Intelligent robot identification and positioning system applied to metal forging and pressing equipment

Abstract

The invention discloses an intelligent robot identification and positioning system applied to metal forging and pressing equipment, which is characterized by comprising an image identification module based on deep learning and used for acquiring image data of a working area of the metal forging and pressing equipment in real time and identifying a metal workpiece; the three-dimensional positioning module based on laser scanning is used for carrying out three-dimensional space positioning on the identified metal workpiece; the data processing unit is used for processing data of the image recognition module and the three-dimensional positioning module and generating accurate position information of the workpiece; the control unit is used for controlling the movement of the robot according to the position information so as to accurately grab and place the metal workpiece; the feedback system is used for monitoring and adjusting actions of the robot in real time so as to ensure the accuracy of operation; and the user interface is used for displaying system states and operation instructions and allowing an operator to carry out intervention and adjustment.

Description

Technical Field

[0001] The present invention relates to the technical field of forging equipment, and in particular to an intelligent robot identification and positioning system applied to metal forging equipment. Background Art

[0002] Metal forging and forming processing is one of the important basic industries in the machinery manufacturing industry; however, traditional metal forging production lines often have problems such as low production efficiency, poor product quality stability and high labor intensity of workers; in addition, due to the harsh working environment such as high temperature, noise and dust generated during the forging process, forging companies are faced with practical problems such as difficulty in recruiting workers, frequent employee turnover and rising labor costs.

[0003] In recent years, with the continuous development and maturity of industrial robot technology, its application in various industries has become more and more extensive; especially in the field of metal forging, the application of industrial robots has become an inevitable trend for industry upgrading and transformation; however, traditional methods often have problems of inaccurate recognition and inaccurate positioning when processing complex and changeable image data in the working area of ​​metal forging equipment; and without the support of accurate recognition and positioning systems, it is difficult for robots to accurately grasp and place metal workpieces; and the working environment of metal forging equipment is usually harsh, and manual operation has high safety risks and limited efficiency; traditional systems often lack sufficient flexibility and adjustability, and it is difficult to adapt to the needs of different production scenarios. Summary of the invention

[0004] The present invention aims to solve one of the technical problems in the related art at least to a certain extent. To this end, one object of the present invention is to provide an intelligent robot recognition and positioning system for metal forging equipment, comprising:

[0005] The image recognition module based on deep learning is used to obtain image data of the working area of ​​metal forging equipment in real time and identify metal workpieces, where the relationship is as follows:

[0006] Input: Image data I of the working area of ​​metal forging equipment;

[0007] Output: Identified metal workpiece information (such as type, location) image ;

[0008] Relationship: O image = ImageRecognition(I);

[0009] The three-dimensional positioning module based on laser scanning is used to locate the identified metal workpiece in three dimensions, where the relationship is as follows:

[0010] Input: Identified metal workpiece information O imageand laser scanning data L;

[0011] Output: 3D spatial position information P of the metal workpiece 3D ;

[0012] Relationship: P 3D =LaserScanPositioning( image , L);

[0013] The data processing unit is used to process the data of the image recognition module and the three-dimensional positioning module and generate the precise position information of the workpiece, wherein the relationship is as follows:

[0014] Input: Output O of the image recognition module image And the output P of the 3D positioning module 3D ;

[0015] Output: The precise position information P of the workpiece final ;

[0016] Relationship: P final =DatatProcessing( image , P 3D );

[0017] The control unit is used to control the movement of the robot according to the position information to achieve accurate grasping and placement of metal workpieces, where the relationship is as follows:

[0018] Input: The precise position information P of the workpiece final ;

[0019] Output: robot motion control instruction C;

[0020] C=ControlAlgorithm(P final );

[0021] The feedback system is used to monitor and adjust the robot's movements in real time to ensure the accuracy of the operation. The relationship is as follows:

[0022] Input: Real-time monitored robot motion data M and expected motion data M expected ;

[0023] Output: adjustment instruction A (used to adjust the subsequent actions of the robot);

[0024] Relational formula: A = FeedbackAdjustment(M, M expected );

[0025] The user interface is used to display system status and operating instructions, allowing operators to intervene and make adjustments, where the relationship is as follows:

[0026] Input: System status data S (may include O image , P 3D , P final , C, A) and operation instructions O user ;

[0027] Output: Display system status S display Or adjusted operation instruction O adjusted ;

[0028] Relationship: S display =DisplaySystemState(S);

[0029] O adjusted =AdjustOperationInstructions(O user , S).

[0030] Preferably, the three-dimensional positioning module based on laser scanning includes:

[0031] A laser scanning device, used for emitting laser light and receiving reflected light to obtain point cloud data of the surface of the metal workpiece;

[0032] A point cloud data processing unit, used for converting point cloud data into three-dimensional coordinate information;

[0033] Coordinate correction unit, used to correct three-dimensional coordinate information and eliminate system errors;

[0034] Positioning result output interface, used to output the three-dimensional position information of the workpiece.

[0035] Preferably, the data processing unit comprises:

[0036] A data fusion module is used to fuse the data of the image recognition module and the three-dimensional positioning module to generate comprehensive workpiece position information;

[0037] A coordinate conversion module, used to convert the workpiece position information into coordinates in the robot coordinate system;

[0038] The data output interface is used to output the converted coordinate information to the control unit.

[0039] Preferably, the control unit comprises:

[0040] Motion planning module, used to plan the robot's motion trajectory based on the workpiece position information;

[0041] Motion control module, used to control the robot's joints and actuators to achieve precise motion control;

[0042] Safety monitoring module, used to monitor the robot's working status and surrounding environment in real time;

[0043] Control instruction output interface, used to output control instructions to the robot.

[0044] Preferably, the feedback system comprises:

[0045] A sensor network for real-time monitoring of the robot’s position, velocity, and acceleration;

[0046] Error analysis module to analyze the difference between sensor data and expected trajectory;

[0047] An adjustment instruction generation module, used for generating adjustment instructions to reduce errors;

[0048] Feedback control interface, used to transmit adjustment instructions to the control unit.

[0049] Preferably, the user interface includes:

[0050] Display module, used to display system status, operation instructions and real-time data;

[0051] An input module, used for receiving input instructions from an operator;

[0052] Status monitoring module, used to monitor system operation status and alarm information;

[0053] The interactive control module is used to process the interactive operations between the operator and the system.

[0054] Preferably, it also includes an adaptive learning module for optimizing the performance of the image recognition module and the three-dimensional positioning module according to the operation history and feedback data.

[0055] Preferably, it also includes an environment perception module for sensing the working environment of the metal forging equipment in real time and using the environmental information to assist workpiece identification and positioning.

[0056] Preferably, it also includes a communication module for realizing data exchange and collaborative work with the control system of the metal forging equipment, other robot systems or external monitoring systems.

[0057] The above solution of the present invention includes at least the following beneficial effects:

[0058] Through the deep learning image recognition module and the laser scanning three-dimensional positioning module, the system can accurately identify and locate metal workpieces in real time, thereby significantly improving the operating accuracy and efficiency of the robot in metal forging equipment. Since the system can accurately control the movement of the robot, it reduces the risk of direct manual operation of metal forging equipment and improves workplace safety. Accurate workpiece identification and positioning reduces material waste and machine downtime caused by misoperation or inaccurate positioning, thereby optimizing the utilization of production resources. The integrated feedback system and user interface enable the system to adjust operations according to real-time conditions, while allowing operators to make necessary interventions and adjustments, thereby improving the intelligence level of the entire production process.

[0059] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present invention 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 invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0061] Figure 1 This is a flow chart of an intelligent robot identification and positioning system for metal forging equipment provided in an embodiment of the present invention:

[0062] Figure 2 It is a flow chart of a module provided in an embodiment of the present invention.

[0063] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0064] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, but are not to be construed as limiting the present invention. All other embodiments obtained by ordinary technicians in the field without creative work based on the embodiments of the present invention are within the scope of protection of the present invention.

[0065] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "circumferential", "radial" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0066] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0067] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0068] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may include that the first and second features are in direct contact, or may include that the first and second features are not in direct contact but are in contact through another feature between them. Moreover, a first feature being "above", "above" and "above" a second feature includes that the first feature is directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. A first feature being "below", "below" and "below" a second feature includes that the first feature is directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0069] The intelligent robot recognition and positioning system applied to metal forging equipment according to an embodiment of the present invention will be described in detail below with reference to the accompanying drawings.

[0070] See also Figures 1-2 , in this embodiment, includes:

[0071] The image recognition module based on deep learning is used to obtain image data of the working area of ​​metal forging equipment in real time and identify metal workpieces, where the relationship is as follows:

[0072] Input: Image data I of the working area of ​​metal forging equipment;

[0073] Output: Identified metal workpiece information (such as type, location, etc.) image ;

[0074] Relationship: O image = ImageRecognition(I);

[0075] The three-dimensional positioning module based on laser scanning is used to locate the identified metal workpiece in three dimensions, where the relationship is as follows:

[0076] Input: Identified metal workpiece information O image and laser scanning data L;

[0077] Output: 3D spatial position information P of the metal workpiece 3D ;

[0078] Relationship: P 3D =LaserScanPositioning( image , L);

[0079] The data processing unit is used to process the data of the image recognition module and the three-dimensional positioning module and generate the precise position information of the workpiece, wherein the relationship is as follows:

[0080] Input: Output O of the image recognition module image And the output P of the 3D positioning module 3D ;

[0081] Output: The precise position information P of the workpiece final ;

[0082] Relationship: P final =DatatProcessing( image , P 3D );

[0083] The control unit is used to control the movement of the robot according to the position information to achieve accurate grasping and placement of metal workpieces, where the relationship is as follows:

[0084] Input: The precise position information P of the workpiece final ;

[0085] Output: robot motion control instruction C;

[0086] C=ControlAlgorithm(P final );

[0087] The feedback system is used to monitor and adjust the robot's movements in real time to ensure the accuracy of the operation. The relationship is as follows:

[0088] Input: Real-time monitored robot motion data M and expected motion data M expected ;

[0089] Output: adjustment instruction A (used to adjust the subsequent actions of the robot);

[0090] Relational formula: A = FeedbackAdjustment(M, M expected );

[0091] The user interface is used to display system status and operating instructions, allowing operators to intervene and make adjustments, where the relationship is as follows:

[0092] Input: System status data S (may include O image , P 3D , P final , C, A) and operation instructions O user ;

[0093] Output: Display system status S display Or adjusted operation instruction O adjusted ;

[0094] Relationship: S display =DisplaySystemState(S);

[0095] O adjusted =AdjustOperationInstructions(O user , S);

[0096] Through the deep learning image recognition module and the laser scanning three-dimensional positioning module, the system can accurately identify and locate metal workpieces in real time, thereby significantly improving the operating accuracy and efficiency of the robot in metal forging equipment. Since the system can accurately control the movement of the robot, it reduces the risk of direct manual operation of metal forging equipment and improves workplace safety. Accurate workpiece identification and positioning reduces material waste and machine downtime caused by misoperation or inaccurate positioning, thereby optimizing the utilization of production resources. The integrated feedback system and user interface enable the system to adjust operations according to real-time conditions, while allowing operators to make necessary interventions and adjustments, thereby improving the intelligence level of the entire production process.

[0097] In this embodiment, the three-dimensional positioning module based on laser scanning includes: a laser scanning device, which is used to emit laser and receive reflected light to obtain point cloud data of the surface of the metal workpiece; a point cloud data processing unit, which is used to convert the point cloud data into three-dimensional coordinate information; a coordinate correction unit, which is used to correct the three-dimensional coordinate information and eliminate system errors; a positioning result output interface, which is used to output the three-dimensional position information of the workpiece;

[0098] The 3D positioning module based on laser scanning includes a series of precisely designed components that work together to achieve high-precision 3D position measurement. First, the laser scanning device is responsible for emitting laser beams and capturing the light reflected from the surface of the metal workpiece. By analyzing these reflected lights, the device can obtain detailed point cloud data of the workpiece surface. These data contain the 3D coordinate information of the workpiece surface and are the basis for subsequent processing.

[0099] The point cloud data processing unit receives the raw point cloud data from the laser scanning device and converts it into three-dimensional coordinate information that is easier to understand and apply through a preset algorithm; this process may include steps such as data filtering, feature extraction, and surface reconstruction to ensure that the final coordinate information is accurate;

[0100] The function of the coordinate correction unit is to further improve the accuracy of the three-dimensional coordinate information. It eliminates errors caused by equipment manufacturing, installation or environmental factors through correction algorithms. The correction process may include temperature compensation, mechanical error correction and optical distortion correction, etc., to ensure that the final output three-dimensional position information is as close to the true value as possible.

[0101] Finally, the positioning result output interface is responsible for outputting the corrected three-dimensional position information for use by other systems or operators. The output interface can be a digital signal, network protocol or other form to ensure compatibility with external devices or systems and accurate transmission of information. Through this interface, the three-dimensional position information of the workpiece can be used in automated assembly, quality inspection, reverse engineering and other applications.

[0102] In this embodiment, the data processing unit includes: a data fusion module, which is used to fuse the data of the image recognition module and the three-dimensional positioning module to generate comprehensive workpiece position information; a coordinate conversion module, which is used to convert the workpiece position information into coordinates in the robot coordinate system; a data output interface, which is used to output the converted coordinate information to the control unit;

[0103] The data fusion module can receive data from the image recognition module and the 3D positioning module. The image recognition module uses image processing technology to identify the shape, size and features of the workpiece, while the 3D positioning module uses laser scanning, vision or other sensor technologies to determine the precise position of the workpiece in the 3D space. The data fusion module combines this information and generates a comprehensive workpiece position information through a preset algorithm. This information includes not only the position of the workpiece in space, but also its posture, direction and possible identification features, providing a comprehensive data basis for subsequent processing.

[0104] The coordinate transformation module converts the workpiece position information generated by the fusion module into coordinates in the robot coordinate system; since the robot needs to operate in its own coordinate system when performing tasks, coordinate transformation is an essential step; the coordinate transformation module takes into account the actual workspace of the robot, the location of the tool center point, and any necessary offsets or calibration parameters to ensure that the workpiece position information can be accurately mapped into a coordinate system that the robot can understand and operate;

[0105] The data output interface can output the converted coordinates of the coordinate conversion module to the control unit in an appropriate format. After receiving this information, the control unit will further process and generate control instructions to drive the robot to perform corresponding actions, such as moving to a specific position, grabbing or placing workpieces, etc. The design of the data output interface must ensure the accuracy and real-time nature of data transmission to avoid any possible delays or errors, which is particularly important in production environments with high speed or high precision requirements.

[0106] The data fusion module, coordinate conversion module and data output interface ensure that the robot can receive and understand data from different sensors, thereby achieving precise automated operation.

[0107] In this embodiment, the control unit includes: a motion planning module, which is used to plan the motion trajectory of the robot according to the workpiece position information; a motion control module, which is used to control the joints and actuators of the robot to achieve precise motion control; a safety monitoring module, which is used to monitor the working status and surrounding environment of the robot in real time; a control instruction output interface, which is used to output control instructions to the robot;

[0108] Motion planning module: receives the internal position information of the workpiece in the equipment, and then plans an optimal motion trajectory using a preset algorithm; this process needs to take into account factors such as the robot's working range, joint limitations, collision avoidance, and motion smoothness; the motion planning module ensures that the robot can move to the specified position in the most efficient way to perform tasks such as grasping, handling, and assembly;

[0109] Motion control module: Once the motion planning module determines the motion trajectory, the motion control module begins to convert the planned trajectory into specific action instructions to control the robot's joints and actuators. The motion control module needs to accurately control the motor's speed, direction, and torque to ensure that the robot's motion is accurate. In addition, it needs to process real-time feedback and fine-tune the robot's motion to adapt to environmental changes or respond to emergencies.

[0110] Safety monitoring module: responsible for real-time monitoring of the robot's working status and surrounding environment to prevent potential safety risks; it detects abnormal situations such as collision, overload or equipment failure through various sensors (such as torque sensors, visual sensors, distance sensors, etc.). Once a dangerous signal is detected, the safety monitoring module will immediately take measures, such as stopping the robot movement, sounding an alarm or executing emergency procedures to ensure the safety of personnel and equipment;

[0111] Control instruction output interface: The control instruction output interface is the communication between the control unit and the robot; the control instructions generated by the control unit are accurately transmitted to the various execution components of the robot through a preset communication method; these instructions may include start, stop, speed adjustment, direction change, etc.; the control instruction output interface needs to have high reliability and fast response capabilities to ensure that the robot can respond to the instructions of the control unit immediately and perform corresponding actions.

[0112] In this embodiment, the feedback system includes: a sensor network for real-time monitoring of the robot's motion parameters such as position, velocity and acceleration; an error analysis module for analyzing the difference between the sensor data and the expected trajectory; an adjustment instruction generation module for generating adjustment instructions to reduce the error; a feedback control interface for transmitting the adjustment instructions to the control unit;

[0113] The sensor network is the basis of the feedback system. It consists of a variety of sensors that are placed at key locations of the robot or at the pipe locations of the forging equipment to monitor the robot's motion state in real time. These sensors can be position sensors, velocity sensors, accelerometers, etc., which can provide detailed information about the robot's current motion state. For example, position sensors can provide the robot's precise coordinates in space, velocity sensors can measure the moving speed of each part of the robot, and accelerometers can detect the acceleration changes of the robot's motion. These data are crucial to understanding the robot's dynamic behavior.

[0114] The error analysis module analyzes the differences between the data collected from the sensor network and the trajectory that the robot is expected to execute. This module usually contains preset algorithms that can process and compare the data to identify any deviations. These deviations may be caused by external interference, internal mechanical errors, or inaccuracies in the control system. The error analysis module must be able to quickly and accurately identify these differences so that timely adjustments can be made.

[0115] The adjustment instruction generation module is based on the information provided by the error analysis module. The adjustment instruction generation module is responsible for calculating the necessary adjustment instructions to reduce the deviation between the robot's motion and the expected trajectory; these adjustment instructions may include changing the speed of the motor, adjusting the angle of the joint, or changing the robot's movement path. The process of generating adjustment instructions requires a high degree of accuracy and real-time performance to ensure that the robot can respond quickly and correct its motion;

[0116] The feedback control interface is the part that transmits adjustment instructions to the robot. The robot is responsible for executing actions and adjusts the robot's movement according to the received adjustment instructions. The feedback control interface must ensure that the instructions can be transmitted to the control unit with the shortest delay and the highest reliability so that the control unit can execute these instructions accurately and without error.

[0117] In this embodiment, the user interface includes: a display module for displaying system status, operation instructions and real-time data; an input module for receiving input instructions from the operator; a status monitoring module for monitoring the system operation status and alarm information; an interactive control module for processing interactive operations between the operator and the system;

[0118] The display module is the part of the user interface responsible for visual presentation, showing the system status, operating instructions and real-time data to the user in the form of graphics, text or symbols;

[0119] The input module is the part of the user interface that receives user operation instructions, allowing the user to interact with the system through keyboard, mouse, touch screen, voice commands or other input devices;

[0120] The status monitoring module is responsible for real-time monitoring of the system's operating status and providing alarm information when an abnormality occurs or when user attention is required;

[0121] The interactive control module is the core part of the user interface that handles the interactive operations between the user and the system. It is responsible for interpreting the user's input instructions and converting these instructions into operations that the system can understand.

[0122] In this embodiment, an adaptive learning module is also included, which is used to optimize the performance of the image recognition module and the three-dimensional positioning module according to the operation history and feedback data; the adaptive learning module is to continuously improve the overall performance of the system, especially in the two functions of image recognition and three-dimensional positioning; the adaptive learning module can intelligently adjust and optimize the algorithms of the image recognition module and the three-dimensional positioning module by analyzing the operation history and the collected feedback data;

[0123] Specifically, the image recognition module is responsible for extracting useful information from the input image data and identifying key features and objects in the image; with the intervention of the adaptive learning module, the system is able to adjust the recognition algorithm based on user interaction and the accuracy of the recognition results; for example, if the system often makes mistakes when recognizing a certain type of object, the adaptive learning module will analyze the cause of the error and adjust the recognition algorithm to reduce the error rate in the future; this may include adjusting the parameters of feature extraction, using more complex machine learning models, or introducing additional training data to enhance the generalization ability of the model;

[0124] The 3D positioning module is responsible for calculating the position and orientation of the object in 3D space based on the image data. The adaptive learning module can optimize the positioning algorithm by analyzing the accuracy and stability of the positioning results. This may involve improving the depth estimation technology, adjusting the calibration parameters of the camera or laser generator, or integrating data from other sensors to improve the accuracy of positioning.

[0125] The adaptive learning module can also adjust the system's performance based on user feedback; for example, if a user points out that the system performs poorly in a specific type of image or scene, the adaptive learning module will take this information into account and adjust the algorithm accordingly; this learning mechanism ensures that the system can continue to improve and better adapt to a variety of different usage environments and needs;

[0126] Through this continuous optimization process, the image recognition system can provide more accurate and reliable recognition results, while also achieving higher precision in three-dimensional positioning.

[0127] In this embodiment, an environment perception module is also included, which is used to perceive the working environment of the metal forging equipment in real time, and use the environment information to assist in workpiece identification and positioning; the environment perception module can monitor and analyze the working environment of the metal forging equipment in real time; the environment perception module is composed of a variety of sensors, including but not limited to temperature sensors, humidity sensors, vibration sensors and visual cameras, etc., which work together to ensure comprehensive perception of the working environment;

[0128] Temperature sensors are responsible for monitoring temperature changes in the equipment and its surroundings, which is essential to prevent equipment from overheating and ensure that materials are processed at the appropriate temperature. Humidity sensors focus on the humidity level in the air, as excessive humidity may adversely affect the surface quality of metal materials and may also affect the normal operation of the equipment.

[0129] Vibration sensors are used to detect vibrations during equipment operation, detect potential mechanical failures in a timely manner, and avoid production interruptions or workpiece damage caused by equipment abnormalities;

[0130] As an important component of the environmental perception module, the visual camera can not only capture real-time images of the equipment operation, but also assist in the identification and positioning of workpieces through image processing technology. Through advanced image recognition algorithms, the visual camera can automatically identify workpieces of different shapes and sizes and accurately locate them in the equipment (it can also serve as an auxiliary identification and positioning function). This not only improves the degree of automation, but also reduces errors caused by human operation and ensures processing accuracy.

[0131] Real-time acquisition and analysis of environmental information enables metal forging equipment to automatically adjust its working parameters, such as pressure, speed and temperature, according to changes in the working environment, thereby achieving more precise and efficient production.

[0132] In this embodiment, a communication module is also included for realizing data exchange and collaborative work with the control system of the metal forging equipment, other robot systems or external monitoring systems; the communication module not only ensures that the robot can seamlessly connect with the control system of the metal forging equipment, but also realizes efficient data exchange and collaborative work with other robot systems or external monitoring systems; through this communication module, the robot can receive real-time data from the forging equipment, such as temperature, pressure, speed and other key parameters, so as to perform precise control and adjustment; at the same time, it can also exchange information with other robots and coordinate their actions to realize complex actions.

[0133] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0134] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. An intelligent robot identification and positioning system for metal forging equipment, characterized in that: include: The image recognition module based on deep learning is used to obtain image data of the working area of ​​metal forging equipment in real time and identify metal workpieces, where the relationship is as follows: Input: Image data I of the working area of ​​metal forging equipment; Output: Identified metal workpiece information O image ; Relationship: O image = ImageRecognition(I); The three-dimensional positioning module based on laser scanning is used to locate the identified metal workpiece in three dimensions, where the relationship is as follows: Input: Identified metal workpiece information O image and laser scanning data L; Output: 3D spatial position information P of the metal workpiece 3D ; Relationship: P 3D =LaserScanPositioning( image , L); The data processing unit is used to process the data of the image recognition module and the three-dimensional positioning module and generate the precise position information of the workpiece, wherein the relationship is as follows: Input: Output O of the image recognition module image And the output P of the 3D positioning module 3D ; Output: The precise position information P of the workpiece final ; Relationship: P final =DatatProcessing( image , P 3D ); The control unit is used to control the movement of the robot according to the position information to achieve accurate grasping and placement of metal workpieces, where the relationship is as follows: Input: The precise position information P of the workpiece final ; Output: robot motion control instruction C; C=ControlAlgorithm(P final ); The feedback system is used to monitor and adjust the robot's movements in real time to ensure the accuracy of the operation. The relationship is as follows: Input: Real-time monitored robot motion data M and expected motion data M expected ; Output: adjustment instruction A (used to adjust the subsequent actions of the robot); Relational formula: A = FeedbackAdjustment(M, M expected ); User interface, which displays system status and operating instructions, allowing operators to intervene and make adjustments; Input: system status data S and operation instructions O user , where the relationship is as follows: Output: Display system status S display Or adjusted operation instruction O adjusted ; Relationship: S display =DisplaySystemState(S); O adjusted =AdjustOperationInstructions(O user ,S)。 2. The intelligent robot identification and positioning system for metal forging equipment according to claim 1 is characterized in that: The image recognition module based on deep learning includes: High-speed image acquisition device for capturing real-time images of the working area of ​​metal forging equipment; A pre-processing unit, used for denoising and enhancing the collected images; Deep learning network model for feature extraction and artifact recognition of preprocessed images; The recognition result output interface is used to output the recognition result.

3. The intelligent robot identification and positioning system for metal forging equipment according to claim 1 is characterized in that: The three-dimensional positioning module based on laser scanning includes: A laser scanning device, used for emitting laser light and receiving reflected light to obtain point cloud data of the surface of the metal workpiece; A point cloud data processing unit, used for converting point cloud data into three-dimensional coordinate information; Coordinate correction unit, used to correct three-dimensional coordinate information and eliminate system errors; Positioning result output interface, used to output the three-dimensional position information of the workpiece.

4. The intelligent robot identification and positioning system for metal forging equipment according to claim 1 is characterized in that: The data processing unit comprises: A data fusion module is used to fuse the data of the image recognition module and the three-dimensional positioning module to generate comprehensive workpiece position information; A coordinate conversion module, used to convert the workpiece position information into coordinates in the robot coordinate system; The data output interface is used to output the converted coordinate information to the control unit.

5. The intelligent robot identification and positioning system for metal forging equipment according to claim 1 is characterized in that: The control unit comprises: Motion planning module, used to plan the robot's motion trajectory based on the workpiece position information; Motion control module, used to control the robot's joints and actuators to achieve precise motion control; Safety monitoring module, used to monitor the robot's working status and surrounding environment in real time; Control instruction output interface, used to output control instructions to the robot.

6. The intelligent robot identification and positioning system for metal forging equipment according to claim 1 is characterized in that: The feedback system comprises: A sensor network for real-time monitoring of the robot’s position, velocity, and acceleration; Error analysis module to analyze the difference between sensor data and expected trajectory; An adjustment instruction generation module, used for generating adjustment instructions to reduce errors; Feedback control interface, used to transmit adjustment instructions to the control unit.

7. The intelligent robot identification and positioning system for metal forging equipment according to claim 1 is characterized in that: The user interface comprises: Display module, used to display system status, operation instructions and real-time data; An input module, used for receiving input instructions from an operator; Status monitoring module, used to monitor system operation status and alarm information; The interactive control module is used to process the interactive operations between the operator and the system.

8. The intelligent robot identification and positioning system for metal forging equipment according to claim 1 is characterized in that: An adaptive learning module is also included to optimize the performance of the image recognition module and the three-dimensional positioning module based on the operation history and feedback data.

9. The intelligent robot identification and positioning system for metal forging equipment according to claim 1 is characterized in that: It also includes an environmental perception module for sensing the working environment of the metal forging equipment in real time, and using the environmental information to assist in workpiece identification and positioning.

10. The intelligent robot identification and positioning system for metal forging equipment according to claim 1, characterized in that: It also includes a communication module for realizing data exchange and collaborative work with the control system of the metal forging equipment, other robot systems or external monitoring systems.

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