Paeonia lactiflora fresh cut flower mechanical picking motion trail optimization system based on automatic control

Abstract

The invention relates to the technical field of non-electrical variable control, in particular to an automatic-control-based mechanical picking motion trail optimization system for fresh Chinese herbaceous peony cut flowers, which comprises an air pressure acquisition module, an air pressure sensor mounted in an air cylinder, an air cylinder internal pressure value obtained and an air pressure regulation characteristic table established. In the invention, an air pressure acquisition and feedback mechanism enables the picking tool to adjust the force in real time, and the unbalanced force caused by air pressure fluctuation is avoided. The stability in the picking process is improved, the contact accuracy of the picking strength and the target object is also ensured, and the physical damage to the Chinese herbaceous peony is reduced. In the picking process, by dynamically adjusting the position and track of the picking tool, the deviation can be corrected in real time, it is guaranteed that the tool moves precisely to be in butt joint with a target object, and errors in operation are reduced. In addition, through the combination of displacement monitoring and air pressure output instructions, the movement track can be automatically compensated in the movement process, and the picking efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of non-electric variable control, and in particular to an automatic control-based mechanical picking motion trajectory optimization system for fresh cut peony flowers. Background Art

[0002] Non-electric variable control technology mainly refers to controlling the variable changes of the system through mechanical or physical means without the need for electric drive. This type of technology usually relies on changes in physical parameters such as hydraulics, pneumatics, mechanical devices, temperature, pressure, etc. for control and regulation. In these control systems, signals and control methods are mostly driven by mechanical input or natural environmental changes, such as the thrust of hydraulic drive, the power output of air pressure regulation, or the physical reaction caused by temperature changes. The Peony Fresh Cut Flower Mechanical Picking Motion Trajectory Optimization System is a system designed to optimize the peony fresh cut flower picking process through automatic control technology.

[0003] In the prior art, since the picking trajectory and tool position are not adjusted in real time, the tool may not be able to 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 tool movement in real time, resulting in low operating efficiency. Therefore, improvements are needed. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings in the prior art and to propose a mechanical picking motion trajectory optimization system for fresh cut peony flowers based on automatic control.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: the mechanical picking motion trajectory optimization system of fresh cut peony flowers based on automatic control 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; the position calibration data and the motion trajectory of the picking end effector are displacement compensated to establish trajectory optimization parameters.

[0006] Preferably, the steps of 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.

[0007] Preferably, the steps of obtaining the force mapping value are: 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.

[0008] Preferably, the steps of obtaining the force 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, It is the correlation data between cylinder pressure and picking tool pressure output. 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.

[0009] Preferably, the steps of acquiring the displacement monitoring data are: 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.

[0010] Preferably, 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.

[0011] Preferably, the steps of acquiring the position calibration data are: 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.

[0012] Preferably, the steps of obtaining the trajectory optimization parameters are: The displacement compensation operation is performed through the displacement 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.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, the air pressure collection and feedback mechanism enables the picking tool to adjust the force in real time to avoid uneven force caused by air pressure fluctuations. The stability during the picking process is improved, and the contact accuracy between the picking force and the target object is guaranteed, reducing 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 that the tool moves accurately and docks with the target object, reducing errors in the operation. In addition, by combining displacement monitoring with air pressure output instructions, the motion trajectory can be automatically compensated during the movement process, improving the picking efficiency, reducing the crop loss caused by deviation, and optimizing energy utilization and operating accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with 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 intended to limit the present invention.

[0016] See also Figure 1 The present invention provides a technical solution: a mechanical picking motion trajectory optimization system for fresh cut peony flowers based on automatic control 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 associates the internal pressure value of the cylinder with the pressure output value of the picking tool according to the air pressure regulation characteristic table to obtain the 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 command 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; the position calibration data is displacement compensated with the motion trajectory of the picking end effector to establish trajectory optimization parameters.

[0017] The steps to obtain 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, analyze the fluctuation trend of the pressure value at different times, calculate the pressure change rate, and extract 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. Combined with the statistical distribution of each pressure point, the mapping relationship between cylinder pressure and operating state is constructed, and the air pressure regulation characteristic table is established.

[0018] Specifically, install an air 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 0MPa to 2MPa based on the evaluation of the maximum bearing pressure range of the equipment. This range is derived from experience after combining the ultimate pressure of 2.2MPa marked on the equipment nameplate and leaving a safety margin. When recording the pressure values, determine whether the collected values ​​exceed the range of 0MPa to 2MPa one by one. If it is less than 0MPa or greater than 2MPa, it is considered abnormal. The abnormal data is reconfirmed manually or automatically and marked in a separate abnormal record set. In order to check the data integrity, it is necessary to check the same time period. Whether the number of collections meets the requirement of ten times per second. For example, if only 8 times or less than 8 times are collected in a certain second, it is regarded as missing data and included in the missing record sequence. The missing records can be interpolated according to 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 in the same time period on the same day. If it is found that the proportion of abnormal records or missing records in certain time periods exceeds 5% continuously, the sensor status and related connection lines can be further checked. At the same time, the working parameters of the sensor are re-calibrated and the sensitive elements are replaced when necessary. All records that are finally confirmed to be valid maintain the original order in the time series and are associated with the corresponding timestamps, and finally form continuous and valid cylinder pressure data to obtain cylinder pressure data.

[0019] Based on the cylinder pressure data, the fluctuation trend of the pressure value at different times is analyzed. First, the cylinder pressure data is divided into multiple time segments according to the hourly or smaller intervals within a day, and the continuous pressure changes are differentially calculated in each time segment to obtain the pressure change rate. In order to determine whether the pressure value is in a relatively stable operation stage, it is necessary to compare the change rate in each time segment with a predetermined fluctuation threshold. The fluctuation threshold can be set to 0.06MPa / s based on the 0.05MPa / s recommended in the equipment manual and field experience evaluation. When most of the differential results in a certain time segment are less than 0.06MPa / s, it is determined that the period can be regarded as a stable operation stage. If some of the differential results exceed 0.06 continuously, the pressure value will be increased or decreased by 1.08MPa / s. MPa / s and the duration of this phenomenon reaches 10 seconds or more, the period can be marked as a fluctuation stage. In order to give statistical quantitative data to the stable stage, the arithmetic mean of the minimum pressure value and the maximum pressure value in the stable stage can be taken as the representative value of this stage, so as to obtain the comprehensive pressure index of the stable operation stage. If the data of some time segments are unevenly distributed or the fluctuation is too large, they are classified as special time periods and stored and excluded as appropriate in subsequent stages. After calculating and judging the time segments one by one, the representative values ​​of all stable stages are stored in a feature array, and then the most common pressure ranges of each time period are further sorted out with the feature array. Finally, the statistical results that can characterize the stable pressure situation of the equipment in different working periods are summarized to generate pressure characteristic data.

[0020] According to the pressure characteristic data, the corresponding relationship between each characteristic pressure value and the internal state of the cylinder is summarized. First, the pressure characteristic data is divided into several categories according to factors such as working time, ambient temperature, and equipment load. The frequency of occurrence of characteristic pressure values ​​in each category is counted 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 related to 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 high-frequency characteristic pressure values ​​in each category as the main reference. If some characteristic pressure values ​​are significantly larger or smaller in duration than other values, they need to be compared again. For the abnormal record set, confirm that the characteristic value is not caused by collection abnormalities 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 matched 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 items in the matrix are arranged in order from the lowest pressure to the highest pressure. Finally, on this basis, state identifiers are set for different pressure areas. If extreme values ​​greater than 2MPa or less than 0MPa appear, they are separately marked and classified into the abnormal interval. After completing the sorting of all characteristic values ​​and the classification of corresponding states, an air pressure regulation characteristic table is established.

[0021] The steps to obtain the intensity mapping value are: 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; 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: 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.

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] The steps for obtaining the parameters are as follows: using a contact surface measuring instrument to obtain the effective area of ​​the contact area between the cylinder piston end and the picking tool, and recording the dynamic changes of the contact area in each time period. If it is found that the contact area suddenly increases or decreases, it is checked according to the shape and angle of the clamping part of the picking tool. The specific value can be obtained by dividing several small areas, measuring their geometric dimensions and then accumulating them. If the measurement process shows that the area is mostly maintained at around 0.004 square meters, 0.004 square meters can be used as the value used in subsequent calculations. By continuously accumulating measurement data and performing statistics, a more detailed S value distribution can be obtained.

[0028] and The parameter acquisition step is to sort all cylinder internal pressure data within a complete working cycle from small to large, record the beginning and end of the sequence, and take the maximum value of the remaining pressure values ​​after excluding all invalid pressure readings as And take the minimum value as For example, if the cylinder pressure monitoring value fluctuates between 0.1MPa and 2.0MPa for ten consecutive hours, and after eliminating several periods of abnormal readings, the minimum pressure value is 0.12MPa and the maximum pressure value is 1.95MPa, then 1.95MPa is acceptable. 0.12MPa can be taken. In actual use, the range can be re-evaluated in combination with data over a longer period of time and the two indicators can be updated when necessary.

[0029] Substitute the velocity mapping value calculated by the parameter It is about 58.27 and is relatively high under the current measurement and calculation conditions. When it is greater than 50, it means that the force exerted by the picking tool at the corresponding moment is greater. If the value is less than 20, it means that the force is smaller. For the intermediate range, the appropriate picking force range can be determined in combination with the specific working environment, and the internal pressure of the cylinder or the output of the picking tool can be further adjusted in the subsequent links.

[0030] The steps to obtain the intensity 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 pressure fluctuation of pneumatic actuator and the force mapping value, the compensation balance value is calculated. The calculation formula is: in, To compensate for the balance value, It is the correlation data between cylinder pressure and picking tool pressure output. 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 compensation balance value, a velocity adjustment sequence is established.

[0031] Specifically, based on the pneumatic actuator operation information obtained previously, it is first necessary to classify and record the pressure fluctuations of the pneumatic actuators under different working conditions, and perform detailed statistics according to daily or hourly time intervals. Each record must be compared with the pre-set working range of 0MPa to 2MPa. If the pressure value of the pneumatic actuator in the corresponding time period exceeds 2MPa or is lower than 0MPa for three consecutive times, the sensor readings of the time period must be checked and additional inspections must be performed to confirm possible leakage channels or overload conditions. After accumulating all valid records, the pressure fluctuation ranges of each time period are grouped. For example, the time period when the pressure fluctuation exceeds 0.2MPa is regarded as a high fluctuation range, the time period when the fluctuation is between 0.05MPa and 0.2MPa is regarded as a medium fluctuation range, and the time period when the fluctuation is lower than 0.05MPa is regarded as a low fluctuation range. These thresholds are derived from the limit pressure marked on the equipment nameplate and are obtained after repeated comparison with the actual test data. The intervals are analyzed second by second or minute by minute, and their duration is recorded and linked to factors such as workload, solenoid valve switching speed, and ambient temperature. After sorting them out item by item, a more accurate fluctuation distribution is obtained. To ensure consistent statistical caliber, all acquisition devices need to be uniformly time-stamped and aligned, and the readings at the same time are checked through a verification program to see if they are synchronized. If data is lost, the missing data are interpolated by comparing the values ​​of adjacent time periods within a short time range, and the supplemented data are then included in the overall statistical process. After analyzing all time periods, the fluctuation data corresponding to each working condition are compared and a pressure fluctuation curve is drawn. The overall standard deviation and average fluctuation amplitude are extracted under different working conditions by means of segmented calculation and comparison of the curve. At this time, combined with the temperature, cylinder load, and related operating hours of the corresponding interval, the most common fluctuation amplitudes and typical intervals are screened and determined one by one, so that these intervals are defined as reference values ​​for standard data, and standard data for pressure fluctuations of pneumatic actuators are obtained.

[0032] The benefit of the formula is that it integrates the key quantities in the overall operation of the pneumatic actuator, including the correlation information between the cylinder pressure and the picking tool, and also takes into account multiple factors such as the pressure fluctuation range, the actuator's own parameters, and the upper and lower limits of the maximum pressure. It has important measurement value for the subsequent establishment of a force adjustment sequence.

[0033] The steps for obtaining parameters are as follows: the associated data of cylinder pressure and picking tool pressure output need to be segmented and counted, and the timestamp alignment degree is required to be within 0.1 second in the same second. The successfully matched records are marked with the same index and summarized according to different loads and ambient temperature levels. The most frequently occurring pressure value of the picking tool output in a certain period of time is stored together with the corresponding cylinder internal pressure value, and then the average or median value within the period of time can be taken as If higher precision is required, the values ​​of the subdivided segments can be calculated within 1 minute or less, and finally a series of time periods can be obtained. By comparing the performance of multiple periods in a complete operation cycle, the sections that best meet the operation requirements are selected to obtain one or more typical For example, during a ten-hour operation period, if the cylinder pressure and the picking tool pressure output average value measured after all records match the index more than 99% is 1.2MPa, it can be recorded as the value of this period. .

[0034] The parameter acquisition steps are as follows: the pressure output of the picking tool under different loads and movement speeds is recorded in real time, and the data is collected at a frequency of ten times per second. The difference between the maximum and minimum values ​​in the same time window is recorded as the fluctuation range, and the median or average value of multiple repeated measurements is selected as , if the fluctuation range of each period in the test is kept between 0.3MPa and 0.5MPa for 8 consecutive hours, the average value of 0.4MPa can be taken as If the measured value exceeds 0.5MPa for a short period of time, it is necessary to mark the possible abnormal condition and find out the specific cause in the subsequent analysis, so as to It can truly reflect the pressure fluctuation amplitude of the picking tools.

[0035] The steps for obtaining parameters are as follows: the model, structural characteristics, and built-in valve switching characteristics of the pneumatic actuator need to be checked, and the impact of the pressure response speed of the pneumatic actuator in loading and unloading actions on the overall performance is measured during multiple cycles. Multiple operation records are summarized, for example, during 300 hours of continuous operation, according to the response time or response efficiency of pressure regulation per hour, and then the data is compared with the sampling frequency comparison chart recommended in the equipment manual, and the key indicators reflecting the characteristics of the pneumatic actuator are screened out, and the indicators are quantified and recorded in the form of formulas or tables. , if calculated This value is continuously valid after measurement in the same model of equipment. It may fluctuate slightly with the aging of the equipment but generally does not exceed ±0.05.

[0036] The parameter acquisition step is to extract the average pressure value at a certain moment or a certain period of time from the working pressure distribution of the pneumatic actuator under actual working conditions, and regard this value as the current pressure level of the actuator. Since pneumatic actuators usually work in the range of 0MPa to 2MPa, the pressure values ​​recorded per second can be averaged during the on-site collection period. If there is no obvious abnormality during this period and the data integrity is above 98%, the calculated average value can be used as For example, if the average pressure recorded during a 2-hour operation is 1.3 MPa, then .

[0037] The steps to obtain parameters are to extract information through special statistics of fluctuation characteristics in the past or current equipment monitoring process, especially to summarize the pulsation frequency of the pneumatic actuator, the instantaneous impact value when the airflow in the pipeline is switched, etc. for multiple days or shifts, and then calculate the fluctuation coefficient of each stage and compare its distribution, select the most representative interval, and compare the fluctuation degree in this interval with the conventional operating specifications. If a stable value is obtained after repeated tests, it can be determined as For example, after half a month of data analysis, It is set to 0.9 as the fluctuation characteristic coefficient during the execution process. If the equipment structure or operating speed changes significantly in actual work, this value must be re-measured in a timely manner.

[0038] The steps for obtaining the parameters are as follows: first, calculate the mean of the pressure readings of the pneumatic actuator within the same time period, then square the difference between each reading and the mean, sum it up and divide it by the number of samples, and finally take the square root to get the standard deviation of the time period. If the recording period is 1 hour and the pressure value is collected ten times per second, 36,000 data can be obtained within 1 hour. Calculate the average value of these data, perform variance calculation and take the square root, and you can get For example, after calculation, it is found that the standard deviation of this period is 0.08MPa, then , the same calculation can be performed on the fluctuations in different time periods to form a standard deviation data series.

[0039] The parameter acquisition step is to differentiate the instantaneous pressure reading of the pneumatic actuator when the load is switched, stopped or accelerated from the adjacent steady-state value, and continuously observe the offset of this differential value within a certain time range, and record the extreme value as To indicate the maximum instantaneous fluctuation amplitude under the current operating conditions, in order to ensure the reliability of the value, the differential curve can be compared in multiple repeated runs to find the most common maximum fluctuation range. If most of the differential peaks in a certain operating environment are between 0.2MPa and 0.3MPa, the average value of 0.25MPa can be extracted and recorded as .

[0040] The steps for obtaining the parameters are to combine the maximum load value given in the manual of the pneumatic actuator and the peak value record of the previous multi-stage pressure test data. Generally, the value is between 2.0MPa and 2.5MPa. It is necessary to pay attention to the equipment's ultimate bearing capacity in multiple tests and record the highest value of each test. If the upper limit of the safety range is confirmed to be 2.2MPa and the actual monitoring peak has reached 2.1MPa, then , to characterize the maximum pressure value of the current equipment and continuously monitor it during subsequent operations.

[0041] Substitute the parameters to calculate the current compensation balance value It is about 0.3498. If similar values ​​are obtained in multiple operation records, it means 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 If it rises to above 0.6, it can be judged as a large fluctuation state, and it is necessary to readjust the force configuration based on the previously obtained correlation data of the cylinder pressure and the pressure output of the picking tool. If it is significantly lower than 0.2, it means that the overall fluctuation is small, and other factors can be further observed to ensure the matching of the overall operation process.

[0042] After obtaining the compensation balance value, it is necessary to The values ​​are recorded continuously and compared with a configurable monitoring period, for example every ten minutes or every hour. The data is sorted from small to large and the intervals with obvious differences are marked. Based on the previously established correlation indicators, if some If the pressure is higher than 0.6 or lower than 0.2, the corresponding cylinder pressure and the pressure output relationship of the picking tool are grouped separately to check whether the equipment structure or operation process needs to be fine-tuned. The interval maintains the original input parameters. After completing this overall summary, it is necessary to The numerical values ​​are bundled with the operation scene information and stored to provide control samples for subsequent multiple shifts or multiple days of continuous operation. When the record scale is expanded to a certain extent, it is possible to observe the same machine under different seasons, loads or opening and closing frequencies. Is there any abnormality in data distribution? Once it is found that the data is under the same load and similar ambient temperature, If the data distribution exceeds the preset safety range of 0.2 to 0.6 continuously, it is necessary to compare the earlier operation history to determine whether the actuator hardware is aging or the cylinder is excessively worn. After the data is reasonable, its sequence is arranged step by step according to the timeline or job batches. This can provide an accurate basis for subsequent force fine-tuning operations, and make slight corrections to the actuator pressure under different shifts or different task scheduling. Finally, after sorting and comparing, these correction values ​​are recorded one by one to establish a force adjustment sequence.

[0043] The steps for obtaining 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 cylinder piston rod displacement and combined 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.

[0044] Specifically, according to the force adjustment sequence obtained previously, 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 to the pre-calibrated reference starting point when starting recording, and check the alignment of the reference point and the displacement sensor. Perform position data acquisition every 0.01 seconds or other appropriate sampling frequency, read the displacement of the cylinder piston rod relative to the initial position at that moment, and compare it with the pre-established safe motion range of 0cm to 30cm. This range is determined by referring to the maximum stroke design of cylinders of the same specifications and combining with on-site measurement results. If the displacement appears to be less than 0cm or greater than 30cm in a single acquisition result, it will be regarded as an abnormal reading and marked for subsequent investigation. In daily operation, if the abnormal reading continues to appear for more than 5% of the total acquisition times, then 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 time, and keep the confirmed and processed records in the time series for subsequent analysis. In order to divide the different operation stages, the current state mark of the pneumatic actuator can be used to distinguish, for example, the speed higher than 1m / s is the rapid extension stage, and the speed lower than 0.3m / s is the slow retraction stage. These different stages are summarized and compared in sections. When the difference between the maximum and minimum displacements in the same stage exceeds 2cm, it can be associated with the force adjustment sequence of the same stage to determine whether the control instructions need to be optimized again. After completing the reading and comparison of all 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 cylinder piston rod displacement.

[0045] Based on the monitoring data of the displacement of the cylinder piston rod and the motion parameters of the pneumatic actuator, it is necessary to first synchronize the displacement collected per second in the same operation cycle with the load pressure value, extension and retraction speed and other information of the pneumatic actuator, and then statistically analyze the displacement change curve over time for the two different action processes of extension and retraction, and check whether there is a sudden change in the displacement curve under the same action. If the displacement jump collected five times in a short period of time exceeds 1cm, it can be marked as a violent fluctuation section. The previously determined load pressure range of 0MPa to 2MPa is used for comparison with the violent fluctuation section. If the corresponding pressure records are concentrated in the high load interval of 1.5MPa to 2MPa, it means that this action stage belongs to a high load state. By comparison, multi-dimensional analysis can also be performed in combination with the extension and retraction speed. For example, the speed can be divided into 0.2m / s to 0.5m / s as a low speed interval and 0.5m / s as a high speed interval. s to 1m / s is the medium speed interval, and greater than 1m / s is the high speed interval. The displacement fluctuations in each interval are classified. If there is a drastic displacement fluctuation in the medium speed interval, it is necessary to further check the force adjustment sequence to see whether there is a large-scale force command output during this period. The displacement distribution range in different stages can be clearly defined based on repeated data for many days. If it is found that the displacement exceeds the established deviation threshold of 2cm for multiple times under certain specific working conditions, maintenance and investigation must be carried out. This threshold is determined by the average plus 3 times the standard deviation selected through empirical methods after statistics of all displacement distributions in daily operation. If the displacement deviation exceeds 2cm for three consecutive periods of time, it is considered that the displacement law of this working condition is obviously abnormal. After checking all the records, the displacement average value, fluctuation range and sampling number in each stage can be seen. These data are integrated into a complete comparison sequence to generate displacement monitoring data.

[0046] The steps for obtaining the motion feature sequence are: Based on the displacement monitoring data, the motion characteristic value is calculated using the formula: 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.

[0047] Specifically, the benefit 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 between the air pressure output value and the displacement data in the denominator, a comprehensive indicator for measuring the characteristics of pneumatic motion is formed. In practical applications, the dynamic coordination of pressure and displacement can be taken into account at the same time, making the subsequent evaluation of the overall motion law of the cylinder more targeted.

[0048] The parameters can be obtained by installing a pressure detection device on the cylinder air supply pipeline to record the air pressure output value several times per second, and compare the collected values ​​with the working range of 0MPa to 2MPa indicated on the equipment nameplate one by one. If the collected data is between 0MPa and 2MPa, it can be regarded as valid. The value and its timestamp are recorded. If the collected values ​​exceed the range for many times, they can be marked as hardware or environment abnormalities and investigated, and finally a time-limited data is formed without large-scale abnormalities. For example, in an 8-hour period, 28,800 valid pressure readings are recorded, and The sequence ranges from 1.0MPa to 1.8MPa, and each line corresponds to the displacement data at the same timestamp.

[0049] The steps for obtaining the parameters are as follows: a displacement sensor matching the cylinder piston stroke needs to be set up and the acquisition frequency per second is the same as that of the pressure detection device. The piston extension and retraction position recorded per second is compared with the initial reference point to obtain the displacement value at the current moment. These displacement values ​​are sorted into a sequence arranged in chronological order. If the displacement is monitored to be more than 30 cm or less than 0 cm, it can be regarded as exceeding the normal movement stroke and an abnormal index is recorded. If the abnormal index accounts for no more than 5% of the entire observation period, it is considered that the abnormal index in the period is not greater than 5%. The values ​​are available. For example, if the displacement values ​​detected during a regular shift mainly fluctuate between 0 cm and 25 cm, these values ​​are arranged according to the timestamp to form Sequence, as mentioned above The sequences correspond one to one.

[0050] The steps for obtaining the parameters are as follows: first, the standard deviation of the displacement data sequence collected above is calculated within a number of fixed time periods, and then the standard deviation is determined according to the degree of dispersion of the displacement distribution within the same time period. For example, in the process of calculating the standard deviation of 3600 displacement data in a certain 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 it, divide it by 3600, and then take the square root to get the displacement standard deviation of the hour, which is regarded as If the on-site statistical results show that the standard deviation of the piston displacement within that hour is 2.0 cm, then it is recorded as If you need to reflect the degree of motion dispersion over a longer period of time, you can continue to count the displacement data for multiple hours or days and finally select a representative standard deviation value for use as .

[0051] Substituting the parameters into the calculation, the degree of coordination between the current air pressure output value and the displacement data reaches about 117.6 under the specified unit conversion. If it is restored to the original measurement unit system, it is necessary to restore the value again in combination with the specific conversion factor. The above steps can be repeated for different shifts or working periods to calculate different ,like If it is greater than 100, it may indicate that the pressure output at a certain moment is significantly higher than the actual displacement requirement. Between 50 and 80, it is in a relatively matching range. If it is lower than 30, it indicates that the displacement change or air pressure output is obviously too small during the corresponding period. Once the resulting sequence is calculated, a more in-depth analysis of the motion characteristics can be performed.

[0052] Based on the motion feature values ​​obtained above, The cylinder extension and retraction speed, load pressure range and piston movement direction in the same period are compared with each other, and timestamps are added to these data. By continuously tracking these identifiers, the distribution of characteristic values ​​in different operation stages can be clearly identified. If there are If there is a large difference in the change, check whether the cylinder extension speed of this batch and the aforementioned air pressure output value are within the established range. For example, the speed can be pre-divided into a range of 0.2m / s to 0.5m / s and the pressure can be pre-divided into a range of 0.8MPa to 1.6MPa. If a large number of If the cylinder is concentrated at a higher or lower level, the load conditions at the specific operation time should be compared to see if there is any fluctuation caused by additional weight or rapid switching. After recording these inspection results item by item, a staged summary of the cylinder motion characteristics is formed. Finally, according to the records of each time period, The values ​​are compared horizontally with the corresponding speed and pressure comparison tables, and the relatively stable intervals are extracted and marked as typical sections. The sections that are too high or too low are marked as abnormal sections or special sections. When the daily operations accumulate to a certain scale, all records can be grouped and key sections can be extracted for comparison under different loads, speeds and external ambient temperatures. If the performance is similar in multiple operations, the data of these sections can be used as a reference in subsequent scheduling, and the numerical distribution of motion features in key time periods can be obtained by extracting and sorting them, and finally connected together to form a complete motion feature sequence.

[0053] The steps to obtain position calibration data are: 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 position data set, the calibration error is calculated using the formula: 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.

[0054] Specifically, when the coordinates of the picking tool's motion trajectory points are collected in real time, it is necessary to determine in advance the three-dimensional reference coordinates of the peony stem cutting point, and by recording and classifying the cutting point position coordinates collected by the image recognition or laser ranging device before each picking, 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 its motion trajectory point coordinates, and then the cutting point coordinates and the picking tool's motion trajectory point coordinates are uniformly mapped to the same coordinate system to align their reference origin and coordinate axis direction. In order to maintain accuracy, it is necessary to measure the installation angle and center offset between the coordinate sensor and the picking tool and record the offset, and correct the offset by adding or subtracting the offset one by one to the collected trajectory point coordinates, and then perform coordinate normalization processing based on the pre-established standard length unit and reference axis. For example, a reference plane can be first determined to correspond the maximum coordinate value and the minimum coordinate value therein to between 0 and 1, respectively, and then the coordinates of each sampling point relative to the reference plane can be normalized. The normalized coordinate value is calculated by the ratio of the difference between the minimum value and the difference between the maximum value and the minimum value. If it is found that some trajectory points differ greatly from the previous and subsequent timestamps or the coordinate jump exceeds a predetermined reasonable range such as ±30cm, the data is marked as invalid or suspected abnormal, and it is necessary to check the coordinate values ​​of the sensor health status and other timestamps one by one. If the same type of abnormal records accumulate for more than 5% in a short period of time, the sensor position offset or connection stability can be checked. After these troubleshooting operations are completed, all coordinate information marked as normal is integrated into a high-precision valid data sequence, and then the cutting point coordinates are associated with the sequence for comparison. If it is found that the sampling density of trajectory points is significantly reduced in some time periods or duplicate data appears in the same timestamp, it is necessary to compare again in different time periods and compare with the counter value stored in the sensor to confirm whether there is any mis-sampling or omission in the time period. When it is confirmed that there are no more abnormalities, all normal data are finally unified and marked to form a positioning data set.

[0055] The benefit of the formula is that it measures the distance difference between the cutting point and the picking tool in the three-dimensional coordinate system through 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 produce a more intuitive error measurement for situations where there is a significant Z-axis coordinate difference.

[0056] The steps for obtaining the parameters are as follows: an observation system needs to be established for the stem cutting points in the actual peony planting area, and the three-dimensional coordinate information of the cutting points needs to be recorded through the visual recognition components or depth sensors installed around the stems, and accurate calibration procedures need to be performed before each picking process begins. The value is compared with the reference origin in the same coordinate system to confirm the rationality of the range. For example, if the actual measurement is If the azimuth component is mostly concentrated between 0cm and 200cm, a test can be performed at each sampling. If it is found to be more than 200cm or less than 0cm, it is necessary to check whether it is lens distortion or acquisition abnormality. After time-sharing screening of thousands of data accumulated every day, a relatively concentrated and coherent set of A sequence of values, such as most of the Falls between 100cm and 150cm.

[0057] The steps to obtain the parameters are as follows: The same positioning system obtains perpendicular to The coordinate values ​​of the cutting points in the axial direction are recorded, and the average or quantile values ​​under multiple test periods are recorded, and compared with the ground height and the growth law of the stems. If a large number of If the value is abnormally large or small, it is necessary to review the shooting angle and equipment optical parameters again and correct them to values ​​consistent with the global coordinate reference or local reference. In order to provide more detailed data accumulation for subsequent operations, different plant samples will be selected for observation multiple times on the same day, and the observation results will be clustered to obtain typical By comparing these intervals with the actual recorded values, a smoother line can be obtained. Coordinate sequence.

[0058] The steps to obtain the parameters are as follows: and In the spatial dimension perpendicular to the axis direction, the height difference between the cutting point and the ground reference plane is recorded by structured light measurement or laser height difference measurement. If some plants are relatively short, then their The value will be too small, and it may also cause The value showed a slowly increasing trend. The plant samples in the same greenhouse were divided into short plant group, medium plant group and tall plant group, and the values ​​were measured respectively. The value range is generally around 15cm to 25cm for the short plant group, around 25cm to 40cm for the medium plant group, and around 40cm to 60cm for the tall plant group. After completing multiple measurements and combining the reference plane elevation at each measurement, the Create a sequence and apply it to actual calculations with corresponding timestamps.

[0059] The steps for obtaining the parameters are as follows: a coordinate sensor needs to be installed on the real-time motion trajectory of the picking tool. The coordinate changes in the axis direction are recorded at high frequency and compared with the cutting point Compare the axis coordinates and screen the values ​​in the records that may exceed the movable limit of the equipment. The coordinate range is 0cm to 180cm. Once the value is found to be greater than 180cm or less than 0cm, it is necessary to cross-check the timestamp and the picking tool posture to confirm whether a collision or data loss has occurred. If no abnormal hardware cause is found, the corresponding data will be marked as invalid. When the proportion of invalid data does not exceed 3%, the calculation can continue.

[0060] The steps to obtain the parameters are: read the picking tool in The motion trajectory value in the axis direction is compared 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 in a certain interval, common Range of motion, if The sensor calibration value in the axial direction is between 0cm and 180cm. Whether it continues to fall within this range. If some time periods exceed this range, it is necessary to check whether it matches the motion state of the picking tool rotation mechanism or the robot arm. Finally, after eliminating the time periods that do not match the machine movement, a chronologically arranged list is obtained. sequence.

[0061] The steps for obtaining the parameters are as follows: The coordinates on the axis are recorded, and the sensor is adjusted by the height adjustment system of the cantilever robot arm. The value is compared with the ground reference plane to determine its vertical position change. If some operations require adjusting the picking tool angle, the inclination data can be collected and converted synchronously to convert the actual value after inclination into the actual value. Compare the height with the sensor reading. If the error is not greater than 1cm, continue to use this value. Otherwise, re-calibrate. Records can be summarized and checked by minute or hour to see if there are high or low operating periods. Whether the value is out of bounds.

[0062] Substituting the parameters into the calculation, the calibration error is about 49.97. In the above units, the larger the value, the more obvious the displacement difference between the picking tool and the cutting point of the peony stem. A value greater than 60 is considered a significant deviation and can be listed as a key investigation target in subsequent position accuracy analysis. If the value is less than 30, it can be judged as a coordinate high matching interval. A sequence of overall position deviation can be obtained, laying the foundation for the subsequent generation of position calibration data.

[0063] 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. To do this, firstly The values ​​correspond to the cutting points and the working status of the picking tools. The corresponding peony varieties, plant heights, stem thicknesses and surrounding ambient light are analyzed item by item to check whether the cutting points are high or low. Whether there are potential factors of abnormal coordinates or abnormal robot arm movement in the segment, then combine multiple error intervals that can be pre-divided such as 0 to 30, 30 to 60, 60 to 90, etc. The frequency of occurrence of values ​​in different intervals is the judgment standard. If the value appears in three or more consecutive sampling periods, If the value is greater than 60 and the corresponding environment or robot drive parameters are the same as usual, it is necessary to focus on checking whether the coordinate sensor or end effector joint activity is disturbed by the outside world. If it falls below 30, it means that most actions can maintain a relatively stable coordinate deviation. After this multi-angle comparison, an accuracy level can be marked for each time period and recorded. If the average value is less than 20, it is marked as a high-precision segment. If most of the points are concentrated between 20 and 40, it is marked as a medium-precision segment. If it exceeds 40 continuously and there are high-value segments concentrated, it is marked as a low-precision segment. By combining these precision-marked segments, a detailed error distribution map can be generated. The comparison between each record and the segment is aggregated. Based on the aggregation result and combined with the previous displacement data, , , The deviations in the three-dimensional directions are counted separately to form a more detailed comparison table. Finally, the key sections with higher or lower accuracy are extracted and converted into traceable index numbers. Through successive superposition and segmented comparison, the position accuracy analysis document is gradually established to form the position calibration data.

[0064] The steps to obtain trajectory optimization parameters are: Displacement compensation calculation is performed through displacement calibration data and the motion trajectory of the picking end effector. Coordinate transformation is used to correct the error between the motion trajectory of the picking end effector and the calibration data to obtain the trajectory optimization parameters.

[0065] Specifically, the displacement calibration data obtained previously needs to be compared with the motion trajectory of the picking end effector, and the coordinate systems of the two need to be synchronized at the same time and divided into several motion segments. In each segment, the three-dimensional coordinates of the end effector are corrected point by point and correspond to the reference values ​​in the calibration data. If it is found that the coordinates of the end effector deviate continuously by more than 2 cm in certain position directions, an error mark is made in the current time segment to check whether it is caused by external vibration or mechanical coupling. If it is confirmed to be a normal phenomenon, continue to record all offsets in the segment. If it is found that the instruction layer is inconsistent with the actual coordinate changes, it is necessary to trace the driving frequency of the transmission mechanism and the number of corrections of the positioning link, and divide the speed of the transmission mechanism into a slow moving range of 0.2m / s to 0.5m / s and a faster moving range of 0.5m / s to 1.0m / s. During the segmented comparison, the coordinate offset distribution in different intervals is observed, and then the extracted offset is compared and analyzed with the previously statistical displacement calibration data to retrieve whether there is a situation where the feature recurs. Through this segmented comparison, the inherent error of the mechanical structure itself and the influence of the on-site random variables on the final position coordinates can be clarified. At the same time, the periodic load information of the current operation should be combined. For example, when the load is in the range of 5kg to 10kg, the mean offset and maximum offset in the multi-point alignment period are recorded, and these values ​​are summarized together with the segmented comparison results. For each period, if the mean offset is greater than 1cm or the maximum offset is greater than 2.5cm, the in-depth investigation phase is entered. By comparing the rotation angle and movement path of the end effector in the same period one by one, the coordinate conversion can be performed against its three-dimensional trajectory data and 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; the position calibration data and the motion trajectory of the picking end effector are displacement compensated to establish trajectory optimization parameters.

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 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 picking tool pressure output value, 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.

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 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, It is the correlation data between cylinder pressure and picking tool pressure output. 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.

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 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.

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 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.

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 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 using the formula: 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.

8. 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 displacement 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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