning device, an obstacle detection device (branches and leaves near the chili peppers, tall weeds, etc.), a harvesting route planning device, and a control system. The chili pepper harvesting device 5 is a multi-degree-of-freedom robotic arm and a sliding rail. It can move horizontally with the chili pepper harvester and can perform vertical movement, 360-degree rotation, and extension / retraction in multiple directions to harvest and classify chili peppers and remove weeds. The NVIDIA Jetson Nano development board 7 is connected to the camera 1 on the chili pepper harvester and is used to identify the chili pepper variety, quality, pests on the chili peppers, and weeds near the chili pepper plant, obtaining relevant information. The NVIDIA Jetson Nano development board 7 includes a high-definition image capture system, an information feedback system, a chili pepper target recognition system, a chili pepper variety and quality classification system, a pest and weed recognition system, and a deep learning model. A chili pepper positioning device, working in conjunction with an image recognition device, is used to determine the spatial location of chili peppers and weeds near the chili pepper plant before the chili pepper harvesting device 5 harvests the peppers. The positioning device includes an image analysis system, optical sensors, ultrasonic sensors, a dynamic positioning system (BeiDou satellite positioning system), and also includes real-time data transmission, automatic correction functions, and multi-sensor fusion technology. An obstacle detection device 9 is used to detect obstacles on the working path of the multi-degree-of-freedom robotic arm for harvesting chili peppers and removing weeds. A harvesting route planning device is used to plan the working path of the chili pepper harvesting device 5.

[0071] This invention discloses a chili pepper variety quality identification, agricultural pest control, and harvesting path planning device. The device includes a chili pepper harvesting device 5, a pesticide spraying device 3, a pest trapping device, a camera 1 installed on the main body of the chili pepper harvesting machine, a data processing unit 8, an NVIDIA Jetson Nano development board 7, a chili pepper positioning device, an obstacle detection device (branches and leaves next to the chili pepper, tall weeds, etc.), a harvesting route planning device, and a control system. The NVIDIA Jetson Nano development board 7 is used to identify the types of chili peppers (bird's eye chili, ghost pepper, horn pepper, bell pepper, sweet pepper, etc.), the quality of the chili peppers, pests on the chili peppers (such as aphids, tobacco budworms, silkworms, mole crickets, snails, grasshoppers, etc.), and weeds near the chili pepper plants (foxtail grass, goosegrass, purslane, etc.). The identified image information is processed using computer vision algorithms for image preprocessing, feature extraction, feature matching, classification and recognition, threshold determination, and output of the threshold determination results. The relevant image information is then transmitted to the data processing unit 8, the chili pepper positioning device, and the obstacle (branches and leaves next to the chili peppers, tall weeds, etc.) detection device. The chili pepper positioning device, used by the chili pepper harvesting device 5, determines the spatial location of mature, harvestable chili peppers and nearby weeds based on information obtained from the NVIDIA Jetson Nano development board 7 before harvesting the chili peppers, and then transmits the location information to the harvesting route planning device. The obstacle (branches and leaves next to the chili peppers, tall weeds, etc.) detection device detects the NVIDIA Jetson... The Nano development board 7 performs image analysis on the information transmitted, detecting obstacles encountered by the chili harvesting device 5 during the chili harvesting process. This information is then transmitted to the harvesting route planning device, which plans the shortest operating path for the chili harvesting device 5 while minimizing damage to the chili trees. The route planning system utilizes information from the chili positioning device and obstacle detection devices (branches and leaves near the chilies, tall weeds, etc.), taking into account obstacles along the harvesting path. The chili harvesting device 5 prioritizes harvesting chilies along the path planned by the route planning system and then places the harvested chilies into the chili collection box 6. After harvesting, if the weed density per unit area along the harvesting path is lower than the system-set threshold, the chili harvesting device 5 will perform weeding; if the weed density is higher than the system-set threshold, the chili harvesting device 5 will not perform weeding, and the pesticide spraying device 3 will then spray pesticides on the area. In terms of pest control, the NVIDIA Jetson Nano development board 7 transmits image information to the data processing unit 8 to determine the severity of pests on the chili pepper trees. If the pest density is less than the system-set threshold, the pest trapping device will operate, sucking the pests on the chili pepper trees into the trapping bag through a vacuum tube. If the pest density is greater than the system-set threshold, the pest trapping device will not operate, and the pesticide spraying device 3 will operate to spray pesticides on the chili pepper trees with high pest density.The pesticide spraying device 3, based on information transmitted by the data processing unit 8, will apply corresponding pesticides to different types of pests or weeds, and will also adjust the dosage of pesticide spraying according to the severity of the infestation, in order to achieve the goals of resource conservation and environmental health. The pest trapping device will adjust different suction levels according to the pest situation to trap different types of pests. In addition, the method of trapping pests using suction achieves the goal of green efficiency. This invention realizes multiple uses in one machine. By adding a pesticide spraying device 3 and a pest trapping device 4 to the chili harvester, the chili harvesting device 5 can also carry out the maximum pollution-free treatment of weeds and pests during the chili harvesting process. The chili harvesting device 5 allows the machine to harvest different types of chilies in different environments, spraying pesticides more scientifically and in a more green and efficient manner, removing pests and weeds from chili fields, effectively completing the chili planting and maintenance work, and saving a lot of manpower and material resources.

[0072] This invention discloses a method for chili pepper variety and quality identification, agricultural pest control, and harvesting route planning, specifically including the following steps: An NVIDIA Jetson Nano development board 7 is used to identify and threshold the types of chili peppers (such as chili peppers, ghost peppers, horn peppers, bell peppers, sweet peppers, etc.), their appearance, pests on the chili peppers (such as aphids, tobacco budworms, silkworms, mole crickets, snails, grasshoppers, etc.), and weeds near the chili pepper plants (such as foxtail grass, goosegrass, purslane, etc.), and transmits the obtained relevant information to a data processing unit 8, a chili pepper positioning device, and an obstacle (branches and leaves next to the chili peppers, tall weeds, etc.) detection device; the chili pepper positioning device, before the chili pepper harvesting device 5 harvests the chili peppers, uses information obtained from the NVIDIA Jetson Nano development board 7 to determine the spatial location of mature chili peppers to be harvested, pests, and nearby weeds, and then transmits the location information to the harvesting route planning device; the obstacle (branches and leaves next to the chili peppers, tall weeds, etc.) detection device uses an NVIDIA Jetson Nano development board 7... The Nano development board 7 transmits information for image analysis, detecting obstacles encountered by the chili harvesting device 5 during chili harvesting. This information is then transmitted to the harvesting route planning device. The harvesting route planning device plans the route for the chili harvesting device 5 to harvest chilies and clear weeds. Using information from the chili positioning device and obstacle detection devices (branches and leaves near the chilies, tall weeds, etc.), it plans the harvesting order of the target chilies and the order of weed clearing, taking into account obstacles along the harvesting path. Through a route simulation system, the chili harvesting device 5 will sequentially remove weeds and bypass obstacles to reach the target chilies for harvesting. The harvested chilies will also be retrieved along the original route to prevent damage to the chili plants. The data processing unit 8 summarizes and processes the information and data obtained from each part. In terms of pesticide spraying, the data processing unit 8 will use NVIDIA Jetson... The information data transmitted by the Nano development board 7 determines the types and severity of pests and weeds in a certain area based on the set relevant thresholds. Finally, the processed execution program is submitted to the control system connected to the chili harvesting device 5 and the pesticide spraying device 3. The control system executes the corresponding program according to the final judgment result (if the weed density is lower than the system-set threshold, the chili harvesting device 5 will perform weeding operation; if the weed density is higher than the system-set threshold, the chili harvesting device 5 will not perform weeding operation, and at this time the pesticide spraying device 3 will work to spray pesticides in the area).In terms of pest capture, the data processing unit 8, based on the information transmitted by the NVIDIA Jetson Nano development board 7, judges the pest situation around the chili pepper trees according to the system-set threshold, and finally submits the processed execution program to the control system connected to the pest capture device. The control system executes the corresponding program according to the final judgment result (if the pest density is less than the system-set threshold, the pest capture device will work, sucking the pests on the chili pepper trees into the capture bag through the vacuum tube; if the pest density is greater than the system-set threshold, the pest capture device will not work, and at this time the pesticide spraying device 3 will work to spray pesticides on the chili pepper trees with high pest density). Finally, the control system controls the chili pepper harvesting device 5, the pest capture device, and the pesticide spraying device 3 to complete the chili pepper harvesting, weeding, pest capture, and pesticide spraying. The pesticide spraying device 3 will configure corresponding pesticides according to the information transmitted by the data processing unit 8 for different types of pests or weeds, and will also adjust the dosage of pesticide spraying according to the severity of the problem, so as to achieve the purpose of saving resources and green health; the pest trapping device will adjust different suction according to the pest situation to trap different types of pests. In addition, the method of trapping pests by suction achieves the purpose of green and efficient.

[0073] This invention discloses a method for chili pepper variety and quality identification, agricultural pest control, and harvesting path planning, comprising: acquiring chili pepper location information, chili pepper shape information, chili pepper size information, obstacle information, pest information, and weed information; obtaining spatial location information of mature chili peppers to be harvested, pests, and nearby weeds based on the chili pepper location information, chili pepper shape information, chili pepper size information, pest information, and weed information; detecting obstacles encountered during chili pepper harvesting and performing image analysis to obtain analyzed obstacle information; planning a route for harvesting chili peppers and handling weeds based on the spatial location information of mature chili peppers to be harvested, pests, and nearby weeds, and the analyzed obstacle information, sequentially removing weeds and bypassing obstacles to reach the target chili peppers for harvesting; processing the chili pepper spatial location information and the analyzed obstacle information to obtain a harvesting execution program, a pest capture program, and a pesticide spraying program; and completing the chili pepper harvesting, weed handling, pest capture, and pesticide spraying work according to the harvesting execution program, pest capture program, and pesticide spraying program. The system acquires information on chili pepper location, shape, size, obstacles, pests, and weeds. Specifically, it uses an NVIDIA Jetson Nano 7 development board to identify chili pepper species, quality, pests on the peppers, and weeds near the chili pepper plant, obtaining corresponding image information. The identified image information is then processed using computer vision algorithms for image preprocessing, feature extraction, feature matching, classification and recognition, threshold determination, and identification. The NVIDIA Jetson Nano 7 development board includes a high-definition image acquisition system, an information feedback system, a chili pepper target recognition system, a chili pepper species and quality analysis system, a pest and weed identification system, and a deep learning model. The high-definition image acquisition system acquires high-definition images of the chili peppers and surrounding objects, and the information feedback system transmits these images to the chili pepper target recognition system, chili pepper species and quality analysis system, and pest and weed identification system. These systems then use deep learning models to identify the appearance of the chili peppers, pests, and weeds.Based on information about the location, shape, and size of the chili peppers, as well as information about pests and weeds, the spatial location information of the mature chili peppers, pests, and nearby weeds to be harvested is obtained. Specifically, this includes: using an image recognition device, an image analysis system, a photosensor, a lighting device, an ultrasonic positioning system, a dynamic positioning system, a real-time data transmission unit, and an automatic correction unit to obtain the spatial location information of the mature chili peppers, pests, and nearby weeds; the image analysis system, based on the information transmitted by the image recognition device, converts the relevant information into a two-dimensional planar image for processing and analysis; the photosensor measures the lighting conditions of the chili pepper harvesting environment, generates a light signal, and transmits it to the lighting device; the ultrasonic positioning system determines the spatial location of the chili peppers; the dynamic positioning system acquires the precise location information of the chili pepper harvester in the field; the real-time data transmission unit transmits the collected location information to the control unit; and the automatic correction unit detects errors or uncertainties and adjusts or repositions the device accordingly. The system detects obstacles encountered during chili pepper harvesting and performs image analysis to obtain obstacle information. Specifically, it combines a lidar system, an optical receiver, an obstacle information extraction and output system, and an information feedback system to obtain the analyzed obstacle information. The lidar transmitter converts electrical pulses into light pulses and emits detection signals along the harvesting route. The optical receiver receives the signals reflected back from the obstacles, restores the reflected light pulses to electrical pulses, and sends them to the display. The information processing system then processes the electrical pulses related to the obstacles on the display into data information such as the obstacle's distance, orientation, attitude, and shape, and displays this data on the display. The obstacle information extraction and output system extracts the information displayed by the lidar and outputs it to the information feedback system. The information feedback system then feeds back the relevant information about the obstacle's distance, orientation, attitude, and shape to the data processing unit 8. After the chili peppers are harvested, if the weed density per unit area along the harvesting path is lower than the system's set threshold, weeding is performed; if the weed density is higher than the system's set threshold, weeding is not performed, and pesticides are sprayed in the area. If the pest density on the chili pepper plant is less than the system-set threshold, the pests are sucked into a capture bag via a vacuum tube; if the pest density exceeds the system-set threshold, pesticides are sprayed onto the plant. During pesticide spraying, based on information transmitted by the data processing unit 8, corresponding pesticides are formulated for different types of pests or weeds, and the dosage is adjusted according to the severity of the infestation. During pest capture, the suction strength is adjusted according to the pest situation to capture different types of pests.

[0074] This invention discloses a method for identifying chili pepper varieties and quality, controlling agricultural pests, and planning harvesting paths. Chili peppers are harvested preferentially along the path planned by the chili pepper harvesting device 5, and then placed in a chili pepper storage box 6. After harvesting, if the weed density per unit area along the harvesting path is lower than a system-set threshold, the chili pepper harvesting device 5 will perform weeding; if the weed density is higher than the system-set threshold, the chili pepper harvesting device 5 will not perform weeding, and the pesticide spraying device 3 will operate to spray pesticides on the area. Regarding pest control, the NVIDIA Jetson Nano development board 7 transmits image information to the data processing unit 8 to determine the severity of pests on the chili pepper trees. If the pest density is lower than the system-set threshold, the pest trapping device will operate, sucking the pests from the chili pepper trees into a trapping bag through a vacuum tube; if the pest density is higher than the system-set threshold, the pest trapping device will not operate, and the pesticide spraying device 3 will operate to spray pesticides on chili pepper trees with high pest density. The pesticide spraying device 3, based on information transmitted by the data processing unit 8, will apply corresponding pesticides to different types of pests or weeds, and will also adjust the dosage of pesticide spraying according to the severity of the infestation, in order to achieve the goals of resource conservation and environmental health. The pest trapping device will adjust different suction levels according to the pest situation to trap different types of pests. In addition, the method of trapping pests using suction achieves the goal of green efficiency. This invention realizes multiple uses in one machine. By adding a pesticide spraying device 3 and a pest trapping device 4 to the chili harvester, the chili harvesting device 5 can also carry out the maximum pollution-free treatment of weeds and pests during the chili harvesting process. The chili harvesting device 5 allows the machine to harvest different types of chilies in different environments, spraying pesticides more scientifically and in a more green and efficient manner, removing pests and weeds from chili fields, effectively completing the chili planting and maintenance work, and saving a lot of manpower and material resources.

[0075] This invention discloses a method for identifying chili pepper varieties and quality, controlling agricultural pests, and planning harvesting paths. It aims to improve the efficiency and accuracy of chili pepper harvesting, is applicable to different environments and varieties, reduces labor intensity, and possesses other functions, including weed removal, pesticide spraying to control pests, scientific maintenance of chili pepper fields, and ensuring chili pepper quality. It features: 1. Automatic Sensing and Navigation: Utilizing advanced sensing technology, it can identify the location of chili peppers and weeds. Equipped with a navigation and positioning system, it ensures the machine can accurately move to the target chili pepper plants. 2. Precise Identification and Positioning: Utilizing visual recognition technology, it can accurately identify chili pepper varieties and quality, pests, and weeds near the chili pepper plants. It has a precise positioning system to ensure that damage to plants or fruits is avoided during harvesting and weeding. 3. High-Efficiency Harvesting and Weeding Robotic Arm: Designed with a high-efficiency, multi-degree-of-freedom robotic arm, it can quickly and accurately harvest chili peppers and remove weeds. The robotic claw uses flexible materials and a design to avoid damage to the plants. 4. Adjustable Harvesting Force: Features adjustable harvesting force to accommodate different varieties and maturity levels of chili peppers. Through an intelligent control system, the force is adjusted rationally based on the characteristics of the chili peppers, maximizing fruit integrity. Further adjustments are made when weeding to ensure thorough removal. 5. Intelligent Pesticide Spraying and Pest Control: The pesticide spraying device 3, based on information from the data processing unit 8, will apply corresponding pesticides to different types of pests or weeds. It will also adjust the pesticide dosage according to the severity of the infestation, achieving resource conservation and environmentally friendly practices. The pest control device adjusts its suction power according to the pest situation to capture different types of pests. Furthermore, the suction method for pest control achieves green and efficient results. 6. Data Recording and Analysis: Equipped with a data recording function, it records relevant information for each harvest, such as variety, quantity, and quality. Data analysis tools are provided to help farmers better understand yield and plant status for decision-making and optimized planting management. 7. Saves time and labor: Automated operation reduces the physical labor burden on farmers and improves production efficiency. The machine integrates the harvesting and sorting of peppers and field maintenance. Utilizing intelligent technology minimizes human intervention, making the pepper harvesting process more efficient and economical, and the spraying of pesticides and other maintenance processes more labor-saving and safer.

[0076] This invention discloses a chili pepper variety and quality identification, agricultural pest control, and harvesting route planning system, comprising: an image acquisition module for acquiring chili pepper location information, chili pepper shape information, chili pepper size information, obstacle information, pest information, and weed information; a chili pepper positioning module for receiving the chili pepper location information, chili pepper shape information, chili pepper size information, obstacle information, pest information, and weed information from the image acquisition module, and obtaining the spatial location of mature chili peppers to be harvested, pests, and nearby weeds; an obstacle detection module for receiving obstacle information from the image acquisition module, performing image analysis, detecting obstacles encountered during chili pepper harvesting, and obtaining analyzed obstacle information; and a harvesting route planning module for receiving the chili pepper spatial location information from the chili pepper positioning module and the analyzed obstacle information obtained from the obstacle detection module. The system receives information on obstacles and plans a chili pepper harvesting route. A data processing module receives chili pepper location, shape, and size information, as well as obstacle, pest, and weed information from the image acquisition module, spatial location information from the chili pepper positioning module, obstacle information analyzed by the obstacle detection module, and the chili pepper harvesting route from the harvesting route planning module. This data is then processed to obtain a harvesting execution program, a pest capture program, and a pesticide spraying program. A control system receives and executes these programs. The chili pepper harvesting module harvests chili peppers according to the control system's harvesting execution program. The pest capture module captures pests according to the control system's pest capture program. The pesticide spraying module sprays pesticides according to the control system's pesticide spraying program.

[0077] The chili pepper variety quality identification, agricultural pest control, and harvesting route planning system disclosed in this invention has the following advantages: 1. Improved harvesting efficiency: It can simultaneously complete the harvesting and quality classification of chili peppers, saving a lot of manpower and resources; 2. Guaranteed chili pepper quality: It can remove weeds and pests from chili pepper trees, spray pesticides to reduce pests and diseases, and scientifically maintain chili pepper fields, thereby improving the quality of chili peppers; 3. Reduced labor intensity: It can automate the harvesting and classification process and maintain chili pepper fields, greatly reducing labor intensity.

[0078] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

[0079] The technical solution proposed in this application is intended to participate in the 11th National Undergraduate Mechanical Innovation Design Competition.

Claims

1. A method for identifying chili pepper varieties and quality, implementing agricultural pest control, and planning harvesting routes, characterized in that... include: Obtain information on chili pepper location, shape, size, obstacles, pests, and weeds; Based on the location information, shape information, size information, pest information, and weed information of the chili peppers, we can obtain the spatial location information of the mature chili peppers that need to be harvested, the pests, and the nearby weeds. The system detects obstacles encountered during chili pepper harvesting and performs image analysis to obtain obstacle information. Based on the spatial location information of the chili peppers to be harvested, pests, and nearby weeds, as well as the analyzed obstacle information, the route for harvesting chili peppers and clearing weeds is planned. Weeds are removed sequentially, and obstacles are bypassed to reach the target chili peppers for harvesting. After the chili peppers are harvested, if the weed density per unit area along the harvesting path is lower than the system-set threshold, weeding is performed; if the weed density is higher than the system-set threshold, weeding is not performed, and pesticides are sprayed on the area. If the pest density on the chili pepper trees is lower than the system-set threshold, the pests are sucked into a capture bag using a vacuum tube; if the pest density on the chili pepper trees is higher than the system-set threshold, pesticides are sprayed on the chili pepper trees. By processing the spatial location information of chili peppers and analyzing the obstacle information, a harvesting execution program, a pest capture program, and a pesticide spraying program are obtained. The harvesting, pest control, and pesticide spraying procedures were followed to complete the harvesting of chili peppers, weed control, pest capture, and pesticide spraying.

2. The method for chili pepper variety quality identification, agricultural pest control, and harvesting route planning according to claim 1, characterized in that, The acquisition of chili pepper location information, chili pepper shape information, chili pepper size information, obstacle information, pest information, and weed information specifically includes: The NVIDIA Jetson Nano development board (7) is used to identify the types of chili peppers, the quality of chili peppers, pests on chili peppers and weeds near chili pepper trees, and obtain the corresponding image information. The identified image information is then processed by computer vision algorithms for image preprocessing, feature extraction, feature matching, classification and recognition, threshold determination and recognition.

3. The method for chili pepper variety quality identification, agricultural pest control, and harvesting route planning according to claim 2, characterized in that, The NVIDIA Jetson Nano development board (7) includes a high-definition image acquisition system, an information feedback system, a chili target recognition system, a chili variety quality analysis system, a pest and weed recognition system, and a deep learning model. The high-definition image acquisition system is used to acquire high-definition images of chili peppers and objects around them, and transmits the high-definition image information of chili peppers and objects around them to the chili pepper target recognition system, the chili pepper variety quality analysis system, and the pest and weed recognition system through the information feedback system. The chili pepper target recognition system, the chili pepper variety quality analysis system, and the pest and weed recognition system use deep learning models to identify the appearance of chili peppers, pests, and weeds.

4. The method for chili pepper variety quality identification, agricultural pest control, and harvesting route planning according to claim 1, characterized in that, The process of obtaining spatial location information of mature chilies, pests, and nearby weeds based on chili location information, chili shape information, chili size information, pest information, and weed information specifically includes: By combining an image recognition device, an image analysis system, a photosensitive sensor, a light emitter, an ultrasonic positioning system, a dynamic positioning system, a real-time data transmission unit, and an automatic correction function unit, the spatial location information of mature peppers that need to be harvested, pests, and nearby weeds can be obtained. The image analysis system converts the information transmitted by the image recognition device into a two-dimensional planar image through sensors for processing and analysis. A photosensitive sensor is used to measure the light conditions in the chili-picking environment, generate a light signal, and transmit it to a light emitter. Ultrasonic positioning systems are used to determine the spatial location of chili peppers; The dynamic positioning system is used to obtain the precise location information of the chili harvester in the field; The real-time data transmission unit transmits the collected location information to the control unit; The automatic correction function unit detects errors or uncertainties and adjusts or repositions the device accordingly.

5. The method for chili pepper variety quality identification, agricultural pest control, and harvesting route planning according to claim 1, characterized in that, The process of detecting obstacles encountered during chili pepper harvesting and performing image analysis to obtain obstacle information is as follows: The analyzed obstacle information is obtained by combining lidar, optical receiver, obstacle information extraction and output system and information feedback system. The laser transmitter converts electrical pulses into light pulses and sends detection signals along the harvesting route. After the light receiver receives the signal reflected back from the obstacle, it restores the light pulse reflected back from the obstacle into an electrical pulse and sends it to the display. The information processing system then processes the electrical pulses of the obstacle in the display into data information about the distance, orientation, attitude and shape of the obstacle and displays it on the display. The obstacle information extraction and output system extracts the information displayed by the lidar and outputs it to the information feedback system; the information feedback system then feeds back information about the distance, orientation, attitude and shape of the obstacle to the data processing unit.

6. The method for chili pepper variety quality identification, agricultural pest control, and harvesting route planning according to claim 1, characterized in that, When pesticides are sprayed, the corresponding pesticides are formulated based on the information transmitted by the data processing unit for different types of pests or weeds, and the dosage of pesticides is adjusted according to the severity of the pests.

7. The method for chili pepper variety quality identification, agricultural pest control, and harvesting route planning according to claim 1, characterized in that, When catching pests, the suction force is adjusted according to the pest situation to catch different types of pests.

8. A system for identifying chili pepper varieties and quality, implementing agricultural pest control, and planning harvesting routes, characterized in that: The method for chili pepper variety quality identification, agricultural pest control, and harvesting route planning based on any one of claims 1-7 includes: The image acquisition module is used to acquire information such as the location, shape, and size of the chili peppers, as well as information about obstacles, pests, and weeds. The chili pepper positioning module is used to receive chili pepper location information, chili pepper shape information, chili pepper size information, obstacle information, pest information, and weed information from the image acquisition module, and obtain the spatial location of mature chili peppers that need to be harvested, pests, and nearby weeds. The obstacle detection module is used to receive obstacle information from the image acquisition module, perform image analysis, detect obstacles encountered during the chili picking process, and obtain the analyzed obstacle information. The harvesting route planning module receives the spatial location information of the chili peppers from the chili pepper positioning module and the analyzed obstacle information obtained from the obstacle detection module, and plans the chili pepper harvesting route. The data processing module is used to receive chili pepper location information, chili pepper shape information, chili pepper size information, obstacle information, pest information and weed information obtained by the image acquisition module, chili pepper spatial location information from the chili pepper positioning module, obstacle information after analysis from the obstacle detection module, and chili pepper harvesting route from the harvesting route planning module, and to process them to obtain the harvesting execution program, pest capture program and pesticide spraying program. The control system is used to receive and execute the harvesting program, pest capture program, and pesticide spraying program transmitted by the data processing module. The chili harvesting module harvests chilies according to the harvesting execution program of the control system; The pest-catching module catches pests according to the pest-catching program of the control system. The pesticide spraying module sprays pesticides according to the pesticide spraying program of the control system.

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