Optimization System for the Trajectory of Mechanical Harvesting of Fresh Cut Peonies Based on Automatic Control

Abstract

The present invention relates to the technical field of non-electric variable control, specifically an optimized system for the mechanical picking movement trajectory of fresh cut peonies based on automatic control. The system includes a pneumatic pressure acquisition module that installs a pneumatic pressure sensor inside the cylinder to obtain the internal pressure value of the cylinder and establish a pneumatic pressure regulation characteristic table. In the present invention, the pneumatic pressure acquisition and feedback mechanism enables the picking tool to adjust the force in real time, avoiding uneven force caused by pneumatic pressure fluctuations. It improves the stability during the picking process, ensures the contact accuracy between the picking force and the target object, and reduces the physical damage to peonies. During the picking process, by dynamically adjusting the position and trajectory of the picking tool, the deviation can be corrected in real time, ensuring the precise movement of the tool to dock with the target object and reducing the error in the operation. In addition, through the combination of displacement monitoring and pneumatic pressure output commands, the movement trajectory can be automatically compensated during the movement process, improving the picking efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of non - electrical variable control, and particularly to an optimized system for the mechanical picking motion trajectory of fresh cut peonies based on automatic control. Background Art

[0002] Non - electrical variable control technology mainly refers to controlling the variable changes of a system through mechanical or physical means without the need for electric drive. Such technologies usually rely on the changes of physical parameters such as hydraulic pressure, pneumatic pressure, mechanical devices, temperature, pressure, etc. for control and adjustment. In these control systems, the signals and control methods are mostly driven by mechanical input or natural environmental changes. For example, the thrust driven by hydraulic pressure, the power output regulated by pneumatic pressure, or the physical reactions caused by temperature changes. And the optimized system for the mechanical picking motion trajectory of fresh cut peonies is a system aiming to optimize the picking process of fresh cut peonies through automatic control technology.

[0003] In the prior art, due to the lack of real - time adjustment of the picking trajectory and the tool position, there may be a situation where the tool cannot accurately dock with the picking target, increasing errors and crop losses. In addition, the lack of displacement compensation and trajectory optimization functions makes it difficult to correct the deviation in the tool movement in real time, resulting in low operation efficiency. Therefore, improvements are needed. Summary of the Invention

[0004] The purpose of the present invention is to solve the deficiencies existing in the prior art, and to propose an optimized system for the mechanical picking motion trajectory of fresh cut peonies based on automatic control.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions: The optimized system for the mechanical picking motion trajectory of fresh cut peonies based on automatic control includes:

[0006] A pneumatic pressure acquisition module, which installs a pneumatic pressure sensor inside the cylinder to obtain the internal pressure value of the cylinder and establish a pneumatic pressure regulation characteristic table;

[0007] A force control module, which performs a correlation operation on the internal pressure value of the cylinder and the pressure output value of the picking tool according to the pneumatic pressure regulation characteristic table to obtain a force mapping value; compensates the force mapping value with the pressure fluctuation value of the pneumatic actuator to establish a force regulation sequence;

[0008] A displacement feedback module, which collects the displacement of the cylinder piston rod and the motion parameters of the pneumatic actuator using a displacement sensor according to the force regulation sequence to generate displacement monitoring data; analyzes the displacement monitoring data and the pneumatic pressure output command to establish a motion characteristic sequence;

[0009] The trajectory optimization module collects the position coordinates of the cutting points of the peony stalks and the coordinates of the movement trajectory points of the picking tool according to the movement feature sequence, and generates position calibration data; performs displacement compensation on the position calibration data and the movement trajectory of the picking end effector to establish trajectory optimization parameters.

[0010] Preferably, the steps for obtaining the air pressure regulation characteristic table are as follows:

[0011] Install an air pressure sensor inside the cylinder, set the working parameters of the sensor, record the pressure values in chronological order, store the pressure values and detect the data integrity, eliminate abnormal pressure readings, and obtain the cylinder pressure data;

[0012] Based on the cylinder pressure data, analyze the fluctuation trend of the pressure value at different times, calculate the pressure change rate, and extract the pressure values in the stable operation stage according to the pressure change rate to generate pressure characteristic data;

[0013] According to the pressure characteristic data, summarize the corresponding relationship between each characteristic pressure value and the internal state of the cylinder, and combine the statistical distribution of each pressure point to construct the mapping relationship between the cylinder pressure and the operating state, and establish the air pressure regulation characteristic table.

[0014] Preferably, the steps for obtaining the force mapping value are as follows:

[0015] According to the air pressure regulation characteristic table, extract the standard data of the internal pressure value of the cylinder, screen the pressure points within the working range of the picking tool, and sort out the corresponding pressure output values of the picking tool according to different pressure levels to obtain the correlation data between the cylinder pressure and the pressure output of the picking tool;

[0016] Based on the correlation data between the cylinder pressure and the pressure output of the picking tool, calculate the force mapping value, and the calculation formula is:

[0017] Among them, is the force mapping value, is the internal pressure value of the cylinder, is the pressure output value of the picking tool, is the distance between the cylinder and the picking tool, is the contact area between the cylinder and the picking tool, and are respectively the maximum and minimum values in the cylinder pressure values.

[0018] Preferably, the steps for obtaining the force adjustment sequence are as follows:

[0019] Extract the pressure fluctuation data of the pneumatic actuator, analyze the change range of the pressure fluctuation under different working conditions, and obtain the standard data of the pressure fluctuation of the pneumatic actuator;

[0020] Calculate the compensation balance value according to the standard data of the pneumatic actuator pressure fluctuation and the force mapping value. The calculation formula is:

[0021] where, is the compensation balance value, is the correlation data between the cylinder pressure and the pressure output of the picking tool, is the fluctuation range of the pressure output of the picking tool, is the parameter of the pneumatic actuator, is the pressure value of the pneumatic actuator, is the fluctuation characteristic coefficient, is the standard deviation of the pressure fluctuation within the time, is the pressure fluctuation value of the pneumatic actuator, is the maximum pressure value of the pneumatic actuator;

[0022] Establish a force adjustment sequence based on the compensation balance value.

[0023] Preferably, the steps for obtaining the displacement monitoring data are as follows:

[0024] According to the force adjustment sequence, combined with the initial position of the cylinder piston rod and the motion state of the pneumatic actuator, use a displacement sensor to collect the displacement data of the cylinder piston rod in real time, record the displacement changes at each moment, and obtain the monitoring data of the displacement of the cylinder piston rod;

[0025] Based on the monitoring data of the displacement of the cylinder piston rod, combined with the motion parameters of the pneumatic actuator, analyze the displacement law of the pneumatic actuator in each working stage, and generate displacement monitoring data.

[0026] Preferably, the steps for obtaining the motion characteristic sequence are as follows:

[0027] Calculate the motion characteristic value based on the displacement monitoring data. The formula is:

[0028] where, is the motion characteristic value, is the air pressure output value, is the displacement data, is the standard deviation of the displacement data;

[0029] Extract the motion characteristics of the cylinder based on the motion characteristic value to form a motion characteristic sequence.

[0030] Preferably, the steps for obtaining the position calibration data are as follows:

[0031] Real-time collection of the coordinates of the movement trajectory points of the picking tool, combined with the position coordinates of the cutting points of the peony stalks, perform coordinate normalization, exclude invalid data, and obtain a positioning data set;

[0032] Based on the movement feature sequence and the position data set, calculate the calibration error, and the formula is:

[0033] Among them, is the calculated calibration error, 、 、 are the coordinates of the cutting points of the peony stalks in three-dimensional space respectively, 、 、 are the coordinates of the movement trajectory points of the picking tool;

[0034] Based on the calibration error, perform position accuracy analysis and generate position calibration data.

[0035] Preferably, the steps for obtaining the trajectory optimization parameters are:

[0036] Through the displacement calibration data and the movement trajectory of the picking end effector, perform displacement compensation operation, and use coordinate transformation to correct the error between the movement trajectory of the picking end effector and the calibration data to obtain the trajectory optimization parameters.

[0037] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0038] In the present invention, the air pressure acquisition and feedback mechanism enables the picking tool to adjust the force in real time, avoiding uneven force caused by air pressure fluctuations. It improves the stability during the picking process, also ensures the contact accuracy between the picking force and the target object, and reduces the physical damage to the peony. During the picking process, by dynamically adjusting the position and trajectory of the picking tool, the deviation can be corrected in real time, ensuring the precise movement of the tool to dock with the target object and reducing the error in the operation. In addition, through the combination of displacement monitoring and air pressure output commands, the movement trajectory can be automatically compensated during the movement process, improving the picking efficiency, reducing the crop loss caused by deviation, and optimizing the energy utilization and operation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is the system flow chart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0040] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0041] Please refer to Figure 1 , the present invention provides a technical solution: an optimized system for the mechanical picking motion trajectory of fresh cut peonies based on automatic control includes:

[0042] A pneumatic pressure acquisition module, which installs a pneumatic pressure sensor inside the cylinder to obtain the internal pressure value of the cylinder and establish a pneumatic pressure regulation characteristic table;

[0043] A force control module, which performs an associative operation on the internal pressure value of the cylinder and the pressure output value of the picking tool according to the pneumatic pressure regulation characteristic table to obtain a force mapping value; compensates the force mapping value with the pressure fluctuation value of the pneumatic actuator to establish a force regulation sequence;

[0044] A displacement feedback module, which collects the displacement of the cylinder piston rod and the motion parameters of the pneumatic actuator by using a displacement sensor according to the force regulation sequence to generate displacement monitoring data; analyzes the displacement monitoring data and the pneumatic pressure output instruction to establish a motion characteristic sequence;

[0045] A trajectory optimization module, which collects the position coordinates of the cutting point of the peony stem and the coordinates of the motion trajectory points of the picking tool according to the motion characteristic sequence to generate position calibration data; compensates the displacement of the position calibration data and the motion trajectory of the picking end effector to establish trajectory optimization parameters.

[0046] The steps for obtaining the pneumatic pressure regulation characteristic table are as follows:

[0047] Install a pneumatic pressure sensor inside the cylinder, set the working parameters of the sensor, record the pressure values in chronological order, store the pressure values and detect the data integrity, and eliminate abnormal pressure readings to obtain the cylinder pressure data;

[0048] Based on the cylinder pressure data, analyze the fluctuation trend of the pressure value at different times, calculate the pressure change rate, and extract the pressure values in the stable operation stage according to the pressure change rate to generate pressure characteristic data;

[0049] According to the pressure characteristic data, summarize the corresponding relationship between each characteristic pressure value and the internal state of the cylinder, and combine the statistical distribution of each pressure point to construct the mapping relationship between the cylinder pressure and the operating state, and establish a pneumatic pressure regulation characteristic table.

[0050] Specifically, install a pressure sensor inside the cylinder, set the working parameters of the sensor, and record the pressure values in chronological order. First, configure the sensor to collect pressure values ten times per second, and set the normal pressure range to 0 MPa to 2 MPa based on an assessment of the maximum bearing pressure range of the equipment. This range is obtained through experience by combining the rated pressure of 2.2 MPa marked on the equipment nameplate and leaving a safety margin. When recording the pressure values, check one by one whether the collected values exceed the range of 0 MPa to 2 MPa. If the value is less than 0 MPa or greater than 2 MPa, it is regarded as abnormal. The abnormal data is reconfirmed manually or automatically and marked in a separate abnormal record set. To check the data integrity, it is necessary to verify whether the number of collections within the same period meets the requirement of ten times per second. For example, if only 8 or fewer collections are made in a certain second, it is regarded as missing data and classified into the missing record sequence. The missing records can be interpolated based on the average value of the same time period or adjacent time points on the same day. The average value is calculated from the confirmed valid pressure data within the same time period on the same day. If it is found that the proportion of abnormal records or missing records continuously exceeds 5% in certain periods, the sensor status and related connection lines can be further checked. At the same time, the working parameters of the sensor are re-verified and the sensitive components are replaced if necessary. All finally confirmed valid records are maintained in the original order in the time series and associated with the corresponding timestamps, finally forming continuous and valid cylinder pressure data, and obtaining the cylinder pressure data.

[0051] Based on the cylinder pressure data, analyze the fluctuation trend of the pressure value at different times. First, divide the cylinder pressure data into multiple time segments according to each hour or smaller intervals within a day, and calculate the difference of the continuous pressure changes within each time segment to obtain the pressure change rate. In order to determine whether the pressure value is in a relatively stable operating stage, it is necessary to compare the change rate within each time segment with a pre-determined fluctuation threshold. This fluctuation threshold can be set to 0.06 MPa / s after combining the 0.05 MPa / s recommended in the equipment operation manual and on-site experience evaluation. When most of the differential results within a certain time segment are less than 0.06 MPa / s, it is considered that this time period can be regarded as a stable operating stage. If some of the differential results continuously exceed 0.06 MPa / s and the duration of this phenomenon reaches 10 seconds or more, this time period can be marked as a fluctuation stage. In order to assign statistical quantitative data to the stable stage, the arithmetic mean of the minimum pressure value and the maximum pressure value can be taken within the stable stage as the representative value of this stage, so as to obtain the comprehensive pressure index of the stable operating stage. If the data distribution of some time segments is uneven or the fluctuation is too large, they are classified as special time periods for storage and excluded as appropriate in subsequent stages. After calculating and judging each time segment one by one, the representative values of all stable stages are stored in a feature array. Subsequently, the most common pressure intervals for each time period are further sorted out from this feature array, and finally a statistical result that can characterize the stable pressure situation of the equipment during different working time periods is summarized to generate pressure characteristic data.

[0052] According to the pressure characteristic data, summarize the corresponding relationship between each characteristic pressure value and the internal state of the cylinder. First, divide the pressure characteristic data into several categories according to factors such as working duration, ambient temperature, and equipment load. The frequency of occurrence of the characteristic pressure values is counted under each category and the corresponding internal state information of the cylinder is marked. In order to facilitate the establishment of mapping relationships under different conditions, the duration of the stable stage closely associated with the characteristic pressure value can be additionally recorded. After completing the category division, it is necessary to comprehensively consider the statistical distribution and select the characteristic pressure values that frequently appear under each category as the main reference. If some characteristic pressure values are significantly larger or smaller than other values in terms of duration, it is necessary to compare the abnormal record set again to confirm that this characteristic value is not caused by reasons such as abnormal acquisition or missing interpolation. Through this step-by-step comparison method, the association between the characteristic pressure value and the internal state of the cylinder is corresponded one by one. After confirming the state categories corresponding to all the main characteristic values, these corresponding relationships are integrated into an overall mapping matrix of cylinder pressure and operating state, and the mapping entries in this matrix are arranged in the order from the lowest pressure to the highest pressure. Finally, on this basis, state identifiers are set for different pressure regions. If extreme values greater than 2 MPa or lower than 0 MPa appear, they are marked separately and classified into the abnormal interval. After completing the sorting and corresponding state classification of all characteristic values, an air pressure adjustment characteristic table is established.

[0053] The steps to obtain the intensity mapping value are:

[0054] According to the air pressure regulation characteristic table, the standard data of the internal pressure value of the cylinder is extracted, the pressure points within the working range of the picking tool are screened, and the corresponding picking tool pressure output values ​​are sorted according to different pressure levels to obtain the correlation data between the cylinder pressure and the picking tool pressure output;

[0055] Based on the correlation data of the cylinder pressure and the picking tool pressure output, the force mapping value is calculated using the following formula:

[0056] in, Map values ​​for velocity, is the internal pressure of the cylinder, is the pressure output value of the picking tool, is the distance between the cylinder and the picking tool, is the contact area between the cylinder and the picking tool, and They are the maximum and minimum values ​​of the cylinder pressure respectively.

[0057] Specifically, according to the contents of the air pressure regulation characteristic table obtained previously, combined with the standard data of the previously recorded internal cylinder pressure values, a comparison is performed, the pressure values ​​sampled within the required time period are selected and screened one by one against the pre-established valid range of 0MPa to 2MPa. For example, if a sampled value is less than 0MPa or greater than 2MPa, it is regarded as invalid data and stored separately. When the proportion of invalid data exceeds 5%, the hardware connection and sensor status are further checked and recorded. After confirming the data quality, the working range of the picking tool during its normal operation is referred to to determine which pressure points match the picking tool. For example, if the picking tool operates between 0.2MPa and 1.6MPa, the cylinder pressure value falling within this interval is marked as a candidate value. At the same time, the picking tool pressure output parameters obtained in the previous stage are read for item-by-item correspondence. After completing the candidate values ​​and the picking tool pressure output parameters, the corresponding values ​​are compared. During the comparison process, it is necessary to check whether the timestamp can correspond to the operating conditions at the same time and the proportion must not be less than 90%. For example, when the pressure output value of the picking tool is sampled ten times per second within a certain period of time, it is necessary to ensure that the cylinder pressure data also has ten valid samples in the same period of time and the time difference does not exceed 0.1 second. If the match is successful, the cylinder pressure point and the picking tool pressure output value will be centrally recorded, and all paired data that meet the working range and have synchronized timestamps will be sorted and sorted from small to large according to different pressure levels. For example, in the 0.2MPa to 0.5MPa segment, the 0.6MPa to 1.0MPa segment, the 1.1MPa to 1.6MPa segment, etc., the corresponding aggregation distribution of the picking tool pressure output value is calculated and the distribution center value is recorded. Then the results of all segments are summarized to form the final corresponding data set to obtain the correlation data between the cylinder pressure and the picking tool pressure output.

[0058] The benefit of the formula is that it combines the real-time pressure in the cylinder and the actual pressure output value of the picking tool, and takes into account the distance and contact area between the cylinder and the picking tool, thereby generating a force mapping value and reflecting the overall force brought about by the synergistic effect of various elements in the pneumatic execution process.

[0059] The parameter acquisition step is to continuously record the internal pressure of the cylinder through the sensor pre-installed inside the cylinder and collect it at a frequency of ten times per second. Then, the collection results within a period of time are compared with the range of 0MPa to 2MPa that the equipment can withstand and invalid readings are eliminated. When the proportion of invalid readings exceeds 5% continuously within a certain period of time, the sensor wiring and sensitivity are checked again. All confirmed valid pressure data will form a pressure sequence. You can select or take the average and median of the time segment at a certain moment from the sequence. For example, take the average value of multiple stable stages in a day as When higher precision is required, short-term high-frequency measurements can be performed to obtain more detailed Numeric value.

[0060] The steps for obtaining parameters are to install a pressure detection device on the picking tool and collect pressure at the same frequency as the cylinder internal pressure per second. The readings that appear at the same timestamp are compared one-to-one and stored in the same record index. Then, check whether there is a picking tool pressure output that seriously does not match the cylinder pressure value, such as a large range of offset or missing. If an abnormality is found, mark the period as an invalid period and list it separately. The remaining valid periods can select the average value or instantaneous value as the value according to specific needs. For example, if the overall distribution of the pressure output values ​​of the picking tools detected within a certain hour is between 0.3MPa and 1.5MPa, its mean value or multiple quantiles can be recorded for subsequent force calculation.

[0061] The parameter acquisition step is to obtain the straight-line distance between the cylinder and the end of the picking tool by field measurement, record the distance and compare it at different picking positions. If the cylinder piston extends 0.25 meters at a certain moment and the picking tool is fixed at the end of a mechanical arm and maintains an additional arm length of 0.2 meters, the distance between the two is 0.45 meters. In this way, the distance can be recorded under different working conditions. The measured values ​​are compared with the measurement benchmark given in the mechanical structure manual. When the change between adjacent time periods is drastic and exceeds 0.05 meters, the robot arm movement path is compared to confirm whether a collision or interference occurs.

[0062] The steps for obtaining the parameters are as follows: Use a contact surface measuring instrument to obtain the effective area of the contact area between the cylinder piston end and the picking tool, and record the dynamic changes of this contact area in each period. If it is found that the contact area suddenly increases or decreases, verify according to the shape and angle of the clamping part of the picking tool. The specific value can be obtained by dividing it into several small areas, measuring their geometric dimensions, and then accumulating them. If the measurement process shows that the area mostly remains around 0.004 square meters, then 0.004 square meters can be used as the value used in subsequent operations. By continuously accumulating measurement data and performing statistics, a more refined S-value distribution can be obtained.

[0063] and The steps for obtaining the parameters are as follows: Sort all the internal cylinder pressure data within a complete working cycle from smallest to largest, record the head and end of the sequence. After excluding all the pressure readings determined to be invalid, take the maximum value of the remaining pressure values as and take the minimum value as , for example, the cylinder pressure monitoring values for ten consecutive hours fluctuate between 0.1 MPa and 2.0 MPa. After excluding several periods with abnormal readings, the minimum pressure value of 0.12 MPa and the maximum pressure value of 1.95 MPa appear. Then 1.95 MPa can be taken, 0.12 MPa can be taken. During actual use, the data for a longer period can be combined to re-evaluate this interval and update these two indicators if necessary.

[0064] The force mapping value calculated by substituting the parameters is approximately 58.27 and is at a relatively high level under the current measurement and operation conditions. When is greater than 50, it indicates that the force exerted by the picking tool at the corresponding moment is relatively large. If the value is lower than 20, it indicates that the force is relatively small. For the intermediate interval, the appropriate picking force range can be judged in combination with the specific working environment, and based on this, further adjustment of the internal cylinder pressure or the output of the picking tool can be made in subsequent links.

[0065] The steps for obtaining the force adjustment sequence are as follows:

[0066] Extract the pressure fluctuation data of the pneumatic actuator, analyze the change range of the pressure fluctuation under different working conditions, and obtain the standard data of the pressure fluctuation of the pneumatic actuator;

[0067] According to the standard data of the pressure fluctuation of the pneumatic actuator and the force mapping value, calculate the compensation balance value. The calculation formula is:

[0068] Among them, is the compensation balance value, The associated data of the cylinder pressure and the pressure output of the picking tool The fluctuation range of the pressure output of the picking tool The parameters of the pneumatic actuator The pressure value of the pneumatic actuator The fluctuation characteristic coefficient The standard deviation of the pressure fluctuation within a period of time The pressure fluctuation value of the pneumatic actuator The maximum pressure value of the pneumatic actuator;

[0069] Based on the compensation balance value, a force adjustment sequence is established.

[0070] Specifically, based on the operating information of the pneumatic actuator obtained previously, it is first necessary to classify and record the pressure fluctuation conditions of the pneumatic actuator under different working conditions, and refine the statistics at intervals of every day or every hour. Each record should be compared with the pre-set working range of 0 MPa to 2 MPa. If the pressure value of the pneumatic actuator exceeds 2 MPa or is lower than 0 MPa three times consecutively within the corresponding period, the sensor readings for that period should be checked and additional investigations should be carried out to confirm possible leakage channels or overload conditions. After accumulating and sorting out all valid records, the pressure fluctuation ranges of each period are grouped. For example, the periods with a pressure fluctuation exceeding 0.2 MPa are regarded as high-fluctuation intervals, the periods with a fluctuation between 0.05 MPa and 0.2 MPa are regarded as medium-fluctuation intervals, and the periods with a fluctuation lower than 0.05 MPa are regarded as low-fluctuation intervals. These thresholds are obtained by repeatedly comparing the limit pressure marked on the equipment nameplate with the actual test data. Subsequently, the high-fluctuation intervals are analyzed second by second or minute by minute, recording their durations and relating them to factors such as the working load, the solenoid valve switching speed, and the ambient temperature. After item-by-item sorting and summarization, a more accurate fluctuation distribution is obtained. To ensure consistent statistical caliber, it is necessary to align the timestamps of all acquisition devices uniformly and check whether the readings at the same moment are synchronized through a verification program. If there is data loss, the missing values are interpolated by comparing the values in adjacent periods within a short time range, and then the supplemented data is incorporated into the overall statistical process. After analyzing all periods, the fluctuation data corresponding to each working condition are compared and a pressure fluctuation curve is drawn. By calculating and comparing the curve segments, an overall standard deviation and average fluctuation amplitude are extracted under different working conditions. At this time, combined with the temperature, the cylinder load, and the relevant operating hours in the corresponding intervals, each item is screened and judged to find the most frequently occurring fluctuation amplitude and typical intervals, so as to define these intervals as the reference values of the standard data, and the standard data of the pressure fluctuation of the pneumatic actuator are obtained.

[0071] The benefit of the formula lies in integrating the key quantities in the overall operation of the pneumatic actuator, including both the correlation information between the cylinder pressure and the picking tool, and considering multiple factors such as the pressure fluctuation range, the actuator's own parameters, and the upper and lower limits of the maximum pressure, which has important measurement value for establishing the force adjustment sequence subsequently.

[0072] The steps to obtain the parameters are as follows. It is necessary to conduct segmented statistics on the correlation data between the cylinder pressure and the pressure output of the picking tool, and require that the timestamp alignment error does not exceed 0.1 second within the same second. Mark the successfully matched records with the same index and summarize them according to different load and ambient temperature levels. Store the pressure value that most frequently appears in the output of the picking tool within a certain period of time and the corresponding internal cylinder pressure value together. Then, the average or median within this period can be taken as , if higher precision is required, the values of the sub - segments can be calculated within 1 minute or a shorter duration. Finally, a series of values are obtained. By comparing the performances in multiple periods within a complete operation cycle, select the paragraphs that best match the operation requirements to obtain one or more typical values for calculation. For example, during a ten - hour operation period, when the matching degree of all records and indexes is greater than 99%, the average value of the cylinder pressure and the pressure output of the picking tool measured is 1.2 MPa, then it can be recorded as the of this period.

[0073] The steps to obtain the parameters are as follows. Real - time record the pressure output of the picking tool under different loads and moving speeds, and collect it at a frequency of ten times per second. Record the difference between the maximum and minimum values within the same time window as the fluctuation range, and then select the median or average value of multiple repeated measurements as , for example, during a continuous 8 - hour test, if the fluctuation range in each period remains between 0.3 MPa and 0.5 MPa, the average value of 0.4 MPa can be taken as , if the value measured in a short time briefly exceeds 0.5 MPa, mark the possible abnormal working conditions and investigate the specific reasons in subsequent analysis, so that can truly reflect the pressure fluctuation amplitude of the picking tool.

[0074] The steps for obtaining the parameters are as follows: It is necessary to check according to information such as the model, structural characteristics, and built-in valve switch characteristics of the pneumatic actuator. During multiple cyclic operations, measure the impact of the pressure response speed of the pneumatic actuator during loading and unloading actions on the overall performance. By summarizing multiple operation records, for example, during 300 consecutive hours of operation, conduct statistics according to criteria such as the response time or response efficiency of pressure regulation within each hour, and then compare the data with the sampling frequency reference diagram recommended in the equipment manual to screen out the key indicators reflecting the characteristics of the pneumatic actuator. Quantify this indicator in the form of a formula or table and record it as For example, after calculation, This value can be continuously valid after measurement in equipment of the same model. It can fluctuate slightly with the degree of equipment aging, but generally does not exceed ±0.05.

[0075] The steps for obtaining the parameters are as follows: Extract the average pressure value at a certain moment or during a certain period from the working pressure distribution of the pneumatic actuator under actual working conditions, and regard this value as the pressure level of the current actuator. Since the pneumatic actuator usually operates within the range of 0 MPa to 2 MPa, the average of the pressure values recorded per second can be calculated during the on-site collection period. If there are no obvious abnormalities during this period and the data integrity is above 98%, the calculated average value can be used as For example, the average pressure value recorded during a 2-hour operation process is 1.3 MPa, then .

[0076] The steps for obtaining the parameters are as follows: Refine information through special statistics on the fluctuation characteristics during past or current equipment monitoring. In particular, summarize the pulsation frequency of the pneumatic actuator, the instantaneous impact value when the air flow in the pipeline switches, etc. over multiple days or shifts, then calculate the fluctuation coefficient of each stage and compare its distribution, screen out the most representative interval, and compare the degree of fluctuation within this interval with the regular operation specifications. If a stable value is obtained after multiple repeated tests, it can be determined as For example, after half a month of data analysis, is set to 0.9 as the fluctuation characteristic coefficient during the execution process. In actual work, if there are obvious changes in the equipment structure or operating speed, this value also needs to be re-measured in a timely manner.

[0077] The steps for obtaining the parameters are as follows: First, calculate the mean value of the pressure readings of the pneumatic actuator within the same time period, then sum the squares of the differences between each reading and this mean value and divide by the number of samples, and finally take the square root to obtain the standard deviation of this time period. If the recording period is 1 hour and the pressure value is collected ten times per second, then 36,000 pieces of data can be obtained within 1 hour. First calculate the average value of these data and then perform variance calculation and take the square root, then , for example, it is found through calculation that the standard deviation during this period is 0.08 MPa, then , the fluctuations in different periods can be measured in the same way to form a standard deviation data sequence.

[0078] The steps for obtaining the parameter are as follows: it is necessary to take the difference between the instantaneous pressure readings of the pneumatic actuator during load switching, stopping or accelerating and the adjacent steady-state values, and continuously observe the offset of this difference value within a certain time range, and record the extreme value among them as to represent the maximum instantaneous fluctuation amplitude under the current operating conditions. To ensure the credibility of the value, the difference curves can be compared during multiple repeated runs and the most frequently occurring maximum fluctuation range can be found. If most of the difference peaks in a certain operating environment are between 0.2 MPa and 0.3 MPa, then the average value of 0.25 MPa can be extracted and recorded as .

[0079] The steps for obtaining the parameter are determined by combining the maximum load-bearing value given in the instruction manual of the pneumatic actuator and the peak records of the previous multi-stage pressure test data. Generally, this value is between 2.0 MPa and 2.5 MPa. It is necessary to pay attention to the ultimate bearing capacity of the equipment during multiple detections and record the highest value of each test. If the upper limit of the safety range is confirmed to be 2.2 MPa and the actual monitored peak has reached 2.1 MPa, then can be used to characterize the maximum pressure value of the current equipment and continuously monitor it during subsequent operations.

[0080] Substitute the parameter into the calculation to obtain the current compensation balance value which is approximately 0.3498. If similar values are obtained in multiple operation records, it indicates that the pressure fluctuation of the pneumatic actuator and the picking tool remain in a relatively stable coupling state during this period. If subsequent monitoring finds that rises above 0.6, it can be determined as a large fluctuation state, and it is necessary to re-adjust the force configuration by combining the previously obtained correlation data between the cylinder pressure and the pressure output of the picking tool. If is significantly lower than 0.2, it indicates that the overall fluctuation is small, and other factors can be further observed to ensure the matching of the overall operation process.

[0081] After obtaining the compensation balance value, it is necessary to continuously record the values within each time period, and compare them with a set monitoring period. For example, every ten minutes or every hour, sort all data from smallest to largest and mark the intervals with obvious differences. Based on the previously established correlation indicators, if certain When the situation of being higher than 0.6 or lower than 0.2 occurs, the corresponding relationship between the cylinder pressure and the picking tool pressure will be grouped separately, and it is necessary to check whether fine-tuning of the equipment structure or operation process is required. For those that meet the current operation standards intervals, the original input parameters will be maintained. After completing this overall induction, it is necessary to bind and store the values of each time period with the operation scenario information to provide a comparison sample for subsequent multiple shifts or multi-day continuous operation. When the record scale expands to a certain extent, it is possible to observe the data distribution of the same machine under different seasons, loads or opening and closing frequencies. Once it is found that the data distribution continuously exceeds the pre-set safety range of 0.2 to 0.6, it is necessary to compare with earlier operation history to determine whether it is due to actuator hardware aging or excessive wear inside the cylinder. After confirming the rationality of all data, arrange its sequence step by step according to the time axis or operation batch, so that an accurate basis can be provided for subsequent force fine-tuning operations, slightly correct the actuator pressure under different shifts or different task schedules, and finally record these correction values item by item after sorting and comparison to establish a force adjustment sequence.

[0082] The steps for obtaining displacement monitoring data are as follows:

[0083] According to the force adjustment sequence, combined with the initial position of the cylinder piston rod and the motion state of the pneumatic actuator, the displacement data of the cylinder piston rod is collected in real time through a displacement sensor, and the displacement changes at each moment are recorded to obtain the monitoring data of the displacement of the cylinder piston rod;

[0084] Based on the monitoring data of the displacement of the cylinder piston rod, combined with the motion parameters of the pneumatic actuator, analyze the displacement law of the pneumatic actuator in each working stage to generate displacement monitoring data.

[0085] Specifically, based on the previously obtained force adjustment sequence, combined with the initial position of the cylinder piston rod and the motion state of the pneumatic actuator, it is necessary to position the cylinder piston rod at a pre-calibrated reference starting point at the beginning of recording, and check the alignment between the reference point and the displacement sensor. Position data is collected every 0.01 seconds or other appropriate sampling frequencies. The displacement of the cylinder piston rod relative to the initial position at this moment is read and compared with the pre-set safe motion range of 0 cm to 30 cm. This range is determined by referring to the maximum stroke design of cylinders of the same specification and combining on-site measurement results. If the displacement reading is less than 0 cm or greater than 30 cm in a single acquisition result, it is regarded as an abnormal reading and marked for subsequent investigation. During daily operation, if the abnormal readings continuously appear more than 5% of the total number of acquisitions, it is necessary to check whether there is wear or looseness on the outer surface of the piston rod. Observe the connecting rod and the sealing ring through mechanical inspection methods and deal with them in a timely manner. The records after confirmation and processing are retained in the time series for subsequent analysis. In order to divide different operation stages, it can be distinguished according to the current state identifier of the pneumatic actuator. For example, when the speed is higher than 1 m / s, it is the fast extension stage, and when the speed is lower than 0.3 m / s, it is the slow retraction stage. The data for these different stages are uniformly summarized and compared in segments. When the difference between the maximum and minimum displacement values within the same stage exceeds 2 cm, it can be correlated with the force adjustment sequence of the same stage to determine whether it is necessary to optimize the control instruction again. After reading and comparing all the segmented data, the real-time displacement sequence at each moment is retained, and the displacement changes at each moment are recorded to obtain the monitoring data of the displacement of the cylinder piston rod.

[0086] Based on the monitoring data of the displacement of the cylinder piston rod and combined with the motion parameters of the pneumatic actuator, it is necessary to first synchronously mark the displacement collected per second within the same operation cycle with information such as the load pressure value and the telescopic speed of the pneumatic actuator. Then, separately count the change curves of displacement over time for the two different action processes of extension and retraction, and check whether there are mutations in the displacement curves under the same action. If the displacement jumps exceed 1 cm continuously five times within a short period, it can be marked as a severely fluctuating paragraph. Compare this severely fluctuating paragraph with the previously determined load pressure range of 0 MPa to 2 MPa. If the corresponding pressure records are concentrated between 1.5 MPa and 2 MPa in the high-load interval, it indicates that this action stage belongs to the high-load state. Through comparison, multi-dimensional analysis can also be combined with the telescopic speed. For example, the speed is divided into a low-speed interval of 0.2 m / s to 0.5 m / s, a medium-speed interval of 0.5 m / s to 1 m / s, and a high-speed interval of greater than 1 m / s. Classify the displacement fluctuations in each interval. If there are severe displacement fluctuations in the medium-speed interval, it is necessary to further check the force adjustment sequence to see if there are large-amplitude force command outputs during this period. Based on the repeated data over multiple days, the displacement distribution range in different stages can be determined. If it is found that the displacement exceeds the established deviation threshold of 2 cm multiple times under certain specific working conditions, maintenance troubleshooting is required. This threshold is determined by the method of taking the average plus 3 times the standard deviation after statistically analyzing all displacement distributions during daily operation. If the displacement deviation exceeds 2 cm in three consecutive time periods, it is considered that the displacement law in this working condition shows obvious anomalies. After checking all the records, the displacement average value, the fluctuation interval, and the sampling times in each stage can be seen. Integrate these data into a complete comparison sequence to generate displacement monitoring data.

[0087] The steps for obtaining the motion feature sequence are as follows:

[0088] Based on the displacement monitoring data, calculate the motion feature value, and the formula is:

[0089] Wherein, is the motion feature numerical value, is the air pressure output value, is the displacement data, is the standard deviation of the displacement data;

[0090] Based on the motion feature numerical value, extract the motion characteristics of the cylinder to form a motion feature sequence.

[0091] Specifically, the advantage of the formula is that by combining the air pressure output value with the displacement data and adding the standard deviation of the displacement data and the difference term between the air pressure output value and the displacement data in the denominator, a comprehensive index for measuring the pneumatic motion characteristics is formed, which can simultaneously consider the dynamic cooperation of pressure and displacement in practical applications, making the subsequent evaluation of the overall motion law of the cylinder more targeted.

[0092] The steps for obtaining the parameters are as follows: The air pressure output value can be recorded by installing a pressure detection device on the cylinder air supply pipeline, collecting several times per second, and comparing each collected value with the working range of 0 MPa to 2 MPa marked on the equipment nameplate one by one. If the collected data is between 0 MPa and 2 MPa, it can be regarded as valid values. Record the value and its timestamp. If there are multiple consecutive collected values exceeding this range, they can be marked as hardware or environmental anomalies and investigated. Eventually, a sequence that meets the duration requirement and has no large-scale anomalies is formed. For example, within an 8-hour cycle, 28,800 valid pressure readings are recorded, obtaining a sequence, the range of which is concentrated between 1.0 MPa and 1.8 MPa, and each corresponds to the displacement data at the same timestamp. The steps for obtaining the parameters are as follows: A displacement sensor matching the cylinder piston stroke needs to be set and the acquisition frequency per second needs to be the same as that of the pressure detection device. Compare the piston expansion and contraction position recorded per second with the initial reference point to obtain the displacement value at the current moment. Organize these displacement values into a sequence arranged in chronological order. If the monitored displacement exceeds 30 cm or is less than 0 cm, it can be regarded as exceeding the normal movement stroke and recorded in the anomaly index. If the proportion of the anomaly index in the entire observation period is not higher than 5%, the

[0093] values during this period are considered available. For example, during a certain regular shift, the monitored displacement values mainly fluctuate between 0 cm and 25 cm. Then arrange these values according to the timestamp to form a sequence, which corresponds one by one to the aforementioned sequence. The steps for obtaining the parameters are as follows: First, calculate the standard deviation of the collected displacement data sequence within several fixed time periods, and then determine

[0094] according to the degree of dispersion of the displacement distribution within the same time period. For example, during the process of calculating the standard deviation of 3,600 displacement data within one hour, it is necessary to first calculate the average value of these displacement data, then square the difference between each data and the average value, sum them up and divide by 3,600, and then take the square root to obtain the displacement standard deviation of this hour, which is regarded as the value of . If the on-site statistical result shows that the standard deviation of the piston displacement within this hour is 2.0 cm, it is recorded as . If it is necessary to reflect the degree of movement dispersion over a longer period, the displacement data for multiple hours or days can be continuously statistically analyzed and finally a representative standard deviation value is selected for use as .

[0095] Substituting the parameters for calculation, the matching degree between the current air pressure output value and the displacement data reaches approximately 117.6 under the specified unit conversion. If it is restored to the original measurement unit system, the numerical value needs to be restored again by combining specific conversion factors. The above steps can also be repeated for different shifts or operation periods to calculate different , if is greater than 100, it may indicate that the air pressure output at a certain moment is significantly higher than the actual displacement requirement. If is between 50 and 80, it is in the relatively matching range, while below 30 indicates that the displacement change or air pressure output is significantly small during the corresponding period. After recording the calculation result sequence, a more in-depth analysis of the motion characteristics can be carried out.

[0096] Based on the motion characteristic values obtained previously, within each time interval, can be compared with the cylinder telescopic speed, the load pressure range, and the piston motion direction within the same period, and timestamp identifiers are added to these data. By continuously tracking these identifiers, the distribution of characteristic values in different operation stages can be clarified. If there is a large difference in changes in the same operation batch, then check whether the cylinder telescopic speed and the aforementioned air pressure output value are within the established range. For example, the speed can be pre-divided into an interval of 0.2 m / s to 0.5 m / s and the pressure into an interval of 0.8 MPa to 1.6 MPa. If a large number of are concentrated at a relatively high or low level, then compare the load conditions at the specific operation moment to see if there are fluctuations caused by additional weight increase or rapid switching. After recording these troubleshooting results item by item, a phased summary of the cylinder motion characteristics is formed. Finally, according to the values in each time period in the record and the corresponding speed-pressure comparison table for horizontal comparison, the relatively stable intervals are extracted separately and marked as typical sections, and the too high or too low sections are marked as abnormal or special sections. When the daily operations accumulate to a certain scale, all the records can be grouped and the key sections under different loads, speeds, and external environmental temperatures can be extracted for comparison. If the are similar in multiple operations under the same environmental temperature, then the data of these sections can be used as a reference basis in subsequent scheduling, and the motion characteristic value distribution of the key periods can be extracted and sorted, and finally linked together to form a complete motion characteristic sequence.

[0097] The steps for obtaining the position calibration data are as follows:

[0098] The real-time acquisition of the coordinates of the motion trajectory points of the picking tool, combined with the position coordinates of the cutting points of the peony stalks, is normalized, invalid data is excluded, and a positioning data set is obtained;

[0099] Based on the motion feature sequence and the position data set, the calibration error is calculated. The formula is:

[0100] where, is the calculated calibration error, 、 、 are the coordinates of the cutting points of the peony stalks in three-dimensional space respectively, 、 、 are the coordinates of the motion trajectory points of the picking tool;

[0101] Based on the calibration error, the position accuracy analysis is carried out to generate the position calibration data.

[0102] Specifically, when collecting the coordinates of the movement trajectory points of the picking tool in real time, it is necessary to determine in advance the three-dimensional reference coordinates of the cutting point of the peony stem. By recording the position coordinates of the cutting point collected by the image recognition or laser ranging device before each picking starts and classifying them, the coordinate sensor configured on the picking tool is set to a sampling frequency of several times per second, so as to obtain a continuous sequence of the coordinates of its movement trajectory points. Then, the cutting point coordinates and the coordinates of the movement trajectory points of the picking tool are uniformly mapped to the same coordinate system to align its reference origin and the axis directions. In order to maintain accuracy, it is necessary to measure and record the installation angle and the center offset between the coordinate sensor and the picking tool, and correct it by adding or subtracting this offset to each of the collected trajectory point coordinates one by one. Then, coordinate normalization processing is carried out according to the standard length unit and reference axis established in advance. For example, a reference plane can be determined first to map the maximum coordinate value and the minimum coordinate value therein to between 0 and 1 respectively, and then the normalized coordinate value is calculated according to the ratio of the difference between each sampling point and the minimum value to the difference between the maximum value and the minimum value. If it is found that some trajectory points have a large difference from the previous and subsequent timestamps or the coordinate jump exceeds the pre-determined reasonable range, such as the range of ±30 cm, then mark this data as invalid or suspected abnormal, and it is necessary to check item by item in combination with the health status of the sensor and the coordinate values of other timestamps. If the continuous accumulation of abnormal records of the same type exceeds 5% in a short period of time, it is possible to check the position offset or connection stability of the sensor. After these checking operations are completed, all the coordinate information marked as normal is integrated into a high-precision valid data sequence, and then the cutting point coordinates are associated and compared with this sequence. If it is found that the sampling density of the trajectory points is significantly reduced in some time periods or duplicate data appears at the same timestamp, it is necessary to compare by time periods again and compare with the counter value stored in the sensor to confirm whether mis-picking or missed-picking has occurred during this time period. When it is confirmed that there are no more abnormalities, all the normal data is subjected to the final coordinate unification and identification processing to form a positioning data set.

[0103] The advantage of the formula lies in measuring the distance difference between the cutting point and the picking tool in the three-dimensional coordinate system in the form of a combination of the two-dimensional plane distance and the Z-axis scale factor. It not only takes into account the position deviation on the plane coordinates but also incorporates the influence of the Z-axis coordinate difference in the denominator, which can generate a more intuitive error measure for the situation where there is an obvious Z-axis coordinate difference.

[0104] The steps for obtaining the parameters are as follows: It is necessary to establish an observation system for the stem cutting point in the field peony planting area, record the three-dimensional coordinate information of the cutting point through the visual recognition component or depth sensor installed around the stem, and obtain the accurate value before the start of each picking process through a calibration program, and compare this value with the reference origin in the same coordinate system to confirm the rationality of the range. For example, if the actual measurement The vertical component is mostly concentrated between 0 cm and 200 cm. Then, a detection can be carried out at each sampling. If it is found that the value exceeds 200 cm or is lower than 0 cm, it is necessary to check whether it is lens distortion or abnormal acquisition. After time-sharing screening of thousands of data accumulated every day, a relatively concentrated and coherent numerical sequence can be obtained. For example, in one acquisition, most values fall between 100 cm and 150 cm.

[0105] The steps for obtaining the parameter are as follows: Through the same positioning system, obtain the coordinate values of the cutting points perpendicular to the axis direction, record the average or quantile values under multiple test periods, and compare them in combination with the ground height and the stem growth law. If a large number of values are observed to be abnormally large or small, it is necessary to re-examine the shooting angle and the optical parameters of the equipment, and correct them to the values consistent with the global coordinate reference or local reference. In order to provide more refined data accumulation for subsequent operations, different plant samples will also be selected for observation multiple times on the same day. After clustering the observation results, a typical interval can be obtained. By comparing these intervals with the actually recorded values, a relatively smooth coordinate sequence can be obtained.

[0106] The steps for obtaining the parameter are as follows: In the spatial dimension perpendicular to the and axis directions, record the height difference between the cutting point and the ground reference plane by means of structured light measurement or laser height difference measurement. If some plants are relatively short, their values will be small. When the observation period coincides with the plant growth period, it may also cause the values to show a slow upward trend. On-site, the plant samples in the same greenhouse are divided into a short-plant group, a medium-plant group, and a tall-plant group, and the value intervals are measured respectively. Generally, the short-plant group will be around 15 cm to 25 cm, the medium-plant group will be around 25 cm to 40 cm, and the tall-plant group will be around 40 cm to 60 cm. After completing multiple measurements and combining the elevation of the reference plane at each measurement, the can be established into a sequence and applied to actual calculations in combination with the corresponding timestamps.

[0107] The steps for obtaining the parameter are as follows: It is necessary to install a coordinate sensor on the picking tool at the real-time motion trajectory points, record the coordinate changes of the picking tool in the axis direction at high frequency, and compare them with the Compared with the axis coordinates, screen for values in the record that may exceed the motion limit of the device. If the normal coordinate range of the picking tool within the working area is from 0 cm to 180 cm, then for any value collected, once it is found that the value is greater than 180 cm or less than 0 cm, it is necessary to cross-check the timestamp and the attitude of the picking tool to confirm whether there is a collision or data loss. If no abnormal hardware reason is found, mark the corresponding data as invalid. When the proportion of invalid data does not exceed 3%, the operation can continue.

[0108] The steps for obtaining the parameter are as follows: Read the motion trajectory value of the picking tool in the axis direction and compare it with the origin of the device. During daily operation, a large number of instantaneous coordinates can be obtained by sampling multiple times per second. By summarizing the frequency of these instantaneous coordinates falling within a certain interval, the common motion range can be summarized. If the sensor calibration value in the axis direction is within the range of 0 cm to 180 cm, then observe whether the collected continuously falls within this range. If it exceeds this range during certain periods, it is necessary to check whether it matches the motion state of the rotation mechanism or the robotic arm of the picking tool. Finally, after removing the periods that do not match the machine motion, a chronological sequence is obtained.

[0109] The steps for obtaining the parameter are as follows: For the coordinate record of the picking tool on the axis, with the help of the height adjustment system of devices such as the cantilever robotic arm, compare the value of the sensor with the ground reference plane to determine its position change in the vertical direction. If the angle of the picking tool needs to be adjusted for some operations, the inclination data can be collected synchronously and converted. Compare the true height after inclination with the sensor reading. If the error is not greater than 1 cm, continue to use this value; otherwise, re - correct it. For all the records obtained by batch collection, they can be summarized and inspected by minute or hour to see whether the value exceeds the boundary during high - position or low - position operation periods.

[0110] Substituting the parameter into the calculation, the calibration error at this time is approximately 49.97. In the above unit, the larger the value, the more obvious the displacement difference between the picking tool and the cutting point of the peony stem. If greater than 60 is regarded as a significant deviation, this situation can be listed as a key investigation object during subsequent position accuracy analysis. If is lower than 30, it can be determined as the coordinate height matching interval. By calculating item by item A sequence for the overall position deviation can be obtained, laying a foundation for generating position calibration data subsequently.

[0111] Based on the calibration error obtained previously sequence, it is necessary to statistically analyze the deviation distribution at different time points and different position coordinates. For this purpose, first, within the same observation period, the numerical values are corresponded to the cutting point and the working state of the picking tool, and the corresponding peony varieties, plant heights, stem thicknesses, and surrounding environmental light are analyzed item by item to check for potential factors such as coordinate anomalies or robotic arm movement anomalies in the high section. Subsequently, combined with multiple pre-divisible error intervals such as 0 to 30, 30 to 60, 60 to 90, etc., using the frequency of the numerical values appearing in different intervals as the judgment criterion. If in more than three consecutive sampling periods is greater than 60 and the corresponding environmental or robotic arm drive parameters are not different from usual, then it is necessary to focus on checking whether the coordinate sensor or the joint movement of the end effector is interfered by the outside world. If most of the falls below 30, it means that most movements can maintain a relatively stable coordinate deviation. After such multi-angle comparisons, a precision level can be marked and recorded for each time period. If the average value is less than 20 within a certain period, it is marked as a high-precision section. If most of the landing points are concentrated between 20 and 40, it is marked as a medium-precision section. If it continuously exceeds 40 and there are concentrated high-value sections, it is marked as a low-precision section. After combining these paragraphs with precision marks, a detailed error distribution map can be generated. By aggregating the comparison situations of each record with the section where it is located, and based on the previous displacement data, the 、 、 deviations in the three-dimensional directions can be statistically analyzed respectively to form a more refined comparison table. Finally, the key sections with higher or lower precision are extracted and converted into traceable index numbers respectively, and a position accuracy analysis document is gradually established through successive superposition and sectional comparison to form position calibration data.

[0112] The steps for obtaining the trajectory optimization parameters are as follows:

[0113] Through the displacement calibration data and the movement trajectory of the picking end effector, displacement compensation operations are performed, and coordinate transformation is used to correct the error between the movement trajectory of the picking end effector and the calibration data to obtain the trajectory optimization parameters.

[0114] Specifically, the displacement calibration data obtained previously needs to be compared with the motion trajectory of the picking end effector. The coordinate systems of the two are synchronized at the same moment and divided into several motion segments. Within each segment, the three-dimensional coordinates of the end effector are corrected point by point and corresponding to the reference values in the calibration data. If it is found that the coordinates of the end effector continuously deviate by more than 2 cm in certain position directions, an error mark is made in the current time segment, and it is checked whether it is caused by external vibration or mechanical coupling. If it is confirmed to be a normal phenomenon, all the offsets in this segment are continued to be recorded. If it is found that the change in the command layer is inconsistent with the actual coordinate change, the drive frequency of the transmission mechanism and the correction times of the positioning link need to be traced. The speed of the transmission mechanism is split into a slow movement interval of 0.2 m / s to 0.5 m / s and a faster movement interval of 0.5 m / s to 1.0 m / s. The coordinate offset distribution in different intervals is observed, and then the extracted offsets are compared and analyzed with the previously statistically displacement calibration data to retrieve whether there are cases where features reappear. Through this segmented comparison, the influence of the inherent errors of the mechanical structure itself and the on-site random variables on the final position coordinates can be clarified. At the same time, the cycle load information of the current operation needs to be combined. For example, when the load is in the range of 5 kg to 10 kg, the offset mean value and the maximum offset amount during the multi-point alignment period are recorded. These values are summarized together with the segmented comparison results. For each time period, if the offset mean value is greater than 1 cm or the maximum offset amount is greater than 2.5 cm, it enters the in-depth investigation link. By comparing the rotation angles and movement paths of the end effector in the same period item by item, the coordinate conversion can be carried out by comparing its three-dimensional trajectory data with the calibration data to obtain the trajectory optimization parameters.

Claims

1. The automatic control-based mechanical picking motion trajectory optimization system for fresh cut peony flowers is characterized by: The system comprises: The air pressure acquisition module installs an air pressure sensor inside the cylinder to obtain the pressure value inside the cylinder and establish an air pressure regulation characteristic table; The force control module performs a correlation operation on the internal pressure value of the cylinder and the pressure output value of the picking tool according to the air pressure regulation characteristic table to obtain a force mapping value; the force mapping value is compensated with the pressure fluctuation value of the pneumatic actuator to establish a force regulation sequence; The displacement feedback module uses a displacement sensor to collect the displacement of the cylinder piston rod and the motion parameters of the pneumatic actuator according to the force adjustment sequence to generate displacement monitoring data; the displacement monitoring data is analyzed with the air pressure output instruction to establish a motion feature sequence; The trajectory optimization module collects the position coordinates of the cutting points of the peony stems and the coordinates of the motion trajectory points of the picking tools according to the motion feature sequence, and generates position calibration data; performs displacement compensation on the position calibration data and the motion trajectory of the picking end effector, and establishes trajectory optimization parameters; The steps for obtaining the force mapping value are as follows: According to the air pressure regulation characteristic table, standard data of the internal pressure value of the cylinder is extracted, pressure points within the working range of the picking tool are screened, and corresponding picking tool pressure output values ​​are sorted according to different pressure levels to obtain correlation data between the cylinder pressure and the picking tool pressure output; Based on the correlation data of the cylinder pressure and the picking tool pressure output, the force mapping value is calculated, and the calculation formula is: in, Map values ​​for velocity, is the internal pressure of the cylinder, is the pressure output value of the picking tool, is the distance between the cylinder and the picking tool, is the contact area between the cylinder and the picking tool, and They are the maximum and minimum values ​​of the cylinder pressure respectively.

2. The automatic control-based mechanical picking motion trajectory optimization system for fresh cut peony flowers according to claim 1 is characterized in that: The steps for obtaining the air pressure regulation characteristic table are: Install an air pressure sensor inside the cylinder, set the working parameters of the sensor, record the pressure values ​​in chronological order, store the pressure values ​​and detect the data integrity, eliminate abnormal pressure readings, and obtain the cylinder pressure data; Based on the cylinder pressure data, analyzing the fluctuation trend of the pressure value at different times, calculating the pressure change rate, and extracting the pressure value in the stable operation stage according to the pressure change rate to generate pressure characteristic data; According to the pressure characteristic data, the corresponding relationship between each characteristic pressure value and the internal state of the cylinder is summarized, and combined with the statistical distribution of each pressure point, a mapping relationship between the cylinder pressure and the operating state is constructed to establish a gas pressure regulation characteristic table.

3. The automatic control-based mechanical picking motion trajectory optimization system for fresh cut peony flowers according to claim 1 is characterized in that: The steps of obtaining the strength adjustment sequence are: Extract the pressure fluctuation data of the pneumatic actuator, analyze the variation range of the pressure fluctuation under different working conditions, and obtain the standard data of the pressure fluctuation of the pneumatic actuator; According to the standard data of the pressure fluctuation of the pneumatic actuator and the force mapping value, the compensation balance value is calculated, and the calculation formula is: in, To compensate for the balance value, Outputs the correlation data between cylinder pressure and picking tool pressure is the fluctuation range of the pressure output of the picking tool, are the pneumatic actuator parameters, is the pneumatic actuator pressure value, is the fluctuation characteristic coefficient, is the standard deviation of pressure fluctuation over time, is the pressure fluctuation value of the pneumatic actuator, is the maximum pressure value of the pneumatic actuator; Based on the compensated balance value, a force adjustment sequence is established.

4. The automatic control-based mechanical picking motion trajectory optimization system for fresh cut peony flowers according to claim 1 is characterized in that: The steps for obtaining the displacement monitoring data are as follows: According to the force adjustment sequence, combined with the initial position of the cylinder piston rod and the motion state of the pneumatic actuator, the displacement data of the cylinder piston rod is collected in real time through the displacement sensor, and the displacement changes at each moment are recorded to obtain the monitoring data of the cylinder piston rod displacement; Based on the monitoring data of the displacement of the cylinder piston rod and in combination with the motion parameters of the pneumatic actuator, the displacement law of the pneumatic actuator in each working stage is analyzed to generate displacement monitoring data.

5. The automatic control-based mechanical picking motion trajectory optimization system for fresh cut peony flowers according to claim 1 is characterized in that: The steps of acquiring the motion feature sequence are: Based on the displacement monitoring data, the motion characteristic value is calculated, and the formula is: in, is the motion characteristic value, is the air pressure output value, is the displacement data, is the standard deviation of the displacement data; Based on the motion feature values, the motion characteristics of the cylinder are extracted to form a motion feature sequence.

6. The automatic control-based mechanical picking motion trajectory optimization system for fresh cut peony flowers according to claim 1 is characterized in that: The steps for obtaining the position calibration data are as follows: The coordinates of the points on the picking tool's motion trajectory are collected in real time, and the coordinates are normalized based on the position coordinates of the cutting points on the peony stems, invalid data are excluded, and a positioning data set is obtained; Based on the motion feature sequence and the position data set, the calibration error is calculated, and the formula is: in, is the calculated calibration error, , , are the coordinates of the cutting points of the peony stem in three-dimensional space, , , is the coordinates of the motion trajectory points of the picking tool; Based on the calibration error, position accuracy analysis is performed to generate position calibration data.

7. The automatic control-based mechanical picking motion trajectory optimization system for fresh cut peony flowers according to claim 1 is characterized in that: The steps for obtaining the trajectory optimization parameters are as follows: The displacement compensation operation is performed through the position calibration data and the motion trajectory of the picking end effector, and the error between the motion trajectory of the picking end effector and the calibration data is corrected by using coordinate transformation to obtain the trajectory optimization parameters.

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