Sorting mechanical arm control system based on two-dimensional code recognition

Abstract

The invention relates to the field of industrial robot control, discloses a sorting mechanical arm control system based on two-dimensional code recognition, and aims to improve the recognition efficiency and the automatic control capability in the material sorting process. According to the system, an industrial camera is used for collecting a material image with a two-dimensional code, a two-dimensional code recognition module is used for analyzing the content of the two-dimensional code, and the category, position information and a sorting instruction of the material are obtained. Compared with a traditional recognition mode based on colors, shapes or depth images, the two-dimensional code has the advantages of being high in recognition accuracy, small in background interference, high in recognition speed, high in information bearing capacity, simple in implementation algorithm and the like, and the response efficiency and the control precision of a system can be remarkably improved. The system completes conversion from an image coordinate to a mechanical arm coordinate system through the computer processing unit, generates a control instruction in combination with inverse kinematics and a path planning algorithm, and drives the mechanical arm to complete material grabbing and placing operation. The system is simple in structure, stable in recognition, high in adaptability and suitable for various automatic sorting application scenes such as intelligent warehousing, production lines and sorting centers.

Description

Technical Field

[0001] The present invention relates to the field of industrial robot control, and specifically to a sorting robotic arm control system based on QR code recognition, aiming to improve the recognition efficiency and automatic control ability during the material sorting process. Background Art

[0002] With the continuous improvement of industrial automation level, robotic arms are widely used in tasks such as sorting and handling on production lines. However, existing sorting systems generally rely on traditional material recognition methods such as color, shape, and depth images. These methods have disadvantages such as low recognition accuracy, sensitivity to environmental interference, and slow processing speed, and are difficult to meet the increasingly complex production requirements. Especially in fast, efficient, and accurate automatic sorting scenarios, traditional technologies often cannot achieve ideal performance.

[0003] Due to its large information carrying capacity, strong anti-interference ability, and efficient recognition ability, QR code technology has gradually been widely used in the fields of logistics and warehousing in recent years. QR codes can provide detailed information for materials in a simple and efficient manner, and the recognition process is not significantly affected by environmental complexity. However, existing sorting robotic arm systems have not fully combined QR code technology. Especially in scenarios of dynamic operation and multi-material classification, how to effectively combine QR code recognition with the robotic arm control system to achieve efficient material grasping and placement is still an urgent problem to be solved.

[0004] Therefore, it is very meaningful to design a new sorting robotic arm control system based on QR code recognition, which can combine QR code recognition technology, visual information processing, robotic arm control, and path planning algorithms to solve the problems of efficiency, accuracy, and adaptability in traditional sorting systems. This will improve the automation level during the material sorting process and be widely applicable to automatic sorting applications such as intelligent warehousing, production lines, and logistics sorting centers. Summary of the Invention

[0005] The present invention provides a sorting robotic arm control system based on QR code recognition, aiming to improve the automatic control ability and recognition efficiency during the material sorting process through QR code recognition technology. The system collects images of materials with QR code labels through an industrial camera, uses a QR code recognition module to analyze the content of the QR code, obtains the category, position information, and sorting instructions of the materials, and finally completes the material grasping and placement operations through the robotic arm.

[0006] To implement the technical solution of the present invention, first, an industrial camera is selected as the image acquisition unit to obtain real-time images of materials with QR code labels on the workbench;

[0007] Next, the collected images are processed by a QR code recognition module to analyze the QR code and obtain the category information and position information of the target material;

[0008] The system further uses a computer processing module to convert the coordinate information in the QR code image into three-dimensional space coordinates in the robotic arm coordinate system, and generates control instructions by combining inverse kinematics algorithms and path planning;

[0009] The control instructions drive the end effector of the robotic arm to complete the material grasping operation through the path planning and motion control module. The end effector is of a gripper structure and has the ability to adapt to different materials for grasping;

[0010] After the grasping operation is completed, the robotic arm moves the material to the specified position according to the control instructions, places the material and completes the task;

[0011] Among them, the system combines the computer vision module and the depth camera module to further improve the accuracy of material positioning. The depth camera provides three-dimensional space information of the object to ensure that the robotic arm can accurately execute tasks;

[0012] The QR code recognition module of the present invention is based on the OpenCV image processing library. By steps such as image grayscale, filtering, binarization, morphological closing operation and perspective correction, the QR code area is extracted, thereby effectively improving the recognition accuracy of the QR code and ensuring efficient execution during the sorting process;

[0013] The computer processing module also establishes a mapping relationship between the industrial camera coordinate system and the robotic arm coordinate system through hand-eye calibration technology, so as to accurately calculate the position of the target object in three-dimensional space and ensure that the robotic arm can make an accurate response according to the image coordinates;

[0014] The path planning module of the present invention adopts the MoveIt motion planning module based on the ROS framework. Through inverse kinematics and path planning algorithms, the robotic arm can calculate the optimal motion trajectory, thereby ensuring that the robotic arm can efficiently and accurately complete tasks;

[0015] The control module of the present invention realizes real-time communication with the robotic arm control unit through the TCP / IP protocol and supports the collaborative work of multiple robotic arms, improving the flexibility and collaboration ability of the system;

[0016] The end effector is equipped with a force sensor to monitor the clamping force in real time and dynamically adjust the gripper force to avoid damage or slipping of the material during the grasping process, ensuring the safety and stability of the grasping operation;

[0017] Through the present invention, the material sorting system can efficiently and accurately complete the grasping and placing operations of materials, and has broad application prospects in application scenarios such as intelligent warehousing, production lines, and logistics sorting centers. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is the overall block diagram of the system structure;

[0019] Figure 2 is the system working flow chart; Specific implementation manners

[0020] To clearly illustrate the above objects and features of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific implementation manners.

[0021] It should be noted that the following detailed descriptions are all illustrative and are intended to provide further descriptions of the present invention.

[0022] Implementation example.

[0023] As Figure 1 shown, this embodiment provides a sorting robotic arm control system based on QR code recognition, which is mainly applied to the express sorting scenario. The system includes a six-degree-of-freedom robotic arm, an industrial camera, a QR code recognition module, a computer processing module, and an end effector, etc.;

[0024] In this embodiment, the materials are first divided into three types of express boxes, and each express box is pasted with a unique QR code. To accurately classify and grab the materials, it is first necessary to collect the images with QR codes through the industrial camera. In the system, the industrial camera is used to obtain images in real time, and the QR code recognition module is responsible for parsing the content in the QR code and extracting the category (such as the size of the express box) and position information of the target material;

[0025] The QR code recognition module used in this system is based on the OpenCV image processing library. The image is processed through techniques such as grayscale conversion, filtering, binarization, morphological closing operation, and perspective correction to accurately extract the QR code area from the image and decode the QR code. Compared with traditional color or shape recognition methods, the QR code provides higher recognition accuracy and stronger anti-interference ability, so as to be able to adapt to a variety of complex environments;

[0026] After the QR code recognition is completed, the computer processing module combines the hand-eye calibration technology according to the image coordinates and the position information in the QR code to convert the image coordinates into three-dimensional coordinates in the base coordinate system of the robotic arm. To achieve this conversion, the system performs internal parameter calibration on the industrial camera through the Zhang Zhengyou calibration method and calculates the mapping relationship between the camera coordinate system and the robotic arm coordinate system through the nine-point calibration method;

[0027] Next, the system uses inverse kinematics and path planning algorithms to generate the motion path of the robotic arm. The path planning module is based on the ROS framework and the MoveIt module, and calculates the exact pose required by the end effector of the robotic arm through inverse kinematics, so as to ensure that the robotic arm can accurately reach the target position;

[0028] Subsequently, the robotic arm moves according to the generated path instructions, and the end effector (gripper) performs a grasping action according to the control instructions. During the grasping process, the end effector monitors the clamping force in real time through the integrated force sensor to ensure the stability and safety during the grasping process, and to avoid damage or slipping of the express box;

[0029] After completing the material grasping, the robotic arm transports the material to the designated position according to the control instructions. The system ensures the accuracy of the robotic arm's path during the transportation process through the path planning and motion control module, and finally places the express box in the target area. If the task includes the "placement" operation of the material, the system will continue to plan the action path and place the material at the designated target position;

[0030] After the task is completed, the system automatically returns to the standby state to prepare for the next round of sorting tasks;

[0031] The entire task process is as Figure 2 shown.

[0032] The above is only the preferred embodiment of the present invention. In addition, for those of ordinary skill in the art in this technical field, various changes and modifications can be made to the invention while maintaining the principle of the present invention. If the modifications and variations fall within the scope of the claims of the present invention and their equivalent technologies, these modifications and variations should also be regarded as within the protection scope of the present invention.

Claims

1. A sorting robotic arm control system based on QR code recognition, characterized in that, Including: An industrial camera, a QR code recognition module, a computer processing module, a robotic arm and its end effector; Among them, the industrial camera is used to collect the material image containing the QR code; The QR code recognition module is used to parse the QR code and obtain the category information and position information of the target material; The computer processing module is used to convert the image coordinates where the QR code is located into three-dimensional coordinates in the robotic arm coordinate system, and generate control instructions by combining the inverse kinematics algorithm and path planning; The robotic arm execution module is used to complete the grasping and sorting placement operations of the target material according to the control instructions.

2. The system according to claim 1, wherein The QR code recognition module is based on the OpenCV image processing library, extracts the QR code area through image grayscale conversion, filtering, binarization, morphological closing operation and perspective correction, and locates and decodes the QR code pattern.

3. The system according to claim 1, wherein The computer processing module establishes the mapping relationship between the image coordinate system and the robotic arm base coordinate system based on hand-eye calibration to achieve spatial positioning.

4. The system according to claim 1, wherein The path planning uses the MoveIt module under the ROS framework for motion planning and trajectory generation.

5. The system according to claim 1, characterized in that The control module realizes real-time communication with the robotic arm control unit through the local area network (LAN) of the TCP / IP protocol and supports the collaborative work of multiple robotic arms.

6. The system according to claim 1, wherein The robotic arm is a six-degree-of-freedom robotic arm, and a gripper end effector is assembled at the end for performing object grasping, moving and placing operations.

7. The system according to claim 1, wherein The end effector is integrated with a force sensor to real-time monitor the contact force during the grasping process, and dynamically adjust the clamping force of the gripper according to the feedback to avoid material damage.

8. A method for remotely controlling a robotic arm based on the system according to any one of claims 1 to 7, characterized in that, Including the following steps: Step 1: A method for remotely controlling a robotic arm based on the system according to any one of claims 1 to 7, characterized by including the following steps; Step 2: Collect the object image through the industrial camera, identify and parse the QR code information; Step 3: According to the recognized QR code information, extract the object position information, and generate the action path of the robotic arm through coordinate conversion and inverse kinematics calculation; Step 4: The robotic arm executes the grasping operation according to the generated path instruction; Step 5: After the robotic arm completes the grasping, place the material at the specified position according to the instruction requirements; Step 6: After completing the task, the system ends the current operation and prepares for the next sorting task.

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