Collaborative Control Method for Material Receiving Robots Based on Mushroom Harvesting Collaboration

Abstract

The present invention relates to the field of agricultural automation technology, and particularly relates to a collaborative control method for a material collection robot based on mushroom harvesting collaboration, including the following steps: S1: Use a suction cup to pick mushrooms and convey the mushrooms to the discharge port through a built-in conveying device; S2: Dynamically adjust the moving route of the picking robot; S3: The material collection mechanism moves synchronously with the picking robot to ensure that the material collection mechanism is aligned with the discharge port; S4: Separate the mushrooms that meet the quality standards from the unqualified mushrooms through a shunting device, and they enter the first hopper and the second hopper respectively; S5: Perform secondary grading on the mushrooms entering the first hopper, and classify the mushrooms by size based on volume and diameter parameters; S6: When any hopper is close to full load, trigger the replacement operation of the material collection mechanism. With the present invention, through intelligent path planning, real-time monitoring and grading control, efficient harvesting, precise classification and automated continuous operation during the mushroom picking process are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural automation, and in particular to a collaborative control method of a material collecting robot based on collaborative mushroom harvesting. Background Art

[0002] With the development of agricultural automation and intelligence, the harvesting of crops such as mushrooms is gradually transforming towards automation. The traditional manual picking method is inefficient, not only consuming a lot of labor, but also easily causing mechanical damage to the mushrooms, affecting product quality and market value. For this reason, picking robots have been introduced into the field of mushroom picking to achieve the initial application of automatic picking. However, the existing picking robot systems still have major deficiencies in the classification, quality inspection, and size grading of mushrooms, and cannot meet the needs of modern agricultural production for efficient and accurate classification and picking. Especially in the process of mushroom harvesting, the coordination and synchronization between the collecting mechanism and the picking robot, the intelligent processing of mushroom grading standards and quality inspection are still important challenges facing current technology.

[0003] In the existing technology, picking robots often lack real-time and accurate detection of mushroom maturity, appearance and volume, resulting in a high loss rate during the picking process. At the same time, in the harvesting operation, how to ensure the synchronization and coordination of the material collection mechanism and the picking robot to avoid the decline in efficiency caused by load imbalance or interruption during the harvesting process has not yet been fully solved. In addition, the mushroom grading process relies too much on manual or simple mechanical means and lacks accurate algorithm support, resulting in inaccurate classification. Therefore, it is of great practical significance and necessity to develop an intelligent mushroom harvesting collaborative control method that can solve these technical problems and improve harvesting efficiency and classification accuracy. Summary of the invention

[0004] Based on the above objectives, the present invention provides a collaborative control method of a material collecting robot based on mushroom harvesting collaboration.

[0005] The collaborative control method of a collecting robot based on mushroom harvesting collaboration includes the following steps:

[0006] S1: The picking robot moves along the cultivation rack, uses a suction cup to pick mushrooms, and transports the mushrooms to the discharge port through a built-in conveying device;

[0007] S2: Based on the distribution status and maturity data of mushrooms, a path planning algorithm is used to dynamically adjust the movement route of the picking robot, and the picking path is optimized based on the real-time location and mushroom density;

[0008] S3: The receiving mechanism moves synchronously with the picking robot and is associated with the path planning algorithm to ensure that the receiving mechanism is aligned with the discharge port and receives the mushrooms delivered by the picking robot;

[0009] S4: The appearance, color and shape of the mushrooms are detected by an image recognition device installed in the material receiving mechanism based on a preset quality recognition algorithm, and the mushrooms that meet the quality standards are separated from the unqualified mushrooms through a diversion device and enter the first drop hopper and the second drop hopper respectively;

[0010] S5: performing secondary classification on the mushrooms entering the first hopper, classifying the mushrooms by size based on volume and diameter parameters, and directing the larger mushrooms to the third hopper and the smaller mushrooms to the fourth hopper by the diversion device;

[0011] S6: When any drop hopper is close to full load, a full load signal will be issued to trigger the replacement operation of the receiving mechanism and start the standby receiving mechanism to ensure continuous harvesting operation.

[0012] Optionally, the S1 specifically includes:

[0013] S11: When the picking robot moves along the track of the cultivation rack, the picking robot is controlled to move forward and backward by a set driving motor, and the driving motor cooperates with the guide rail on the cultivation rack to achieve a stable moving process. The guide rail has a positioning device to ensure that the picking robot can be accurately positioned above the position of the mushrooms;

[0014] S12: The picking robot picks mushrooms through the suction cup installed on the mechanical arm. The mechanical arm extends vertically according to the preset picking height parameters. The suction cup is connected to the pneumatic system, and the mature mushrooms are separated from the fungus body and stably grasped through the negative pressure adsorption principle;

[0015] S13: The picking robot conveys the mushrooms caught by the suction cup from the suction cup end to the discharge port inside the robot through the built-in conveyor belt.

[0016] Optionally, the S2 specifically includes:

[0017] S21: Obtain the distribution and maturity information of mushrooms in the target area through the visual sensor deployed on the picking robot. The sensor is used to scan the growth position and size of the mushrooms in real time and generate relevant data;

[0018] S22: Based on the collected mushroom distribution and maturity data, a path planning algorithm is executed to determine the optimal moving route by analyzing mushroom information such as the current spatial position of the picking robot, mushroom density, mushroom cap shading, mushroom height and maturity, and to select a path that can complete lossless picking in the shortest time, avoiding picking areas of immature mushrooms;

[0019] S23: The picking robot automatically adjusts the moving route and speed according to the calculated path. During the movement, the real-time position of the picking robot is continuously obtained, and the route is dynamically adjusted according to the mushroom information in the picking area and the newly collected data to optimize the path and avoid repeated picking and omission.

[0020] S24: When the picking robot approaches the target area, the real-time feedback information is used to fine-tune its moving position to ensure that the optimal picking distance is reached when approaching the target mushrooms, so as to achieve precise picking operations.

[0021] Optionally, the S22 specifically includes:

[0022] S221: Acquire spatial distribution information of mushrooms, including the three-dimensional coordinate position and maturity of each mushroom, and record the current position of the picking robot to clarify the relative position of the mushrooms and the picking robot;

[0023] S222: based on the relative distance between the current position of the picking robot and each mushroom, calculating the moving distance of the robot to each mushroom, and sorting the mushrooms by distance, giving priority to mushrooms with a closer distance;

[0024] S223: Considering the maturity of the mushrooms at the same time, a weight value is assigned to each mushroom by combining the maturity and the moving distance. Mushrooms with high maturity and close distance are given higher priority. ;

[0025] S224: Considering both the mushroom cap shielding and the mushroom height, the weights of the mushroom cap shielding and the mushroom height are combined with the classification of maturity and moving distance. Combined with high maturity, close distance, high altitude, and unobstructed mushrooms, high priority is given. ;

[0026] S225: Use the greedy algorithm to select the weight value The largest mushroom is selected as the picking target. After the picking robot moves to the mushroom position, it updates the current position and continues to select the next mushroom with a high priority. The process is repeated until all mushrooms that meet the maturity requirements are picked.

[0027] S226: The entire picking path is planned according to the principle of minimizing the total moving distance, ensuring that the picking robot can complete the picking operation of all target mushrooms in sequence along the shortest path.

[0028] Optionally, the S24 specifically includes:

[0029] S241: When the picking robot approaches the target mushroom area, the relative distance between the picking robot and the target mushroom is first obtained through the real-time position sensor, and the lateral and longitudinal position deviations between the current position of the robot and the target mushroom are recorded;

[0030] S242: Based on the acquired position deviation information, the proportional-integral-differential control algorithm is used to perform position fine-tuning, and the moving speed and direction of the robot are dynamically adjusted according to the distance error to ensure that the robot gradually approaches the target mushroom;

[0031] S243: When the distance error between the robot and the target mushroom is reduced to within a preset range, that is, when the optimal picking distance is reached, the PID controller will reduce the moving speed and maintain a stable position accuracy to ensure that the suction cup is accurately aligned with the mushroom for picking.

[0032] Optionally, the S3 specifically includes:

[0033] S31: When the picking robot is started, the real-time position information of the picking robot is first obtained, including its current coordinates and moving speed on the cultivation rack, and transmitted to the material receiving mechanism;

[0034] S32: The material receiving mechanism adjusts its own moving route according to the position information provided by the picking robot using a synchronous tracking algorithm to ensure that the material receiving mechanism and the picking robot maintain a consistent speed and moving direction;

[0035] S33: Continuously monitor the relative position of the receiving mechanism and the material outlet of the picking robot. When a deviation is detected, the moving speed and direction of the receiving mechanism will be automatically adjusted until the deviation between the receiving mechanism and the material outlet is reduced to a preset range, ensuring seamless connection between the material outlet and the receiving area.

[0036] Optionally, the S4 specifically includes:

[0037] S41: collecting the appearance image of each mushroom after picking through an image recognition device, the image recognition device includes a high-definition camera and a light source system, the camera captures the appearance, color and morphological characteristics of the mushrooms and generates corresponding digital image data, and the light source system ensures stable image quality;

[0038] S42: inputting the collected mushroom image data into a preset quality recognition algorithm, and comparing it with the qualified mushroom templates in the quality standard library to determine whether the mushrooms meet the preset standards;

[0039] S43: classifying the mushrooms into qualified mushrooms and unqualified mushrooms according to the test results in S42, wherein the qualified mushrooms have appearance, color and morphological characteristics that meet the set standards, and the unqualified mushrooms have obvious differences or defects from the template;

[0040] S44: After the detection result is transmitted to the central control system, the diversion device is started according to the judgment result. The diversion device controls two flow channels in different directions through an actuator to guide qualified mushrooms to the first drop hopper, while unqualified mushrooms enter the second drop hopper through another flow channel.

[0041] Optionally, the S42 specifically includes:

[0042] S421: Preprocessing the mushroom image collected by the image recognition device, the preprocessing includes removing noise, adjusting color balance, and enhancing edge details; after the image processing, extracting color information and brightness information of each pixel, including three colors of red, green, and blue;

[0043] S422: extracting feature information of the mushrooms from the preprocessed image through a convolutional neural network, the feature information including color and morphological parameters of the mushrooms, wherein the color information is obtained by analyzing a color histogram, including focusing on the color distribution of three color channels: red, green, and blue; the morphological parameters are extracted through edge detection and contour analysis, and are used to reflect the symmetry, shape, and surface characteristics of the mushrooms;

[0044] S423: comparing the extracted mushroom characteristic information with a preset qualified mushroom template in the quality standard library, where the template also includes the color and morphological characteristics of the standard mushrooms; by calculating the difference between the mushrooms and the template, evaluating the degree of matching between the appearance, color and morphology of the mushrooms and the qualified standards;

[0045] S424: According to the comparison result, whether the mushrooms meet the preset quality standards is determined according to the difference between the mushrooms and the qualified template; if the characteristic difference of the mushrooms is within the preset tolerance range, the mushrooms are judged to be qualified; if it exceeds the range, they are judged to be unqualified.

[0046] Optionally, the S5 specifically includes:

[0047] S51: In the first hopper, the volume and diameter parameters of each mushroom are measured by an image recognition device;

[0048] S52: Compare the volume parameter and the diameter parameter with the preset size classification standard respectively. The classification standard sets different volume and diameter thresholds based on the type and specification of the mushroom. If the volume and diameter of the mushroom exceed the preset threshold at the same time, it is judged as a large mushroom; if it is lower than the threshold, it is judged as a small mushroom.

[0049] S53: According to the classification result, large mushrooms are directed to the third drop hopper; at the same time, according to the determination result, small mushrooms are directed to the fourth drop hopper to avoid mixing of mushrooms of different sizes.

[0050] Optionally, the S6 specifically includes:

[0051] S61: A load sensor is installed in each hopper to monitor the current load of the hopper in real time; the load sensor transmits the measured current weight data W to the central control system, where W is the actual weight in the hopper;

[0052] S62: The central control system is based on the preset full load threshold , continuously monitor the current weight W; when the current weight W measured by the sensor is close to or equal to the full load threshold , that is, satisfy When the conditions are met, the system automatically sends a full load signal;

[0053] S63: After the full load signal is transmitted to the central control system, the standby material receiving mechanism is triggered to start; the standby material receiving mechanism is in standby state in advance. After the full load signal is issued, the central control system sends a command to the actuator, and the actuator switches the material receiving path to ensure that the standby material receiving mechanism takes over the existing material receiving hopper and continues the material receiving operation.

[0054] Beneficial effects of the present invention:

[0055] The present invention solves the problem of lack of accurate detection and synchronous control of picking robots in the mushroom picking process in the prior art by introducing path planning algorithms, real-time feedback control and intelligent grading systems. By real-time monitoring of the growth status, volume and diameter parameters of mushrooms, combined with intelligent grading algorithms, the maturity, size and quality of mushrooms can be accurately judged, and automatic classification and processing of different types of mushrooms can be achieved. The system also ensures seamless connection between the material collection process and the picking process through the synchronous operation of the material collection mechanism and the picking robot, avoiding interruptions and greatly improving the picking efficiency.

[0056] The present invention sends a signal when the hopper is close to being fully loaded, automatically switches to a standby material receiving mechanism, and ensures the continuous progress of the harvesting operation. Compared with the traditional manual picking or simple mechanical sorting method, it not only significantly reduces the damage rate of mushrooms, but also improves the accuracy of classification, and enhances the intelligence level of the entire picking process. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0058] Figure 1 Schematic diagram of a collaborative control method of a material receiving robot according to an embodiment of the present invention;

[0059] Figure 2The figure is a flow chart of a path planning algorithm used in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0061] like Figure 1-Figure 2 As shown, the collaborative control method of the collecting robot based on mushroom harvesting collaboration includes the following steps:

[0062] S1: The picking robot moves along the cultivation rack, uses a suction cup to pick mushrooms, and transports the mushrooms to the discharge port through a built-in conveying device;

[0063] S2: Based on the distribution status and maturity data of mushrooms, a path planning algorithm is used to dynamically adjust the movement route of the picking robot, and the picking path is optimized based on the real-time location and mushroom density;

[0064] S3: The receiving mechanism moves synchronously with the picking robot and is associated with the path planning algorithm to ensure that the receiving mechanism is aligned with the discharge port and receives the mushrooms delivered by the picking robot;

[0065] S4: The appearance, color and shape of the mushrooms are detected by an image recognition device installed in the material receiving mechanism based on a preset quality recognition algorithm, and the mushrooms that meet the quality standards are separated from the unqualified mushrooms through a diversion device and enter the first drop hopper and the second drop hopper respectively;

[0066] S5: performing secondary classification on the mushrooms entering the first hopper, classifying the mushrooms by size based on volume and diameter parameters, and directing the larger mushrooms to the third hopper and the smaller mushrooms to the fourth hopper by the diversion device;

[0067] S6: When any drop hopper is close to full load, a full load signal will be issued to trigger the replacement operation of the receiving mechanism and start the standby receiving mechanism to ensure continuous harvesting operation.

[0068] S1 specifically includes:

[0069] S11: When the picking robot moves along the track of the cultivation rack, the picking robot is controlled to move forward and backward by a set driving motor, and the driving motor cooperates with the guide rail on the cultivation rack to achieve a stable moving process. The guide rail has a positioning device to ensure that the picking robot can be accurately positioned above the position of the mushrooms;

[0070] S12: The picking robot picks mushrooms through the suction cup installed on the mechanical arm. The mechanical arm extends vertically according to the preset picking height parameters. The suction cup is connected to the pneumatic system, and the mature mushrooms are separated from the fungus body and stably grasped through the negative pressure adsorption principle;

[0071] S13: The picking robot transports the mushrooms caught by the suction cup from the suction cup end to the discharge port inside the robot through the built-in conveyor belt. The conveyor belt has an adjustable speed control device to ensure that the mushrooms are not damaged during the transmission process. At the same time, the end of the conveyor belt is seamlessly connected with the discharge port to achieve smooth output of the mushrooms. Through the coordinated work of the specific movement control, suction cup picking and conveying devices in the above steps, the picking robot can be accurately positioned, the mushrooms can be effectively picked and the mushrooms can be safely transported, ensuring the efficient harvesting and low damage rate of the mushrooms, and improving the picking efficiency and quality.

[0072] S2 specifically includes:

[0073] S21: Obtain the distribution and maturity information of mushrooms in the target area through the visual sensor deployed on the picking robot. The sensor is used to scan the growth position and size of the mushrooms in real time and generate relevant data;

[0074] S22: Based on the collected mushroom distribution and maturity data, a path planning algorithm is executed to determine the optimal moving route by analyzing mushroom information such as the current spatial position of the picking robot, mushroom density, mushroom cap shading, mushroom height and maturity, and to select a path that can complete lossless picking in the shortest time, avoiding picking areas of immature mushrooms;

[0075] S23: The picking robot automatically adjusts the moving route and speed according to the calculated path. During the movement, the real-time position of the picking robot is continuously obtained, and the route is dynamically adjusted according to the mushroom information in the picking area and the newly collected data to optimize the path and avoid repeated picking and omission.

[0076] S24: When the picking robot approaches the target area, the real-time feedback information is used to fine-tune its moving position to ensure that the optimal picking distance is reached when approaching the target mushrooms, so as to achieve accurate picking operations; the above steps realize the efficient picking path planning of the picking robot in different picking areas through the real-time acquisition of mushroom distribution and maturity data and the dynamic adjustment of the path planning algorithm, thereby improving the picking efficiency and accuracy, avoiding duplication and omission, and improving the overall operation efficiency.

[0077] S22 specifically includes:

[0078] S221: Acquire spatial distribution information of mushrooms, including the three-dimensional coordinate position and maturity of each mushroom, and record the current position of the picking robot. These data are used to build a model of the picking area and clarify the relative position of the mushrooms and the picking robot.

[0079] S222: based on the relative distance between the current position of the picking robot and each mushroom, calculating the moving distance of the robot to each mushroom, and sorting the mushrooms by distance, giving priority to mushrooms with a closer distance;

[0080] S223: Considering the maturity of the mushrooms at the same time, a weight value is assigned to each mushroom by combining the maturity and the moving distance. Mushrooms with high maturity and close distance are given higher priority. ;

[0081] S224: Considering both the mushroom cap shielding and the mushroom height, the weights of the mushroom cap shielding and the mushroom height are combined with the classification of maturity and moving distance. Combined with high maturity, close distance, high altitude, and unobstructed mushrooms, high priority is given. ;

[0082] S225: Use the greedy algorithm to select the weight value The largest mushroom is selected as the picking target. After the picking robot moves to the mushroom position, it updates the current position and continues to select the next mushroom with a high priority. The process is repeated until all mushrooms that meet the maturity requirements are picked.

[0083] S226: The entire picking path is planned according to the principle of minimizing the total moving distance, ensuring that the picking robot can complete the picking operation of all target mushrooms in sequence along the shortest path.

[0084] The specific calculation steps of the path planning algorithm are as follows:

[0085] First, obtain the spatial distribution information of all mushrooms in the target area and collect the three-dimensional coordinate position of each mushroom ,in is the coordinate of mushroom i on the surface, is the coordinate of mushroom i in the longitudinal direction, is the coordinate of mushroom i in the depth direction, and records the maturity of each mushroom , represents the maturity level of mushroom i; at the same time, the coordinates of the current position of the picking robot are set to ,in , and are the coordinates of the picking robot in the horizontal, vertical and depth directions respectively;

[0086] Then, the path planning algorithm calculates the Euclidean distance between the current position of the picking robot and the target mushroom i , and its calculation formula is: ,in, is the distance between mushroom i and the current position of the picking robot, is the coordinate of mushroom i, is the coordinate of the picking robot, distance Used to determine the relative distance between the mushroom and the robot; and distance , assign weight values ​​to each mushroom , and its calculation formula is: ,in, represents the weight value of mushroom i, is the maturity of mushroom i, is the distance between mushroom i and the picking robot. The weight value is used to comprehensively measure the maturity of the mushroom and the picking cost (i.e., distance). The larger the weight value, the priority is given to picking the mushroom. The largest mushroom is selected as the next picking target, and the current position of the picking robot is updated as the new coordinates. ,in , and The updated coordinates of the picking robot; based on the new robot position, the Euclidean distance between it and the remaining mushrooms is recalculated, and the iterative selection continues until all mushrooms that meet the maturity standards are picked;

[0087] Assume the total path length is L, and its calculation formula is:

[0088] , where L represents the total moving distance of the picking robot, n is the total number of mushrooms in the target area, and is the coordinate of mushroom i, and is the coordinate of the current position of the picking robot. The path planning algorithm aims to minimize the total path length to ensure that the picking robot completes the picking of all mushrooms that meet the standards in the shortest time. The above steps achieve precise optimization of the picking path by introducing a combination of Euclidean distance calculation, weight allocation and greedy algorithm. It can not only plan the picking according to the maturity and distance priority of the mushrooms, but also reduce the movement time through the shortest path algorithm, thereby significantly improving the picking efficiency.

[0089] S24 specifically includes:

[0090] S241: When the picking robot approaches the target mushroom area, the relative distance between the picking robot and the target mushroom is first obtained through the real-time position sensor, and the lateral and longitudinal position deviations between the current position of the robot and the target mushroom are recorded, which are expressed as ; ; ,in , and are the coordinates of the mushroom, , and is the current three-dimensional coordinate position of the robot;

[0091] S242: Based on the acquired position deviation information, the proportional-integral-derivative (PID) control algorithm is used to fine-tune the position. The PID algorithm adjusts the robot movement through the following formula: ,in, is the distance error between the robot’s current position and the target mushroom, is the proportionality coefficient, is the integration coefficient, is the differential coefficient. The PID controller dynamically adjusts the robot's moving speed and direction according to the distance error to ensure that the robot gradually approaches the target mushroom.

[0092] S243: When the distance error between the robot and the target mushroom is reduced to within a preset range, that is, when the optimal picking distance is reached, the PID controller will further reduce the moving speed, maintain a stable position accuracy, and ensure that the suction cup is accurately aligned with the mushroom for picking; the above steps can achieve precise position adjustment of the picking robot when approaching the target mushroom through the PID control algorithm and real-time position information feedback, ensuring that the robot reaches the optimal picking distance. This process improves the positioning accuracy by automatically adjusting the moving speed and direction, ensuring the accuracy and stability of the picking operation.

[0093] S3 specifically includes:

[0094] S31: When the picking robot is started, the real-time position information of the picking robot is first obtained, including its current coordinates and moving speed on the cultivation rack, and transmitted to the material receiving mechanism;

[0095] S32: The receiving mechanism adjusts its own moving route according to the position information provided by the picking robot using the synchronous tracking algorithm to ensure that the receiving mechanism and the picking robot maintain the same speed and moving direction. The synchronous tracking algorithm is used to calculate the relative distance between the picking robot and the receiving mechanism. The calculation formula is:

[0096] ,in For the picking robot position, is the position of the receiving mechanism, Used to determine the spatial deviation between the receiving mechanism and the robot;

[0097] S33: In order to ensure the precise alignment of the receiving mechanism and the discharging port of the picking robot, the system continuously monitors the relative position of the receiving mechanism and the discharging port of the picking robot through position feedback control. When a deviation is detected, the moving speed and direction of the receiving mechanism will be automatically adjusted until the deviation between the receiving mechanism and the discharging port is reduced to within a preset range, thereby ensuring seamless connection between the discharging port and the receiving area. The above steps use the synchronous tracking algorithm and position feedback control technology, so that the receiving mechanism can maintain precise synchronous movement with the picking robot, ensuring accurate alignment of the receiving mechanism and the discharging port. This process dynamically adjusts the position and speed of the receiving mechanism through real-time data feedback, thereby ensuring the efficiency and accuracy of receiving materials during mushroom picking and reducing errors and losses.

[0098] S4 specifically includes:

[0099] S41: collecting the appearance image of each mushroom after picking through an image recognition device, the image recognition device includes a high-definition camera and a light source system, the camera captures the appearance, color and morphological characteristics of the mushrooms and generates corresponding digital image data, and the light source system ensures stable image quality;

[0100] S42: inputting the collected mushroom image data into a preset quality recognition algorithm, and comparing the data with qualified mushroom templates in the quality standard library to determine whether the mushrooms meet the preset standards. The parameters involved in the algorithm include color saturation, surface finish, and symmetry of mushroom morphology.

[0101] S43: classifying the mushrooms into qualified mushrooms and unqualified mushrooms according to the test results in S42, wherein the qualified mushrooms have appearance, color and morphological characteristics that meet the set standards, and the unqualified mushrooms have obvious differences or defects from the template;

[0102] S44: After the detection results are transmitted to the central control system, the diversion device is started according to the judgment results. The diversion device controls two flow channels in different directions through the actuator to guide qualified mushrooms to the first drop hopper, while unqualified mushrooms enter the second drop hopper through another flow channel. The diversion process relies on the electrically controlled mechanical separation plate to ensure that each type of mushroom enters the designated drop hopper separately; the above steps can efficiently and accurately detect the appearance, color and morphological characteristics of mushrooms through the quality recognition algorithm of the deep learning model, and separate qualified and unqualified mushrooms in real time. Combined with the electrically controlled diversion device, the automation and high precision of the mushroom separation process are ensured, human intervention and judgment errors are reduced, and the sorting efficiency and accuracy are improved.

[0103] S42 specifically includes:

[0104] S421: Preprocessing the mushroom image collected by the image recognition device, the preprocessing includes removing noise, adjusting color balance, and enhancing edge details to ensure the clarity and accuracy of the image; after the image processing, extracting the color information and brightness information of each pixel, including the three colors of red, green, and blue;

[0105] S422: extracting feature information of the mushrooms from the preprocessed image through a convolutional neural network, the feature information including color and morphological parameters of the mushrooms, wherein the color information is obtained by analyzing a color histogram, including focusing on the color distribution of three color channels: red, green, and blue; the morphological parameters are extracted through edge detection and contour analysis, and are used to reflect the symmetry, shape, and surface characteristics of the mushrooms;

[0106] S423: comparing the extracted mushroom characteristic information with a preset qualified mushroom template in the quality standard library, where the template also includes the color and morphological characteristics of the standard mushrooms; by calculating the difference between the mushrooms and the template, evaluating the degree of matching between the appearance, color and morphology of the mushrooms and the qualified standards;

[0107] S424: According to the comparison result, whether the mushrooms meet the preset quality standards is determined according to the difference between the mushrooms and the qualified template; if the characteristic difference of the mushrooms is within the preset tolerance range, the mushrooms are judged to be qualified; if it exceeds the range, they are judged to be unqualified.

[0108] The specific calculation steps of S42 are as follows:

[0109] First, the mushroom image data obtained by the image recognition device is preprocessed. After preprocessing, the image is converted into a two-dimensional pixel matrix. Each pixel contains color and brightness information, and is separated and analyzed according to the values ​​of the three channels R (red), G (green), and B (blue);

[0110] Then, the processed image is subjected to feature extraction. The algorithm uses a convolutional neural network to extract the appearance, color, and morphological features of the mushrooms. The feature vector is set as Represents the characteristics of mushroom i, including color value and morphological parameters ;but , color value Through color histogram analysis, including the intensity distribution of the three color channels of red, green and blue, and the morphological parameters Extract the symmetry and shape of mushrooms through edge detection and contour analysis;

[0111] Next, the extracted feature vector Qualified mushroom templates in the quality standard library For comparison, Represents the jth qualified mushroom template in the quality standard library; template Also contains color and shape feature vectors ; When comparing, the Euclidean distance formula is used to calculate the difference between the characteristics of mushroom i and qualified template j: ,in, represents the Euclidean distance between mushroom i and template j, and are the kth feature components of mushroom i and template j respectively, Represents the total number of dimensions used to compare mushroom features, that is, the number of features contained in the feature vector;

[0112] S424: Based on the European distance size to determine whether the mushrooms meet the quality standards; if the distance between a mushroom and the template is less than the preset threshold ,Right now , then the mushroom is judged as qualified mushroom; otherwise, it is judged as unqualified mushroom; the threshold Preset by the quality standard library, adjusted according to different mushroom types and specifications; the above steps use convolutional neural networks to extract image features, and combine Euclidean distance to calculate the difference between mushrooms and qualified templates, which can achieve accurate comparison and judgment of the appearance, color and morphology of mushrooms. The algorithm can effectively distinguish between qualified and unqualified mushrooms, ensure the high precision of the recognition process, and improve the efficiency and accuracy of automated grading.

[0113] S5 specifically includes:

[0114] S51: In the first drop hopper, the volume and diameter parameters of each mushroom are measured by an image recognition device; the image recognition device includes a three-dimensional scanning system and image processing software, the three-dimensional scanning system is used to generate a three-dimensional model of the mushroom, and the volume of the mushroom is calculated according to the model, and the image processing software determines the maximum diameter of the mushroom by image edge detection technology;

[0115] S52: Compare the volume parameter and the diameter parameter with the preset size classification standard respectively. The classification standard sets different volume and diameter thresholds based on the type and specification of the mushroom. If the volume and diameter of the mushroom exceed the preset threshold at the same time, it is judged as a large mushroom; if it is lower than the threshold, it is judged as a small mushroom.

[0116] S53: According to the grading result, large mushrooms are directed to the third hopper; at the same time, according to the determination result, small mushrooms are directed to the fourth hopper; mushrooms of different sizes are avoided from being mixed; the volume and diameter of the mushrooms are accurately measured by the image recognition device, and the mushrooms are automatically classified by size according to the grading standard, ensuring that large and small mushrooms can be accurately separated, effectively improving the classification efficiency and reducing the risk of mushroom mixing.

[0117] S6 specifically includes:

[0118] S61: A load sensor is installed in each hopper to monitor the current load of the hopper in real time; the load sensor transmits the measured current weight data W to the central control system, where W is the actual weight in the hopper;

[0119] S62: The central control system is based on the preset full load threshold (This threshold is set according to the maximum capacity of the hopper) and continuously monitors the current weight W; when the current weight W measured by the sensor is close to or equal to the full load threshold , that is, satisfy When the conditions are met, the system automatically sends a full load signal;

[0120] S63: After the full-load signal is transmitted to the central control system, the standby material receiving mechanism is triggered to start; the standby material receiving mechanism is in standby state in advance. After the full-load signal is issued, the central control system sends a command to the actuator, and the actuator switches the material receiving path to ensure that the standby material receiving mechanism takes over the existing material receiving hopper and continues the material receiving operation; the originally fully loaded drop hopper is marked as fully loaded, isolated from the current operation, and the staff is instructed to empty and replace it. At this time, the standby material receiving mechanism has taken over all material receiving tasks to ensure that the entire harvesting operation is seamless and continuous.

[0121] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0122] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A collaborative control method for collecting materials based on mushroom harvesting collaboration, characterized in that: The following steps are involved: S1: The picking robot moves along the cultivation rack, uses a suction cup to pick mushrooms, and transports the mushrooms to the discharge port through a built-in conveying device; S2: Based on the distribution status and maturity data of mushrooms, a path planning algorithm is used to dynamically adjust the movement route of the picking robot, and the picking path is optimized based on the real-time location and mushroom density; The S2 specifically includes: S21: Obtain the distribution and maturity information of mushrooms in the target area through the visual sensor deployed on the picking robot. The sensor is used to scan the growth position and size of the mushrooms in real time and generate relevant data; S22: Based on the collected mushroom distribution and maturity data, a path planning algorithm is executed to determine the optimal moving route by analyzing the current spatial position of the picking robot, mushroom density, mushroom cap shading, mushroom height and mushroom maturity information, and to select a path that can complete lossless picking in the shortest time, avoiding picking areas of immature mushrooms; S23: The picking robot automatically adjusts the moving route and speed according to the calculated path. During the movement, the real-time position of the picking robot is continuously obtained, and the route is dynamically adjusted according to the mushroom information in the picking area and the newly collected data to optimize the path and avoid repeated picking and omission. S24: When the picking robot approaches the target area, the real-time feedback information is used to fine-tune its moving position to ensure that the optimal picking distance is reached when approaching the target mushrooms, so as to achieve accurate picking operations; The S22 specifically includes: S221: Acquire spatial distribution information of mushrooms, including the position coordinates and maturity of each mushroom, and record the current position of the picking robot to clarify the relative position of the mushrooms and the picking robot; S222: based on the relative distance between the current position of the picking robot and each mushroom, calculating the moving distance of the robot to each mushroom, and sorting the mushrooms by distance, giving priority to mushrooms with a closer distance; S223: Considering the maturity of the mushrooms at the same time, a weight value is assigned to each mushroom by combining the maturity and the moving distance. Mushrooms with high maturity and close distance are given higher priority. ; S224: Considering both the mushroom cap shielding and the mushroom height, the weights of the mushroom cap shielding and the mushroom height are combined with the classification of maturity and moving distance. Combined with high maturity, close distance, high altitude, and unobstructed mushrooms, high priority is given. ; S225: Use the greedy algorithm to select the weight value The largest mushroom is selected as the picking target. After the picking robot moves to the mushroom position, it updates the current position and continues to select the next mushroom with a high priority. The process is repeated until all mushrooms that meet the maturity requirements are picked. S226: The entire picking path is planned according to the principle of minimizing the total moving distance, so as to ensure that the picking robot can complete the picking operation of all target mushrooms in sequence along the shortest path; S3: The receiving mechanism moves synchronously with the picking robot and is associated with the path planning algorithm to ensure that the receiving mechanism is aligned with the discharge port and receives the mushrooms delivered by the picking robot; S4: The appearance, color and shape of the mushrooms are detected by an image recognition device installed in the material receiving mechanism based on a preset quality recognition algorithm, and the mushrooms that meet the quality standards are separated from the unqualified mushrooms through a diversion device and enter the first drop hopper and the second drop hopper respectively; S5: performing secondary classification on the mushrooms entering the first hopper, classifying the mushrooms by size based on volume and diameter parameters, and directing the larger mushrooms to the third hopper and the smaller mushrooms to the fourth hopper by the diversion device; S6: When any drop hopper is close to full load, a full load signal will be issued to trigger the replacement operation of the receiving mechanism and start the standby receiving mechanism to ensure continuous harvesting operation.

2. The collaborative control method of the collecting robot based on mushroom harvesting collaboration according to claim 1 is characterized in that: The S1 specifically includes: S11: When the picking robot moves along the track of the cultivation rack, the picking robot is controlled to move forward and backward by a set driving motor, and the driving motor cooperates with the guide rail on the cultivation rack to achieve a stable moving process. The guide rail has a positioning device to ensure that the picking robot can be accurately positioned above the position of the mushrooms; S12: The picking robot picks mushrooms through the suction cup installed on the mechanical arm. The mechanical arm extends vertically according to the preset picking height parameters. The suction cup is connected to the pneumatic system, and the mature mushrooms are separated from the fungus body and stably grasped through the negative pressure adsorption principle; S13: The picking robot conveys the mushrooms caught by the suction cup from the suction cup end to the discharge port inside the robot through the built-in conveyor belt.

3. The collaborative control method of the collecting robot based on mushroom harvesting collaboration according to claim 1 is characterized in that: The S24 specifically includes: S241: When the picking robot approaches the target mushroom area, the relative distance between the picking robot and the target mushroom is first obtained through the real-time position sensor, and the lateral and longitudinal position deviations between the current position of the robot and the target mushroom are recorded; S242: Based on the acquired position deviation information, the proportional-integral-differential control algorithm is used to perform position fine-tuning, and the moving speed and direction of the robot are dynamically adjusted according to the distance error to ensure that the robot gradually approaches the target mushroom; S243: When the distance error between the robot and the target mushroom is reduced to within a preset range, that is, when the optimal picking distance is reached, the PID controller will reduce the moving speed and maintain a stable position accuracy to ensure that the suction cup is accurately aligned with the mushroom for picking.

4. The collaborative control method of the collecting robot based on mushroom harvesting collaboration according to claim 1 is characterized in that: The S3 specifically includes: S31: When the picking robot is started, the real-time position information of the picking robot is first obtained, including its current coordinates and moving speed on the cultivation rack, and transmitted to the material receiving mechanism; S32: The material receiving mechanism adjusts its own moving route according to the position information provided by the picking robot using a synchronous tracking algorithm to ensure that the material receiving mechanism and the picking robot maintain a consistent speed and moving direction; S33: Continuously monitor the relative position of the receiving mechanism and the material outlet of the picking robot. When a deviation is detected, the moving speed and direction of the receiving mechanism will be automatically adjusted until the deviation between the receiving mechanism and the material outlet is reduced to a preset range, ensuring seamless connection between the material outlet and the receiving area.

5. The collaborative control method of the collecting robot based on mushroom harvesting collaboration according to claim 1 is characterized in that: The S4 specifically includes: S41: collecting the appearance image of each mushroom after picking through an image recognition device, the image recognition device includes a high-definition camera and a light source system, the camera captures the appearance, color and morphological characteristics of the mushrooms and generates corresponding digital image data, and the light source system ensures stable image quality; S42: inputting the collected mushroom image data into a preset quality recognition algorithm, and comparing it with the qualified mushroom templates in the quality standard library to determine whether the mushrooms meet the preset standards; S43: classifying the mushrooms into qualified mushrooms and unqualified mushrooms according to the test results in S42, wherein the qualified mushrooms have appearance, color and morphological characteristics that meet the set standards, and the unqualified mushrooms have obvious differences or defects from the template; S44: After the detection result is transmitted to the central control system, the diversion device is started according to the judgment result. The diversion device controls two flow channels in different directions through an actuator to guide qualified mushrooms to the first drop hopper, while unqualified mushrooms enter the second drop hopper through another flow channel.

6. The collaborative control method of the collecting robot based on mushroom harvesting collaboration according to claim 5 is characterized in that: The S42 specifically includes: S421: Preprocessing the mushroom image collected by the image recognition device, the preprocessing includes removing noise, adjusting color balance, and enhancing edge details; after the image processing, extracting color information and brightness information of each pixel, including three colors of red, green, and blue; S422: extracting feature information of the mushrooms from the preprocessed image through a convolutional neural network, the feature information including color and morphological parameters of the mushrooms, wherein the color information is obtained by analyzing a color histogram, specifically including color distribution of three color channels: red, green, and blue; the morphological parameters are extracted through edge detection and contour analysis, and are used to reflect the symmetry, shape, and surface characteristics of the mushrooms; S423: comparing the extracted mushroom characteristic information with a preset qualified mushroom template in the quality standard library, where the template also includes the color and morphological characteristics of the standard mushrooms; by calculating the difference between the mushrooms and the template, evaluating the degree of matching between the appearance, color and morphology of the mushrooms and the qualified standards; S424: According to the comparison result, whether the mushrooms meet the preset quality standards is determined according to the difference between the mushrooms and the qualified template; if the characteristic difference of the mushrooms is within the preset tolerance range, the mushrooms are judged to be qualified; if it exceeds the range, they are judged to be unqualified.

7. The collaborative control method of the collecting robot based on mushroom harvesting collaboration according to claim 1 is characterized in that: The S5 specifically includes: S51: In the first hopper, the volume and diameter parameters of each mushroom are measured by an image recognition device; S52: Compare the volume parameter and the diameter parameter with the preset size classification standard respectively. The classification standard sets different volume and diameter thresholds based on the type and specification of the mushroom. If the volume and diameter of the mushroom exceed the preset threshold at the same time, it is judged as a large mushroom; if it is lower than the threshold, it is judged as a small mushroom. S53: According to the classification result, large mushrooms are directed to the third drop hopper; at the same time, according to the determination result, small mushrooms are directed to the fourth drop hopper to avoid mixing of mushrooms of different sizes.

8. The collaborative control method of a collecting robot based on mushroom harvesting collaboration according to claim 1, characterized in that: The S6 specifically includes: S61: A load sensor is installed in each hopper to monitor the current load of the hopper in real time; the load sensor transmits the measured current weight data W to the central control system, where W is the actual weight in the hopper; S62: The central control system is based on the preset full load threshold , continuously monitor the current weight W; when the current weight W measured by the sensor is close to or equal to the full load threshold , that is, satisfy When the conditions are met, the system automatically sends a full load signal; S63: After the full load signal is transmitted to the central control system, the standby material receiving mechanism is triggered to start; the standby material receiving mechanism is in standby state in advance. After the full load signal is issued, the central control system sends a command to the actuator, and the actuator switches the material receiving path to ensure that the standby material receiving mechanism takes over the existing material receiving hopper and continues the material receiving operation.

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