A robot control system and method

Abstract

The application provides a kind of mechanical arm control system and method, it is related to intelligent assembly technical field;System includes total control end, execution control end and target identification device, the method is, to the end node positioning of mechanical arm, establishes the geometric relation of end node and corner node, further determines the corner node information of mechanical arm from starting point to terminal by inverse kinematics algorithm and geometric relation, to control the rotating speed and rotation angle of stepping motor of mechanical arm, realizes the accurate positioning control of mechanical arm movement, and target identification device is installed in the end node of mechanical arm, converts world coordinate to pixel coordinate, to determine the distance between target object, realizes more accurate target detection and positioning, improves autonomous processing capacity and assembly efficiency.The application realizes remote control mechanical arm by the combination of total control end, execution control end and target identification device, realizes the target identification grasping and placing of high automation under the condition of lower cost.

Description

Technical Field

[0001] This invention mainly relates to the field of intelligent assembly technology, specifically to a robotic arm control system and method. Background Technology

[0002] With the development of artificial intelligence and sensing technology, the application of robotic arms is becoming increasingly widespread, placing higher demands on their precise positioning and target recognition. Traditional robotic arms are expensive, complex to control, and their long arms limit their workspace and operational flexibility, increasing inertia and friction and affecting accuracy and sensitivity. This is especially true in assembly manufacturing, where the positional accuracy of the robotic arm directly impacts assembly precision. Traditional robotic arms typically require precise programming and settings, and their autonomous handling capabilities are weak for unpredictable tasks or environmental changes. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a robotic arm control system and method to address the shortcomings of the prior art.

[0004] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: a robotic arm control system, comprising a main control terminal, an execution control terminal, and a target recognition device, wherein the execution control terminal is mounted on the robotic arm, the main control terminal is connected to the execution control terminal, and the target recognition device is connected to both the execution control terminal and the main control terminal.

[0005] The main control terminal is used to receive control requests sent by the operator, generate a first positioning command through the control request, and send it to the target recognition device.

[0006] The target recognition device is used to image the target object according to the first positioning command, form a target object image, obtain target positioning information based on the target object image, and send it to the main control terminal to generate a second positioning command.

[0007] The execution control terminal is used to perform real-time positioning of the end node of the robotic arm according to the second positioning command, obtain end positioning information, and send it to the main control terminal;

[0008] The main control terminal is used to determine whether the target positioning information and the end-effector positioning information are consistent. If they are, a grasping command is generated. If not, the corner node information of the robotic arm is calculated based on the inverse kinematics algorithm, the target positioning information and the end-effector positioning information, and a movement command is generated based on the corner node information.

[0009] The execution control terminal is used to perform a grasping operation on the target object according to the grasping instruction; it is also used to control the robotic arm to move to the target object according to the movement instruction, and to perform a grasping operation on the target object when it reaches the target object.

[0010] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: a robotic arm control method, applied to the robotic arm control system, comprising a main control terminal, an execution control terminal and a target recognition device, wherein the execution control terminal is mounted on the robotic arm, the main control terminal is connected to the execution control terminal, and the target recognition device is connected to both the execution control terminal and the main control terminal.

[0011] The central control unit receives a control request sent by the operator and generates a first positioning command based on the control request, which is then sent to the target identification device.

[0012] The target recognition device images the target object according to the first positioning command, forms an image of the target object, obtains target positioning information based on the target object image, and sends it to the central control terminal to generate a second positioning command.

[0013] The execution control terminal performs real-time positioning of the end effector of the robotic arm according to the second positioning command, obtains end effector positioning information, and sends it to the main control terminal;

[0014] The central control unit determines whether the target positioning information and the end-effector positioning information are consistent. If they are, a grasping command is generated. If not, the rotation node information of the robotic arm is calculated based on the inverse kinematics algorithm, the target positioning information, and the end-effector positioning information. A movement command is generated based on the rotation node information.

[0015] The execution control terminal performs a grasping operation on the target object according to the grasping instruction; it is also used to control the robotic arm to move to the target object according to the movement instruction, and perform a grasping operation on the target object when it reaches the target object.

[0016] The beneficial effects of this invention are: by combining the main control terminal, the execution control terminal and the target recognition device, remote control of the robotic arm is achieved, realizing highly automated target recognition, grasping and placement under low cost conditions. This invention can efficiently and accurately complete target grasping and placement tasks, and can replace manual labor in different work scenarios, improving production efficiency while reducing costs. Attached Figure Description

[0017] Figure 1 This is a schematic diagram showing the connection of various functional components in the robotic arm control system provided in an embodiment of the present invention;

[0018] Figure 2A diagram showing the rotation angle relationship of the robotic arm provided in an embodiment of the present invention;

[0019] Figure 3 A trajectory diagram of the end effector node of the robotic arm provided in an embodiment of the present invention;

[0020] Figure 4 A schematic diagram of the robotic arm structure provided in an embodiment of the present invention;

[0021] Figure 5 This is a schematic diagram of the structure of the slide module provided in an embodiment of the present invention;

[0022] Figure 6 This is a transmission principle diagram of the slide module provided in an embodiment of the present invention;

[0023] Figure 7 A schematic diagram illustrating the principle of camera coordinate system transformation provided in an embodiment of the present invention;

[0024] Figure 8 A schematic flowchart illustrating the robotic arm control method provided in an embodiment of the present invention;

[0025] Figure 9 The control flowchart provided for embodiments of the present invention.

[0026] In the attached diagram, the component names represented by each label are as follows:

[0027] 1. Robotic arm; 2. Camera; 3. Mechanical gripper; 4. Slide module; 4-1. Stepper motor; 4-2. Displacement sensor; 4-3. Threaded rod; 4-4. Dual linear rail. Detailed Implementation

[0028] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0029] like Figures 1-4 As shown, this embodiment of the invention provides a robotic arm control system, including a main control terminal, an execution control terminal, and a target recognition device. The main control terminal is connected to the execution control terminal, and the target recognition device is connected to both the execution control terminal and the main control terminal.

[0030] The main control terminal is used to receive control requests sent by the operator, generate a first positioning command through the control request, and send it to the target recognition device.

[0031] The target recognition device is used to image the target object according to the first positioning command, form a target object image, obtain target positioning information based on the target object image, and send it to the main control terminal to generate a second positioning command.

[0032] The execution control terminal is used to perform real-time positioning of the end node of the robotic arm according to the second positioning command, obtain end positioning information, and send it to the main control terminal;

[0033] The main control terminal is used to determine whether the target positioning information and the end-effector positioning information are consistent. If they are, a grasping command is generated. If not, the corner node information of the robotic arm is calculated based on the inverse kinematics algorithm, the target positioning information and the end-effector positioning information, and a movement command is generated based on the corner node information.

[0034] The execution control terminal is used to perform a grasping operation on the target object according to the grasping instruction; it is also used to control the robotic arm to move to the target object according to the movement instruction, and to perform a grasping operation on the target object when it reaches the target object.

[0035] In the above embodiments, the combination of the main control terminal, the execution control terminal and the target recognition device enables remote control of the robotic arm 1, achieving highly automated target recognition, grasping and placement under low cost conditions. This invention can efficiently and accurately complete target grasping and placement tasks, and can replace manual labor in different work scenarios, improving production efficiency while reducing costs.

[0036] The main control terminal can be a PC, and the execution control terminal has an integrated STM32 main control chip. The execution control terminal is mounted on robotic arm 1 and electrically connected to the main control terminal. The target recognition device is mounted on robotic arm 1 and electrically connected to both the execution control terminal and the main control terminal. The electrical connection can be via a data cable, or via wireless connections such as 4G / 5G signals, Bluetooth, or WiFi.

[0037] Based on the above embodiments, preferably, the mechanical gripper is a replaceable mechanical gripper used for gripping and placing by the robotic arm.

[0038] like Figure 7 As shown, preferably, in the target recognition device, the target object is imaged to form a target object image, and target positioning information is obtained based on the target object image, specifically as follows:

[0039] A grating is projected onto the surface of a target object, and an image of the target object is formed based on the grating using a camera element.

[0040] Based on the target object image and the coordinate transformation formula, the target object is transformed from world coordinates to pixel coordinates to obtain target positioning information. The coordinate transformation formula is as follows:

[0041]

[0042] Among them, X w,Y w Z w Let u and v be points in the world coordinate system of the target object, and let u and v be points in the image coordinate system of the target object.

[0043] Specifically, firstly, the intrinsic and extrinsic parameters of the camera element (camera) are determined through camera calibration. The intrinsic parameters include focal length, principal point coordinates, etc., while the extrinsic parameters involve the position and orientation of the camera.

[0044] The intrinsic parameter matrix is ​​usually represented as:

[0045]

[0046] The extrinsic parameters describe the position and orientation of the camera relative to the world coordinate system, and are usually represented by the rotation matrix R and the translation vector t.

[0047] like Figure 2 As shown, preferably, in the main control terminal, the rotation node information of the robotic arm is calculated based on the inverse kinematics algorithm, the target positioning information, and the end-effector positioning information, specifically as follows:

[0048] Based on the end-effector positioning information and the working range of the robotic arm, the geometric relationship between the end-effector node and the corner node of the robotic arm is established, specifically as follows:

[0049] Next, let the end effector node of the robotic arm be S3, and the corner nodes of the robotic arm be S1 and S2, where S1 is located at the front end of the robotic arm and S2 is located between S1 and S3; let the working range of the robotic arm be [l1-l2, l1+l2], where l1 is the distance between S1 and S2, l2 is the distance between S2 and S3, and a coordinate system is established with S1 as the origin. The angle between the robotic arm between S1 and S2 and the vertical axis is θ1, and the angle between the robotic arm between S1 and S2 and between the robotic arm between S2 and S3 is θ2. Given the end effector positioning information of the end effector node of the robotic arm as (L, H), where L is the horizontal coordinate and H is the vertical coordinate.

[0050] Establish the geometric relationship between the end effector node and the corner node of the robotic arm:

[0051]

[0052] Where l1 > l2, the working range of the robotic arm is [l1-l2, l1+l2].

[0053] Assuming the target location information is the endpoint, the corner node information for the endpoint moving from the starting point to the intermediate point and from the intermediate point to the endpoint is determined based on the inverse kinematics algorithm and the geometric relationship. Specifically:

[0054] Based on the inverse kinematics algorithm and the aforementioned geometric relationships, the rotation angle of each corner node when the end node moves from the starting point to the intermediate point is calculated.

[0055] Based on the inverse kinematics algorithm and the aforementioned geometric relationships, the rotation angle of each corner node from the intermediate point to the endpoint is calculated. The formula for the inverse kinematics algorithm is as follows:

[0056]

[0057] Where L>0, the angle between the robotic arm between S2 and S3 and the horizontal axis is θ3, θ3 is the angle of the actuator of the end node, and the actuator of the end node is ensured to be in a horizontal state, and θ1 and θ2 are the rotation angles of the corner node S1 and the corner node S2.

[0058] In the above embodiment, the rotation angles of corner nodes S1 and S2 are obtained by performing two inverse kinematic calculations on the starting and ending coordinates of the end node S3.

[0059] Horizontal movement of the robotic arm's end effector can cause the bottom of the object being grasped to bump into it, so an intermediate point is set to solve this problem. The extension and retraction of the robotic arm requires determining the coordinates of the start and end points of the end effector and the intermediate point, as well as the trajectory, angular velocity, and rotation angle of each node.

[0060] like Figures 5-6 As shown, preferably, the slide module 4 includes a stepper motor 4-1, a displacement sensor 4-2, and a double linear guide threaded rod, which is mainly composed of a threaded rod 4-3 and a double linear guide 4-4.

[0061] The slide is slidably connected to the double linear guide threaded rod, the robotic arm is mounted on the slide, the stepper motor controls the rotation of the double linear guide threaded rod, and the rotation of the double linear guide threaded rod drives the slide and the robotic arm to reciprocate on the double linear guide threaded rod.

[0062] Stepper motor 4-1 is used to control the planar positioning of the robotic arm 1 platform.

[0063] Displacement sensor 4-2 is used to convert the length of the pull wire into a resistance signal output. The resistance signal of the displacement sensor is acquired by the ADC channel of the STM32 main control chip and converted into position information.

[0064] The threaded rod 4-3 is used to provide excellent self-locking during constant downward rotation, making the robotic arm 1 more stable during movement.

[0065] The double linear guide 4-4 is used to compensate for the low load-bearing capacity of the threaded rod, which is beneficial to the stable operation of the slide table.

[0066] Robotic arm platform 4-5 is used to mount robotic arm 1. Robotic arm 1 and slide module 4 are combined for the movement and positioning of robotic arm 1.

[0067] Based on the above embodiments, the execution control terminal is further configured to send control signals to the stepper motor to control the overall left and right movement of the entire robotic arm, specifically:

[0068] Based on the above embodiment, the execution control terminal is further used to send control signals to the stepper motor to control the overall left and right movement of the entire robotic arm, specifically: the speed of the slide table is used to generate control signals based on the slide table's movement speed. The speed conversion formula is:

[0069]

[0070] Where v is the moving speed of the slide table, Ph is the lead of the double linear guide threaded rod, and ω is the relative angular velocity of the stepper motor.

[0071] Specifically, the transmission principle of slide module 4 is as follows: Figure 6 As shown, the main function of the slide module 4 is to position the robotic arm platform in a plane. The stepper motor drives the screw transmission to realize the movement of the slide, so that the robotic arm 1 can operate stably.

[0072] In the above embodiments, the slide table is moved by a stepper motor driving a screw drive.

[0073] The slide table achieves precise positioning and prevents it from exceeding its travel limit through a displacement sensor. The displacement sensor converts the length of the pull wire into a resistance signal output.

[0074] The execution control end includes an STM32 control chip, which acquires the resistance signal of the displacement sensor through the ADC channel of the STM32 control chip and converts it into position information.

[0075] Preferably, in the execution control terminal, the grasping operation on the target object specifically includes:

[0076] A monocular ranging model is established based on coordinate transformation. The distance between the robotic arm mounted on the robotic arm and the target object is calculated using the monocular ranging model. The monocular ranging model is as follows:

[0077]

[0078] Where d represents the distance between the robotic arm and the target object, F represents the camera focal length, and H... c Indicates the camera mounting height, y b This represents the y-coordinate of the midpoint of the bottom of the target object, obtained from the image coordinate system. hThis represents the ordinate of the horizon obtained from the image coordinate system, where α represents the angle between the camera optical axis and the ground.

[0079] The robotic arm is controlled to grasp the target object based on the distance between the robotic arm and the target object.

[0080] Preferably, the execution control terminal is further configured to send a scanning command to the target recognition device when the target object is grasped;

[0081] The target recognition device is used to scan the positioning area according to the scanning command, and determine whether it is the target placement location according to the scanning result. If it is, the device sends a placement command to the execution control terminal; otherwise, the device sends a move to the next location command to the execution control terminal.

[0082] The execution control terminal is also used to control the robotic arm's robotic hand to place the target object at the target placement position according to the placement instruction; and is also used to control the robotic arm's robotic hand to move to the next position according to the move to the next position instruction.

[0083] Specifically, the target recognition device includes a camera, a servo cloud platform, and a barcode scanning module. The servo cloud platform is installed at the end node of the robotic arm 1, and the camera and barcode scanning module are installed on the servo cloud platform. The servo cloud platform is used to adjust the angle and position of the camera and barcode scanning module. The camera and barcode scanning module are mainly used to acquire image data and / or barcode data. The camera recognizes the barcode and obtains the coordinate system position information of the anchor frame center distance from the camera center. The position is adjusted to ensure that the barcode scanning module acquires the barcode information to determine the target placement position.

[0084] The device of this invention achieves remote control of the robotic arm 1 by combining a central control terminal, an execution control terminal, and a target recognition device. It realizes highly automated target recognition, grasping, and placement under low cost conditions, enabling the invention to efficiently and accurately complete target grasping and placement tasks. It can replace manual labor in different work scenarios, improving production efficiency while reducing costs.

[0085] like Figure 8 As shown, this embodiment of the invention also provides a robotic arm control method applied to the robotic arm control system, which includes a main control terminal, an execution control terminal, and a target recognition device. The execution control terminal is mounted on the robotic arm, the main control terminal is connected to the execution control terminal, and the target recognition device is connected to both the execution control terminal and the main control terminal.

[0086] The central control unit receives a control request sent by the operator and generates a first positioning command based on the control request, which is then sent to the target identification device.

[0087] The target recognition device images the target object according to the first positioning command, forms an image of the target object, obtains target positioning information based on the target object image, and sends it to the central control terminal to generate a second positioning command.

[0088] The execution control terminal performs real-time positioning of the end effector of the robotic arm according to the second positioning command, obtains end effector positioning information, and sends it to the main control terminal;

[0089] The central control unit determines whether the target positioning information and the end-effector positioning information are consistent. If they are, a grasping command is generated. If not, the rotation node information of the robotic arm is calculated based on the inverse kinematics algorithm, the target positioning information, and the end-effector positioning information. A movement command is generated based on the rotation node information.

[0090] The execution control terminal performs a grasping operation on the target object according to the grasping instruction; it is also used to control the robotic arm to move to the target object according to the movement instruction, and perform a grasping operation on the target object when it reaches the target object.

[0091] Preferably, the target object is imaged to form an image of the target object, and the target positioning information is obtained based on the target object image, specifically as follows:

[0092] A grating is projected onto the surface of a target object, and an image of the target object is formed based on the grating using a camera element.

[0093] Based on the target object image and the coordinate transformation formula, the target object is transformed from world coordinates to pixel coordinates to obtain target positioning information. The coordinate transformation formula is as follows:

[0094]

[0095] Among them, X w ,Y w Z w Let u and v be points in the world coordinate system of the target object, and let u and v be points in the image coordinate system of the target object.

[0096] Preferably, the corner node information of the robotic arm is calculated based on the inverse kinematics algorithm, the target positioning information, and the end effector positioning information, specifically as follows:

[0097] Based on the end-effector positioning information and the working range of the robotic arm, the geometric relationship between the end-effector node and the corner node of the robotic arm is established, specifically as follows:

[0098] Let the end effector node of the robotic arm be S3, and the corner nodes of the robotic arm be S1 and S2, where S1 is located at the front end of the robotic arm and S2 is located between S1 and S3; let the working range of the robotic arm be [l1-l2, l1+l2], where l1 is the distance between S1 and S2, l2 is the distance between S2 and S3, and a coordinate system is established with S1 as the origin. The angle between the robotic arm between S1 and S2 and the vertical axis is θ1, and the angle between the robotic arm between S1 and S2 and between the robotic arm between S2 and S3 is θ2. Given the end effector positioning information of the end effector node of the robotic arm as (L, H), where L is the horizontal coordinate and H is the vertical coordinate.

[0099] Establish the geometric relationship between the end effector node and the corner node of the robotic arm:

[0100]

[0101] Where l1 > l2, the working range of the robotic arm is [l1-l2, l1+l2];

[0102] Assuming the target location information is the endpoint, the corner node information for the endpoint moving from the starting point to the intermediate point and from the intermediate point to the endpoint is determined based on the inverse kinematics algorithm and the geometric relationship. Specifically:

[0103] Based on the inverse kinematics algorithm and the aforementioned geometric relationships, the rotation angle of each corner node when the end node moves from the starting point to the intermediate point is calculated.

[0104] Based on the inverse kinematics algorithm and the aforementioned geometric relationships, the rotation angle of each corner node from the intermediate point to the endpoint is calculated. The formula for the inverse kinematics algorithm is as follows:

[0105]

[0106] Where L>0, the angle between the robotic arm between S2 and S3 and the horizontal axis is θ3, θ3 is the angle of the actuator of the end node, and the actuator of the end node is ensured to be in a horizontal state, and θ1 and θ2 are the rotation angles of the corner node S1 and the corner node S2.

[0107] The following is through Figure 9 Describe the remote control process of the robotic arm control system during assembly:

[0108] Remote control processes can be divided into manual control mode and automatic control mode.

[0109] In manual control mode, control signals are sent to the STM32 main control chip at the execution control end via the control panel. The STM32 main control chip controls the robotic arm and positions the slide to grasp the target object. The target recognition device locates the placement area, detects the position of the placement area, determines the target placement position through scanning and comparison, and places the target object at that position.

[0110] In automatic control mode, the main control unit sends a positioning command to the STM32 main control chip at the execution control unit to locate the target position. The target is detected and located using a camera. The main control unit generates movement commands based on the calculation process of the robotic arm's corner nodes and sends them to the STM32 main control chip. The STM32 main control chip then controls the robotic arm to grasp the target object. The STM32 main control chip controls the robotic arm and positions the slide table based on the corner node information to grasp the target object. A target recognition device locates and detects the placement area, and the target placement position is determined through scanning and comparison. The target object is then placed at that position.

[0111] Compared with existing technologies, this invention achieves remote control of a robotic arm by combining a central control terminal, an execution control terminal, and a target recognition device. It realizes highly automated target recognition, grasping, and placement at a lower cost, enabling the invention to efficiently and accurately complete target grasping and placement tasks. It can replace manual labor in different work scenarios, improving production efficiency while reducing costs.

[0112] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0113] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described apparatus and unit can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0114] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0115] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention, depending on actual needs.

[0116] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A robotic arm control system, characterized in that, It includes a central control terminal, an execution control terminal, and a target identification device. The central control terminal is connected to the execution control terminal, and the target identification device is connected to both the execution control terminal and the central control terminal. The main control terminal is used to receive control requests sent by the operator, generate a first positioning command through the control request, and send it to the target recognition device. The target recognition device is used to image the target object according to the first positioning command, form a target object image, obtain target positioning information based on the target object image, and send it to the main control terminal to generate a second positioning command. The execution control terminal is used to perform real-time positioning of the end node of the robotic arm according to the second positioning command, obtain end positioning information, and send it to the main control terminal; The main control terminal is used to determine whether the target positioning information and the end-effector positioning information are consistent. If they are, a grasping command is generated. If not, the corner node information of the robotic arm is calculated based on the inverse kinematics algorithm, the target positioning information and the end-effector positioning information, and a movement command is generated based on the corner node information. The execution control terminal is used to perform a grasping operation on the target object according to the grasping instruction; it is also used to control the robotic arm to move to the target object according to the movement instruction, and perform a grasping operation on the target object when it reaches the target object. The rotation node information of the robotic arm is calculated based on the inverse kinematics algorithm, the target positioning information, and the end effector positioning information, specifically as follows: Based on the end-effector positioning information and the working range of the robotic arm, the geometric relationship between the end-effector node and the corner node of the robotic arm is established, including: Let the end effector of the robotic arm be... The corner node of the robotic arm is and , Located at the front end of the robotic arm, lie in and Between; let the working range of the robotic arm be , where l1 is and The distance between them, l2 is and The distance between them Establish a coordinate system with the origin as the coordinate point. and The angle between the robotic arm and the vertical axis is , and between robotic arms and and The angle between the robotic arms is Given the end-effector positioning information of the robotic arm's end-effector as (L, H), where L is the x-coordinate and H is the y-coordinate, Establish the geometric relationship between the end effector node and the corner node of the robotic arm: ， in, ; Assuming the target positioning information is the endpoint, the corner node information for the end node moving from the starting point to the intermediate point and from the intermediate point to the endpoint is determined based on the inverse kinematics algorithm and the geometric relationship, including: Based on the inverse kinematics algorithm and the aforementioned geometric relationships, the rotation angle of each corner node when the end node moves from the starting point to the intermediate point is calculated. Based on the inverse kinematics algorithm and the aforementioned geometric relationships, the rotation angle of each corner node from the intermediate point to the endpoint is calculated. The formula for the inverse kinematics algorithm is as follows: ， ， Where L>0, and The angle between the robotic arm and the horizontal axis is , The angle of the actuator at the end node, ensuring that the actuator at the end node is in a horizontal position. and Corner node With corner nodes The rotation angle.

2. The robotic arm control system according to claim 1, characterized in that, In the target recognition device, the target object is imaged to form an image of the target object, and target positioning information is obtained based on the target object image, specifically as follows: A grating is projected onto the surface of a target object, and an image of the target object is formed based on the grating using a camera element. Based on the target object image and the coordinate transformation formula, the target object is transformed from world coordinates to pixel coordinates to obtain target positioning information. The coordinate transformation formula is as follows: ， in, , , Let be the point of the target object in the world coordinate system. , The point is located in the coordinate system of the target object's image.

3. The robotic arm control system according to claim 1, characterized in that, In the execution control terminal, the target object is grasped, specifically as follows: A monocular ranging model is established based on coordinate transformation. The distance between the robotic arm mounted on the robotic arm and the target object is calculated using the monocular ranging model. The monocular ranging model is as follows: ， in, This indicates the distance between the robotic arm and the target object; F represents the camera focal length. Indicates the height at which the camera is mounted. This represents the ordinate of the midpoint of the bottom of the target object, obtained from the image coordinate system. This represents the ordinate of the horizon obtained from the image coordinate system. Indicates the angle between the camera's optical axis and the ground. The robotic arm is controlled to grasp the target object based on the distance between the robotic arm and the target object.

4. The robotic arm control system according to claim 1, characterized in that, It also includes a slide module, which includes a double linear guide threaded rod, a slide, and a stepper motor. The slide is slidably connected to the double linear guide threaded rod, and the robotic arm is mounted on the slide. The stepper motor controls the rotation of the double linear guide threaded rod, and the rotation of the double linear guide threaded rod drives the slide and the robotic arm to reciprocate on the double linear guide threaded rod.

5. The robotic arm control system according to claim 4, characterized in that, The execution control terminal is also used to send control signals to the stepper motor, specifically: The angular velocity of the stepper motor is converted into the moving speed of the slide table using a speed conversion formula. A control signal is then generated based on the moving speed of the slide table. The speed conversion formula is as follows: ， Where v is the moving speed of the slide table, Ph is the lead of the double linear guide threaded rod, and ω is the relative angular velocity of the stepper motor.

6. The robotic arm control system according to claim 1, characterized in that, The execution control terminal is also used to send a scanning command to the target recognition device when the target object is captured; The target recognition device is used to scan the positioning area according to the scanning command, and determine whether it is the target placement location according to the scanning result. If it is, the device sends a placement command to the execution control terminal; otherwise, the device sends a move to the next location command to the execution control terminal. The execution control terminal is also used to control the robotic arm's robotic hand to place the target object at the target placement position according to the placement instruction; and is also used to control the robotic arm's robotic hand to move to the next position according to the move to the next position instruction.

7. A robotic arm control method, applied to the robotic arm control system according to any one of claims 1 to 6, comprising a main control terminal, an execution control terminal, and a target recognition device, wherein the main control terminal is connected to the execution control terminal, and the target recognition device is connected to both the execution control terminal and the main control terminal; characterized in that, The central control unit receives a control request sent by the operator and generates a first positioning command based on the control request, which is then sent to the target identification device. The target recognition device images the target object according to the first positioning command, forms an image of the target object, obtains target positioning information based on the target object image, and sends it to the central control terminal to generate a second positioning command. The execution control terminal performs real-time positioning of the end effector of the robotic arm according to the second positioning command, obtains end effector positioning information, and sends it to the main control terminal; The central control unit determines whether the target positioning information and the end-effector positioning information are consistent. If they are, a grasping command is generated. If not, the rotation node information of the robotic arm is calculated based on the inverse kinematics algorithm, the target positioning information, and the end-effector positioning information. A movement command is generated based on the rotation node information. The execution control terminal performs a grasping operation on the target object according to the grasping instruction; it is also used to control the robotic arm to move to the target object according to the movement instruction, and perform a grasping operation on the target object when it reaches the target object; The rotation node information of the robotic arm is calculated based on the inverse kinematics algorithm, the target positioning information, and the end effector positioning information, specifically as follows: Based on the end-effector positioning information and the working range of the robotic arm, the geometric relationship between the end-effector node and the corner node of the robotic arm is established, including: Let the end effector of the robotic arm be... The corner node of the robotic arm is and , Located at the front end of the robotic arm, lie in and Between; let the working range of the robotic arm be , where l1 is and The distance between them, l2 is and The distance between them Establish a coordinate system with the origin as the coordinate point. and The angle between the robotic arm and the vertical axis is , and between robotic arms and and The angle between the robotic arms is Given the end-effector positioning information of the robotic arm's end-effector as (L, H), where L is the x-coordinate and H is the y-coordinate, Establish the geometric relationship between the end effector node and the corner node of the robotic arm: ， in, ; Assuming the target positioning information is the endpoint, the corner node information for the end node moving from the starting point to the intermediate point and from the intermediate point to the endpoint is determined based on the inverse kinematics algorithm and the geometric relationship, including: Based on the inverse kinematics algorithm and the aforementioned geometric relationships, the rotation angle of each corner node when the end node moves from the starting point to the intermediate point is calculated. Based on the inverse kinematics algorithm and the aforementioned geometric relationships, the rotation angle of each corner node from the intermediate point to the endpoint is calculated. The formula for the inverse kinematics algorithm is as follows: ， ， Where L>0, and The angle between the robotic arm and the horizontal axis is , The angle of the actuator at the end node, ensuring that the actuator at the end node is in a horizontal position. and Corner node With corner nodes The rotation angle.

8. The robotic arm control method according to claim 7, characterized in that, The target object is imaged to form an image of the target object, and the target location information is obtained based on the target object image, specifically as follows: A grating is projected onto the surface of a target object, and an image of the target object is formed based on the grating using a camera element. Based on the target object image and the coordinate transformation formula, the target object is transformed from world coordinates to pixel coordinates to obtain target positioning information. The coordinate transformation formula is as follows: ， in, , , Let be the point of the target object in the world coordinate system. , The point is located in the coordinate system of the target object's image.

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