Turntable feeding and discharging control system based on machine vision

Abstract

The invention relates to the technical field of industrial control, and discloses a turntable feeding and discharging control system based on machine vision, which comprises a sensor module, a dynamic compensation module, a visual control module, a fuzzy control module and a response module. According to the application, the sensor module is used for collecting the sensing motion data, the dynamic compensation module is combined with the sensing motion data to generate the first prediction position, and preliminary prediction is realized; the visual control module collects visual motion data and corrects the first prediction position to obtain a second prediction position; the fuzzy control module generates a third prediction position through a fuzzy control mechanism in combination with the first prediction position; the response module responds to feeding and discharging control based on the second or third predicted position; therefore, the fault tolerance of feeding and discharging control of the rotary table is remarkably improved, the motion condition of the rotary table is predicted and corrected from different angles, the accuracy and reliability of position prediction are improved, and accurate feeding and discharging can be ensured even in a complex industrial environment.

Description

Technical Field

[0001] The present application relates to the field of industrial control technology, and specifically to a turntable loading and unloading control system based on machine vision. Background Art

[0002] With the development of intelligent industrial production, turntable loading and unloading operations are frequent and critical in many production scenarios. The traditional manual loading and unloading method is not only inefficient, but also labor-intensive, and it is difficult to meet the large-scale and high-efficiency production needs of modern industry. Therefore, the turntable loading and unloading control system based on machine vision came into being. It combines advanced machine vision technology and automation control technology to improve the speed and accuracy of loading and unloading, reduce production costs, and improve production efficiency.

[0003] However, the inventors found that the existing turntable loading and unloading control system based on machine vision still has the following problems in practical application:

[0004] 1. Environmental factors have a great impact on the machine vision system. For example, changes in lighting, dust, oil, etc. will affect the image quality and lead to inaccurate recognition of workpieces.

[0005] 2. The movement of the turntable is difficult to predict. Mechanical wear and clearance can cause the actual position of the turntable to deviate from the expected position. The response delay of the control system can also cause asynchronous movement, affecting the accuracy of loading and unloading.

[0006] 3. The system is not adaptable enough to workpiece differences and production changes. For example, workpieces of different sizes and shapes may cause difficulties in identification and grasping, and complex adjustments and debugging are required when production tasks change.

[0007] In summary, it is very important to improve the fault tolerance of the turntable loading and unloading control system based on machine vision. Therefore, a technical solution for turntable loading and unloading control with high fault tolerance is urgently needed. Summary of the invention

[0008] The purpose of this application is to provide a turntable loading and unloading control system based on machine vision to solve the technical problems raised in the above background technology.

[0009] To achieve the above-mentioned purpose, the present application discloses the following technical solutions: a turntable loading and unloading control system based on machine vision, comprising a sensor module, a dynamic compensation module, a visual control module, a fuzzy control module and a response module;

[0010] The sensor module is used to collect sensor motion data of the turntable using a preset sensor; wherein the sensor motion data is used to characterize the motion of the turntable collected by the sensor;

[0011] The dynamic compensation module is used to generate a first predicted position by using a preset dynamic compensation mechanism and combining the sensor motion data; wherein the dynamic compensation mechanism is used to compensate the sensor motion data to generate the first predicted position, and the first predicted position is used to represent the result of the initial prediction of the motion of the turntable;

[0012] The visual control module is used to collect visual motion data of the turntable using machine vision technology, and use the visual motion data to correct the first predicted position to generate a second predicted position; wherein the visual motion data is used to characterize the motion of the turntable collected using machine vision technology, and the second predicted position is used to characterize the result of the fine prediction of the motion of the turntable;

[0013] The fuzzy control module is used to generate a third predicted position by using a preset fuzzy control mechanism and combining the first predicted position; wherein the fuzzy control mechanism is used to generate the third predicted position by blurring the motion data, and the third predicted position is used to represent the result of the fine prediction of the motion of the turntable;

[0014] The response module is used to respond to the turntable loading and unloading control based on the second predicted position or the third predicted position;

[0015] The sensor module is connected to the dynamic compensation module for communication, the visual control module and the fuzzy control module are both connected to the dynamic compensation module for communication, and the visual control module and the fuzzy control module are also both connected to the response module for communication.

[0016] Preferably, the preset process of the dynamic compensation mechanism specifically includes:

[0017] Obtaining historical sensor motion data collected by the sensor and the corresponding historical first predicted position;

[0018] Fitting to obtain a fitting relationship between the historical sensor motion data and the corresponding historical first predicted position, and generating a corresponding first fitting parameter set; wherein the first fitting parameter set is used to generate an initial calculation of the first predicted position using the sensor motion data;

[0019] Acquire historical visual motion data corresponding to the historical sensory motion data, and use the historical visual motion data to correct the first fitting parameter set to obtain a second fitting parameter set; wherein the second fitting parameter set is used to generate a fine calculation of the first predicted position using the sensory motion data;

[0020] The second set of fitting parameters is stored in the dynamic compensation mechanism, and when the dynamic compensation mechanism is running, the first predicted position is generated by using the second set of fitting parameters in combination with the sensor motion data.

[0021] Preferably, the process of generating the first predicted position specifically includes:

[0022] Acquiring the sensor motion data;

[0023] The motion compensation mechanism of the motion compensation module is run and combined with the sensor motion data to generate the first predicted position using the second set of fitting parameters.

[0024] Preferably, the using the visual motion data to correct the first predicted position specifically includes:

[0025] Analyzing the visual motion data to obtain the actual motion of the turntable in the image, and calibrating the motion with the sensor motion data;

[0026] Calculating a correction between the actual motion situation in the visual motion data and the first predicted position;

[0027] The first predicted position is corrected using the calculated correction amount.

[0028] Preferably, the process of generating the second predicted position specifically includes:

[0029] Acquire the first predicted position and the corresponding visual motion data, and use the visual motion data to correct the first predicted position;

[0030] verifying the revised first predicted position;

[0031] The verified and corrected first predicted position is output and defined as the second predicted position.

[0032] Preferably, the preset process of the fuzzy control mechanism specifically includes:

[0033] Collect the historical first prediction positions;

[0034] Performing fuzzification processing; wherein the fuzzification processing is used to generate a fuzzy value corresponding to the first predicted position;

[0035] Establishing a fuzzy rule base; wherein the fuzzy rule base is used for fuzzy reasoning and defuzzification;

[0036] Performing the fuzzy reasoning and the defuzzification, performing reasoning based on the fuzzy value and the fuzzy rule base to obtain an output fuzzy value, and converting the output fuzzy value into an accurate adjustment amount using a defuzzification method;

[0037] The precise adjustment amount is adjusted and stored in the fuzzy control mechanism. When the dynamic compensation mechanism is running, the precise adjustment amount is used in combination with the first predicted position to generate the third predicted position.

[0038] Preferably, the process of generating the third predicted position specifically includes:

[0039] Get the first predicted position;

[0040] Running the fuzzy control mechanism of the fuzzy control module to obtain the corresponding fuzzy value;

[0041] Performing the fuzzy reasoning and the defuzzification, performing reasoning based on the fuzzy value and the fuzzy rule base to obtain the output fuzzy value, and converting the output fuzzy value into a precise adjustment amount using a defuzzification method;

[0042] The third predicted position is generated by using the precise adjustment amount and combining it with the first predicted position.

[0043] Preferably, the response process of the response module specifically includes:

[0044] receiving the second predicted position;

[0045] The second predicted position is used to determine the timing and position of loading and unloading and output.

[0046] Preferably, the response process of the response module further includes:

[0047] receiving the third predicted position;

[0048] The third predicted position is used to determine the timing and position of loading and unloading and output them.

[0049] Preferably, the operation process of the turntable loading and unloading control system specifically includes the following steps:

[0050] S1: running the sensor module to obtain the sensor motion data;

[0051] S2: running the dynamic compensation module to obtain the first predicted position;

[0052] S3: using the visual control module to obtain a corresponding turntable image, and determining whether the image quality of the turntable image meets a preset image quality threshold, if yes, executing step S4, otherwise executing step S5;

[0053] S4: running the visual control module to obtain the second predicted position, and executing step S6;

[0054] S5: Run the fuzzy control module to obtain the third predicted position, and execute step S6;

[0055] S6: Run the response module to respond to the turntable loading and unloading control based on the second predicted position or the third predicted position.

[0056] Beneficial effects: The machine vision-based turntable loading and unloading control system of the present application uses a sensor module to collect the sensor motion data of the turntable, and the dynamic compensation module generates a first predicted position in combination with the sensor motion data to achieve preliminary prediction of the turntable movement; the visual control module uses machine vision technology to collect visual motion data, and corrects the first predicted position to obtain a more precise second predicted position; the fuzzy control module generates a third predicted position in combination with the first predicted position through a preset fuzzy control mechanism; the response module implements the response of loading and unloading control based on the second or third predicted position; through the collaborative work of multiple modules, the fault tolerance of the turntable loading and unloading control is significantly improved, the dynamic compensation mechanism and the fuzzy control mechanism predict and correct the turntable movement from different angles, respectively, thereby improving the accuracy and reliability of position prediction, and can effectively cope with various interference factors even in complex industrial environments to ensure the accuracy of loading and unloading operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0058] Figure 1 A structural block diagram of a turntable loading and unloading control system based on machine vision provided in an embodiment of the present application;

[0059] Figure 2 A flowchart of the operation process of a turntable loading and unloading control system based on machine vision provided in an embodiment of the present application. DETAILED DESCRIPTION

[0060] The technical solutions in the embodiments of the present application are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0061] In this article, the term "comprising" is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprising..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0062] This embodiment discloses Figure 1 A turntable loading and unloading control system based on machine vision is shown, comprising a sensor module, a dynamic compensation module, a vision control module, a fuzzy control module and a response module;

[0063] The sensor module is used to collect the sensor motion data of the turntable using a preset sensor; wherein the sensor motion data is used to characterize the motion of the turntable collected by the sensor;

[0064] The dynamic compensation module is used to generate a first predicted position by using a preset dynamic compensation mechanism and combining the sensor motion data; wherein the dynamic compensation mechanism is used to compensate the sensor motion data to generate the first predicted position, and the first predicted position is used to represent the result of the initial prediction of the motion of the turntable;

[0065] The visual control module is used to collect visual motion data of the turntable using machine vision technology, and use the visual motion data to correct the first predicted position and generate a second predicted position; wherein the visual motion data is used to characterize the motion of the turntable collected using machine vision technology, and the second predicted position is used to characterize the result of the fine prediction of the motion of the turntable;

[0066] The fuzzy control module is used to generate a third predicted position by using a preset fuzzy control mechanism and combining the first predicted position; wherein the fuzzy control mechanism is used to generate the third predicted position by using the fuzzy motion data, and the third predicted position is used to represent the result of the fine prediction of the motion of the turntable;

[0067] The response module is used to respond to the turntable loading and unloading control based on the second predicted position or the third predicted position;

[0068] The sensor module is connected in communication with the dynamic compensation module, the visual control module and the fuzzy control module are both connected in communication with the dynamic compensation module, and the visual control module and the fuzzy control module are also connected in communication with the response module.

[0069] Based on the above, this embodiment uses the sensor module to collect the sensor motion data of the turntable, and the dynamic compensation module generates a first predicted position in combination with the sensor motion data to achieve preliminary prediction of the turntable movement; the visual control module uses machine vision technology to collect visual motion data, and corrects the first predicted position to obtain a more precise second predicted position; the fuzzy control module generates a third predicted position in combination with the first predicted position through a preset fuzzy control mechanism; the response module implements the response of loading and unloading control based on the second or third predicted position; through the collaborative work of multiple modules, the fault tolerance of the turntable loading and unloading control is significantly improved, the dynamic compensation mechanism and the fuzzy control mechanism predict and correct the turntable movement from different angles, respectively, thereby improving the accuracy and reliability of position prediction, and can effectively deal with various interference factors even in complex industrial environments, ensuring the accurate loading and unloading operations.

[0070] Specifically, the preset process of the dynamic compensation mechanism includes:

[0071] Obtaining historical sensor motion data collected by the sensor and the corresponding historical first predicted position;

[0072] Fitting to obtain a fitting relationship between the historical sensor motion data and the corresponding historical first predicted position, and generating a corresponding first fitting parameter set; wherein the first fitting parameter set is used to generate an initial calculation of the first predicted position using the sensor motion data;

[0073] Acquire historical visual motion data corresponding to the historical sensory motion data, and use the historical visual motion data to correct the first fitting parameter set to obtain a second fitting parameter set; wherein the second fitting parameter set is used to generate a fine calculation of the first predicted position using the sensory motion data;

[0074] The second fitting parameter set is stored in the dynamic compensation mechanism, and when the dynamic compensation mechanism is running, the first predicted position is generated using the second fitting parameter set in combination with the sensor motion data.

[0075] It should be noted that, in actual application, the motion data of this embodiment includes at least parameters such as the rotation speed, acceleration and position change of the turntable, so as to provide a data basis for the predicted position; the sensor of this embodiment is used to collect the corresponding motion data, for example, such as a laser displacement sensor, a high-precision encoder and an accelerometer; this embodiment uses the existing fitting technology for fitting, and further, the second fitting parameter set is obtained by further fitting based on the historical visual motion data. The purpose of designing the second fitting parameter set in this embodiment is to provide a more accurate first predicted position for the fuzzy control of the missing visual motion data.

[0076] Based on the above, this embodiment utilizes the dynamic compensation mechanism to ensure the accuracy of the first predicted position, and provides a data basis for improving the fault tolerance of the turntable loading and unloading control.

[0077] Specifically, the process of generating the first predicted position includes:

[0078] Acquire sensor motion data;

[0079] A dynamic compensation mechanism of the dynamic compensation module is run and combined with the sensor motion data to generate a first predicted position using a second set of fitting parameters.

[0080] Based on the above, this embodiment uses the first predicted position to provide an accurate data basis for the operation of the visual control module and the fuzzy control module.

[0081] Specifically, using the visual motion data to correct the first predicted position specifically includes:

[0082] Analyze the visual motion data to obtain the actual motion of the turntable in the image, and calibrate the motion with the sensor motion data;

[0083] Calculating a correction between the actual motion situation in the visual motion data and the first predicted position;

[0084] The first predicted position is corrected using the calculated correction amount.

[0085] It can be understood that the visual motion data of this embodiment and the aforementioned sensor motion data are both motion data, which are named differently due to different acquisition methods, and are both used to characterize the motion of the turntable. The purpose of designing sensor motion data and visual motion data in this embodiment is to verify the motion of the turntable using multiple acquisition methods, thereby ensuring the accuracy of the data used for position prediction, and providing accurate historical data for fuzzy control in the absence of visual motion data, thereby optimizing the fault tolerance of loading and unloading control.

[0086] It should be noted that this embodiment uses existing machine vision technology to realize the processing of visual motion data. In a specific application, the visual motion data collected by the machine vision technology is processed and analyzed to extract the position, speed, acceleration and other information of the turntable in the image, and compare and calibrate it with the sensor motion data collected by the sensor module, so as to eliminate inaccurate information caused by factors such as sensor error and environmental interference. Furthermore, the calculated correction amount can be position deviation, speed deviation or acceleration deviation, etc. By analyzing these deviations, the accuracy and reliability of the first predicted position can be determined. The first predicted position can be corrected by weighted averaging, linear interpolation or other suitable algorithms to integrate the accurate information in the visual motion data into the first predicted position to obtain a more accurate second predicted position.

[0087] Based on the above, this embodiment uses visual motion data to correct the first predicted position, thereby improving the accuracy of position prediction.

[0088] Specifically, the process of generating the second predicted position includes:

[0089] Acquire a first predicted position and corresponding visual motion data, and use the visual motion data to correct the first predicted position;

[0090] verifying the revised first predicted position;

[0091] The verified corrected first predicted position is output and defined as the second predicted position.

[0092] It should be noted that the corrected first predicted position of the present embodiment can be verified by comparing it with the actual turntable position, analyzing the consistency with historical data, etc., to determine the accuracy and reliability of the second predicted position.

[0093] Based on the above, this embodiment uses the second predicted position to provide an accurate data basis for the operation of the response module.

[0094] Specifically, the preset process of the fuzzy control mechanism includes:

[0095] Collect the historical first prediction positions;

[0096] Performing fuzzification processing; wherein the fuzzification processing is used to generate a fuzzy value corresponding to the first predicted position;

[0097] Establish a fuzzy rule base; wherein the fuzzy rule base is used for fuzzy reasoning and defuzzification;

[0098] Perform fuzzy reasoning and defuzzification, perform reasoning based on fuzzy values ​​and fuzzy rule base, obtain output fuzzy values, and use defuzzification methods to convert output fuzzy values ​​into precise adjustment quantities;

[0099] The precise adjustment amount is adjusted and stored in the fuzzy control mechanism. When the dynamic compensation mechanism is running, the precise adjustment amount is used and combined with the first predicted position to generate a third predicted position.

[0100] It should be noted that this embodiment uses the existing fuzzy control technology to implement the preset fuzzy control mechanism, wherein the fuzzy rule base is established based on the experience and expert knowledge known to those skilled in the art.

[0101] Based on the above, this embodiment uses the fuzzy control mechanism to provide technical support for the turntable loading and unloading control in the absence of visual motion data, thereby improving the fault tolerance and applicability of the turntable loading and unloading control.

[0102] Specifically, the process of generating the third predicted position includes:

[0103] Get the first predicted position;

[0104] Run the fuzzy control mechanism of the fuzzy control module to obtain the corresponding fuzzy value;

[0105] Perform fuzzy reasoning and defuzzification, perform reasoning based on fuzzy values ​​and fuzzy rule base, obtain output fuzzy values, and use defuzzification methods to convert output fuzzy values ​​into precise adjustment quantities;

[0106] The third predicted position is generated by using the precise adjustment amount and combining it with the first predicted position.

[0107] Based on the above, this embodiment uses the third predicted position to provide an accurate data basis for the operation of the response module. It can be understood that the third predicted position of this embodiment is a redundant setting. In actual operation, there is a situation where the visual control module cannot obtain high-quality turntable images, which leads to the inability to obtain visual motion data, making it impossible to optimize the first predicted position. Therefore, this embodiment integrates historical visual motion data in the process of generating the first predicted position, and combines fuzzy control to achieve the optimization of the first predicted position in the absence of visual motion data, thereby improving the accuracy and reliability of position prediction. Even in a complex industrial environment, it can effectively deal with various interference factors to ensure the accurate loading and unloading operations.

[0108] Specifically, the response process of the response module includes:

[0109] receiving a second predicted position;

[0110] The second predicted position is used to determine the timing and position of loading and unloading and output them.

[0111] Specifically, the response process of the response module also includes:

[0112] receiving a third predicted position;

[0113] The third predicted position is used to determine the timing and position of loading and unloading and output them.

[0114] It should be noted that the response module of this embodiment is connected to the actuator of the turntable loading and unloading in actual application, for example, a robotic arm. In a simple example, based on the second or third predicted position, the system can accurately plan the motion path of the robotic arm or other actuator to ensure that the loading and unloading operations are performed at the correct time and position. For example, when the turntable moves to a specific position, the response module issues instructions based on the second or third predicted position to allow the robotic arm to accurately grab or place metal powder, thereby achieving an efficient and accurate loading and unloading process. At the same time, the response module can also adjust the speed and strength of loading and unloading in real time according to the second or third predicted position to adapt to different working conditions and improve the stability and reliability of the system.

[0115] Based on the above, the second predicted position or the third predicted position of this embodiment is a refined prediction result obtained after correcting the first predicted position, representing a more accurate state of the turntable movement. By responding to the second predicted position or the third predicted position by the response module, more precise turntable loading and unloading control is achieved, and the third predicted position serves as a redundant setting for the second predicted position, thereby improving the fault tolerance of the turntable loading and unloading control system.

[0116] Specifically, Figure 2 As shown in the figure, the operation process of the turntable loading and unloading control system specifically includes the following steps:

[0117] S1: Run the sensor module to obtain sensor motion data;

[0118] S2: Run the dynamic compensation module to obtain the first predicted position;

[0119] S3: using the visual control module to obtain the corresponding turntable image, and determining whether the image quality of the turntable image meets a preset image quality threshold, if yes, executing step S4, otherwise executing step S5;

[0120] S4: Run the visual control module to obtain the second predicted position, and execute step S6;

[0121] S5: Run the fuzzy control module to obtain the third predicted position, and execute step S6;

[0122] S6: Run the response module to respond to the turntable loading and unloading control based on the second predicted position or the third predicted position.

[0123] It should be noted that, in this embodiment, judging whether the image quality of the turntable image meets the preset image quality threshold is an evaluation method of image quality by existing image processing technology, for example, such as the evaluation of the clarity of the turntable and the integrity of the key positions of the turntable.

[0124] Based on the above, this embodiment utilizes the judgment of the image quality of the turntable image to significantly improve the fault tolerance of the turntable loading and unloading control system. Based on the collaborative work of multiple modules, different prediction methods are adopted in different situations to effectively deal with various possible problems; even when the image quality is poor, the fuzzy control module can still play a role to ensure the stable operation of the system and improve the accuracy and reliability of position prediction.

[0125] In summary, the turntable loading and unloading control system based on machine vision in this embodiment uses a sensor module to collect the sensor motion data of the turntable, and the dynamic compensation module generates a first predicted position in combination with the sensor motion data to achieve preliminary prediction of the turntable movement; the visual control module uses machine vision technology to collect visual motion data, and corrects the first predicted position to obtain a more precise second predicted position; the fuzzy control module generates a third predicted position in combination with the first predicted position through a preset fuzzy control mechanism; the response module implements the response of the loading and unloading control based on the second or third predicted position; through the collaborative work of multiple modules, the fault tolerance of the turntable loading and unloading control is significantly improved, the dynamic compensation mechanism and the fuzzy control mechanism predict and correct the turntable movement from different angles, respectively, which improves the accuracy and reliability of position prediction, and can effectively cope with various interference factors even in complex industrial environments, ensuring the precise loading and unloading operations.

[0126] In the embodiments provided in the present application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor, controller, microcontroller, microprocessor, other electronic units designed to implement the functions described herein or their combination. For software implementation, part or all of the flow of the embodiment can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable storage medium or transmitted as one or more instructions or codes on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein the communication medium includes any medium that is convenient for transmitting a computer program from one place to another. The storage medium can be any available medium that a computer can access. The computer-readable storage medium can include but is not limited to RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer.

[0127] Finally, it should be noted that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A turntable loading and unloading control system based on machine vision, characterized in that: It includes a sensor module, a dynamic compensation module, a visual control module, a fuzzy control module and a response module; The sensor module is used to collect sensor motion data of the turntable using a preset sensor; wherein the sensor motion data is used to characterize the motion of the turntable collected by the sensor; The dynamic compensation module is used to generate a first predicted position by using a preset dynamic compensation mechanism and combining the sensor motion data; wherein the dynamic compensation mechanism is used to compensate the sensor motion data to generate the first predicted position, and the first predicted position is used to represent the result of the initial prediction of the motion of the turntable; The visual control module is used to collect visual motion data of the turntable using machine vision technology, and use the visual motion data to correct the first predicted position to generate a second predicted position; wherein the visual motion data is used to characterize the motion of the turntable collected using machine vision technology, and the second predicted position is used to characterize the result of the fine prediction of the motion of the turntable; The fuzzy control module is used to generate a third predicted position by using a preset fuzzy control mechanism and combining the first predicted position; wherein the fuzzy control mechanism is used to generate the third predicted position by blurring the motion data, and the third predicted position is used to represent the result of the fine prediction of the motion of the turntable; The response module is used to respond to the turntable loading and unloading control based on the second predicted position or the third predicted position; The sensor module is connected to the dynamic compensation module for communication, the visual control module and the fuzzy control module are both connected to the dynamic compensation module for communication, and the visual control module and the fuzzy control module are also both connected to the response module for communication.

2. The turntable loading and unloading control system based on machine vision according to claim 1 is characterized in that: The preset process of the dynamic compensation mechanism specifically includes: Obtaining historical sensor motion data collected by the sensor and the corresponding historical first predicted position; Fitting to obtain a fitting relationship between the historical sensor motion data and the corresponding historical first predicted position, and generating a corresponding first fitting parameter set; wherein the first fitting parameter set is used to generate an initial calculation of the first predicted position using the sensor motion data; Acquire historical visual motion data corresponding to the historical sensory motion data, and use the historical visual motion data to correct the first fitting parameter set to obtain a second fitting parameter set; wherein the second fitting parameter set is used to generate a fine calculation of the first predicted position using the sensory motion data; The second set of fitting parameters is stored in the dynamic compensation mechanism, and when the dynamic compensation mechanism is running, the first predicted position is generated by using the second set of fitting parameters in combination with the sensor motion data.

3. The turntable loading and unloading control system based on machine vision according to claim 2 is characterized in that: The process of generating the first predicted position specifically includes: Acquiring the sensor motion data; The motion compensation mechanism of the motion compensation module is run and combined with the sensor motion data to generate the first predicted position using the second set of fitting parameters.

4. The turntable loading and unloading control system based on machine vision according to claim 1 is characterized in that: The method of correcting the first predicted position by using the visual motion data specifically includes: Analyzing the visual motion data to obtain the actual motion of the turntable in the image, and calibrating the motion with the sensor motion data; Calculating a correction between the actual motion situation in the visual motion data and the first predicted position; The first predicted position is corrected using the calculated correction amount.

5. The turntable loading and unloading control system based on machine vision according to claim 4 is characterized in that: The generation process of the second predicted position specifically includes: Acquire the first predicted position and the corresponding visual motion data, and use the visual motion data to correct the first predicted position; verifying the revised first predicted position; The verified and corrected first predicted position is output and defined as the second predicted position.

6. The turntable loading and unloading control system based on machine vision according to claim 1 is characterized in that: The preset process of the fuzzy control mechanism specifically includes: Collect the historical first prediction positions; Performing fuzzification processing; wherein the fuzzification processing is used to generate a fuzzy value corresponding to the first predicted position; Establishing a fuzzy rule base; wherein the fuzzy rule base is used for fuzzy reasoning and defuzzification; Performing the fuzzy reasoning and the defuzzification, performing reasoning based on the fuzzy value and the fuzzy rule base to obtain an output fuzzy value, and converting the output fuzzy value into an accurate adjustment amount using a defuzzification method; The precise adjustment amount is adjusted and stored in the fuzzy control mechanism. When the dynamic compensation mechanism is running, the precise adjustment amount is used in combination with the first predicted position to generate the third predicted position.

7. The turntable loading and unloading control system based on machine vision according to claim 6 is characterized in that: The generation process of the third predicted position specifically includes: Get the first predicted position; Running the fuzzy control mechanism of the fuzzy control module to obtain the corresponding fuzzy value; Performing the fuzzy reasoning and the defuzzification, performing reasoning based on the fuzzy value and the fuzzy rule base to obtain the output fuzzy value, and converting the output fuzzy value into a precise adjustment amount using a defuzzification method; The third predicted position is generated by using the precise adjustment amount and combining it with the first predicted position.

8. The turntable loading and unloading control system based on machine vision according to claim 1 is characterized in that: The response process of the response module specifically includes: receiving the second predicted position; The second predicted position is used to determine the timing and position of loading and unloading and output.

9. The turntable loading and unloading control system based on machine vision according to claim 1 is characterized in that: The response process of the response module further includes: receiving the third predicted position; The third predicted position is used to determine the timing and position of loading and unloading and output them.

10. The turntable loading and unloading control system based on machine vision according to claim 1, characterized in that: The operation process of the turntable loading and unloading control system specifically includes the following steps: S1: running the sensor module to obtain the sensor motion data; S2: running the dynamic compensation module to obtain the first predicted position; S3: using the visual control module to obtain a corresponding turntable image, and determining whether the image quality of the turntable image meets a preset image quality threshold, if yes, executing step S4, otherwise executing step S5; S4: running the visual control module to obtain the second predicted position, and executing step S6; S5: Run the fuzzy control module to obtain the third predicted position, and execute step S6; S6: Run the response module to respond to the turntable loading and unloading control based on the second predicted position or the third predicted position.

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