Mechanical arm control grabbing system based on three-dimensional visual recognition

Abstract

The utility model discloses a mechanical arm control grabbing system based on three-dimensional visual identification. The grabbing system comprises a mechanical arm, a mechanical arm control board and a Linux main control board which are installed on a base, a three-dimensional depth camera is installed on the mechanical arm and is consistent with a clamping jaw of the mechanical arm in direction, the three-dimensional depth camera is used for obtaining three-dimensional space information and transmitting the three-dimensional space information to the Linux main control board, and the Linux main control board analyzes the three-dimensional space information and issues a control instruction to the mechanical arm control board. And the mechanical arm executes grabbing operation. According to the utility model, the surrounding environment is scanned through the three-dimensional depth camera, three-dimensional information in a space is captured, the three-dimensional space information is analyzed through the Linux main control board, different objects are identified and distinguished, the Linux main control board calculates the accurate positions of the objects, then a control instruction is generated and sent to the mechanical arm control board, and the mechanical arm control board controls the mechanical arm to work. The mechanical arm is used for controlling the mechanical arm to grab an object at a proper angle, and the grabbing convenience and accuracy are improved.

Description

Technical Field

[0001] The utility model relates to the technical field of robot arm control grasping, in particular to a robot arm control grasping system based on three-dimensional visual recognition. Background Art

[0002] Currently, most robotic arms on the market are equipped with ordinary 2D cameras, which cannot detect the exact position of objects in front of the camera. Therefore, most high-precision gameplay cannot be achieved. The objects to be clamped can only be set in a fixed position. When the robotic arm clamps, it still needs to use a fixed posture to clamp, which makes it impossible to perform convenient and accurate clamping. Utility Model Content

[0003] The purpose of the utility model is to overcome the deficiencies of the prior art and provide a robotic arm controlled grasping system based on three-dimensional visual recognition.

[0004] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0005] An embodiment of the utility model provides a robotic arm control grasping system based on three-dimensional visual recognition, comprising: a base, a robotic arm, a Linux main control board, a robotic arm control board and a three-dimensional depth camera, wherein the robotic arm, the robotic arm control board and the Linux main control board are installed on the base, the three-dimensional depth camera is installed on the robotic arm and is consistent with the direction of the gripper of the robotic arm, the robotic arm control board and the three-dimensional depth camera are electrically connected to the Linux main control board, the robotic arm is electrically connected to the robotic arm control board, the three-dimensional depth camera is used to obtain three-dimensional spatial information and transmit it to the Linux main control board, the Linux main control board is used to parse the three-dimensional spatial information and issue control instructions to the robotic arm control board, and the robotic arm is used to perform grasping operations according to the control instructions transmitted to the robotic arm control board.

[0006] In a specific embodiment, the Linux main control board is further connected to a wireless communication module.

[0007] In a specific embodiment, the robotic arm control board is further connected to an OLED screen module.

[0008] In a specific embodiment, a protective shell is installed in the area of ​​the base located at the Linux main control board and the robotic arm control board.

[0009] In a specific embodiment, the protective shell is further connected to a speech synthesis and announcement module, and the speech synthesis and announcement module is electrically connected to the robotic arm control board.

[0010] In a specific embodiment, the protective shell is further connected to a voice recognition module, and the voice recognition module is electrically connected to the robotic arm control board.

[0011] In a specific embodiment, the protective shell is further connected to a touch screen, and the touch screen is electrically connected to the Linux main control board.

[0012] In a specific embodiment, the three-dimensional depth camera is fixed to the robotic arm via a bracket.

[0013] In a specific embodiment, the base is further connected to a plurality of suction cup members.

[0014] In a specific embodiment, the robotic arm is fixed to the base via a mounting base.

[0015] The robotic arm control grasping system based on three-dimensional visual recognition of the present utility model has the following advantages compared with the existing technology: the surrounding environment or designated space is scanned in all directions and at multiple angles by a three-dimensional depth camera, and detailed three-dimensional information in the space can be captured to provide data support for subsequent operations. The three-dimensional spatial information obtained by the three-dimensional depth camera is then analyzed by the Linux main control board to identify and distinguish different objects. Once the object is identified, the Linux main control board can calculate the precise position of the object in the three-dimensional space, and then generate and send control instructions to the robotic arm control board. The robotic arm grasps the object at an appropriate angle according to the control instructions transmitted to the robotic arm control board, thereby improving the convenience and accuracy of grasping.

[0016] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. 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 these drawings without paying any creative labor.

[0018] Figure 1 A schematic diagram of the structure of a robotic arm controlled grasping system based on three-dimensional visual recognition provided by the present invention;

[0019] Figure 2 This is a schematic diagram of the decomposition of the robotic arm controlled grasping system based on three-dimensional visual recognition provided by the utility model. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0022] 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" and the like to 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 device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0023] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. In the description of this utility model, "plurality" means two or more, unless otherwise specifically defined.

[0024] In this utility model, unless otherwise specified or limited, the terms "installed," "connected," "connect," "fixed," etc. should be understood in a broad sense. For example, they can refer to connection, detachable connection, or integration; mechanical connection or electrical connection; direct connection or indirect connection through an intermediate medium; internal communication between two components or interaction between two components. For those skilled in the art, the specific meanings of the above terms in this utility model can be understood according to specific circumstances.

[0025] In the present invention, unless otherwise expressly specified or limited, a first feature being "above" or "below" a second feature may include the first and second features being in direct contact, or may include the first and second features being in contact not directly but through another feature between them. Moreover, a first feature being "above," "above," and "above" a second feature may include the first feature being directly above or obliquely above the second feature, or may simply mean that the first feature is higher in level than the second feature. A first feature being "below," "below," and "below" a second feature may include the first feature being directly below or obliquely below the second feature, or may simply mean that the first feature is lower in level than the second feature.

[0026] In the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean 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 expressions of the above terms should not be understood as necessarily referring to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine the different embodiments or examples described in this specification.

[0027] See also Figures 1 to 2 In the specific embodiment shown, the present invention discloses a robotic arm control grasping system based on three-dimensional visual recognition, including: a base 10, a robotic arm 20, a Linux main control board 30, a robotic arm control board 50 and a three-dimensional depth camera 40, wherein the robotic arm 20, the robotic arm control board 50 and the Linux main control board 30 are installed on the base 10, the three-dimensional depth camera 40 is installed on the robotic arm 20 and is consistent with the gripper direction of the robotic arm 20, the robotic arm control board 50 and the three-dimensional depth camera 40 are electrically connected to the Linux main control board 30, the robotic arm 20 is electrically connected to the robotic arm control board 50, the three-dimensional depth camera 40 is used to obtain three-dimensional spatial information and transmit it to the Linux main control board 30, the Linux main control board 30 is used to parse the three-dimensional spatial information and issue control instructions to the robotic arm control board 50, and the robotic arm 20 is used to perform a grasping operation according to the control instructions transmitted to the robotic arm control board 50.

[0028] The 3D depth camera 40 is an RGBD depth camera that can obtain color and depth images of the identified object, thereby obtaining the coordinates of the pixel points and the value of the depth information. The robotic arm control board 50 is also connected to a power module to provide power to the entire system.

[0029] Specifically, by designing the 3D depth camera 40 to be located at the end of the robotic arm 20 and aligned with the orientation of the gripper, i.e., "eyes in hand," not only can the robot's motion control be achieved, but the 3D depth camera 40 can also capture the 3D coordinates of objects based on the 3D depth camera 40's coordinate system, thereby more accurately implementing AI visual recognition, spatial tracking, and spatial grasping. In other words, the 3D depth camera 40 performs a full-scale, multi-angle scan of the surrounding environment or a designated space, capturing detailed 3D information within the space and providing data support for subsequent operations. The Linux main control board 30 then analyzes the 3D spatial information acquired by the 3D depth camera 40 to identify and distinguish different objects. Once an object is identified, the Linux main control board 30 calculates the object's precise position in 3D space and then generates and sends control instructions to the robotic arm control board 50. Based on the control instructions transmitted to the robotic arm control board 50, the robotic arm 20 grasps the object at an appropriate angle, improving the convenience and accuracy of grasping.

[0030] More specifically, the robotic arm control board 50 receives command signals from the Linux main control board 30. These signals are typically parsed based on spatial information acquired by the 3D depth camera 40 and features such as the object's position and outline. The robotic arm control board 50 then converts these command signals into drive signals that the robotic arm 20 can understand and execute. Furthermore, the robotic arm control board 50 controls the various joints and motors of the robotic arm 20, enabling the robotic arm 20 to move along a predetermined trajectory and speed. This motion can be linear, rotational, or complex, depending on the content of the control command. Furthermore, within the entire system, the robotic arm control board 50 works in conjunction with components such as the Linux main control board 30 and the 3D depth camera 40 to form a complete closed-loop control system. Through real-time information exchange and command execution, the system achieves precise control of the motion of the robotic arm 20. Furthermore, the presence of the robotic arm control board 50 enables the robotic arm 20 to perform grasping operations more accurately. Through precise motor control and motion trajectory planning, the system ensures that the robotic arm 20 optimally approaches and grasps the target object, thereby improving grasping accuracy and success rate.

[0031] In one embodiment, the Linux main control board 30 is further connected to a wireless communication module 60 .

[0032] Specifically, the wireless communication module 60 allows the operator to remotely control the robot arm 20 from a location far away from it, which is particularly important for the robot arm 20 that needs to operate in an environment that is dangerous or not suitable for human work. The operator can use a terminal device (such as a mobile phone, tablet computer or computer) to send instructions to the Linux main control board 30 through the wireless communication module 60, and the Linux main control board 30 then transmits the instructions to the robot arm 20 to achieve remote control and monitoring. In addition, the addition of the wireless communication module 60 enhances the scalability of the system. With the popularization of the Internet of Things and smart devices, more and more devices support wireless connections. Through the wireless communication module 60, the system can connect and interact with other smart devices to achieve more diverse functions and applications; for example, the system can be connected to a smart home system to achieve functions such as moving and organizing items in a smart home.

[0033] In one embodiment, the robotic arm control board 50 is further connected to an OLED screen module 70 .

[0034] Specifically, the OLED screen module 70 can intuitively display the CPU occupancy rate, system time, storage occupancy rate, memory occupancy rate, and IP address. Among them, the real-time display of the CPU occupancy rate can help the operator understand the operating load of the system; when the CPU occupancy rate is too high, it may mean that the system is processing a large amount of data or there are certain abnormalities. At this time, the operator can take appropriate measures to intervene. In addition, displaying the current system time helps the operator to grasp the work progress and arrange tasks reasonably; at the same time, the system time is also an important reference for system logs and event records. In addition, by displaying the storage space occupancy rate, the operator can understand the remaining amount of system storage resources and avoid system crashes or data loss caused by insufficient storage space. In addition, the display of memory occupancy rate helps the operator understand the usage of the system memory and ensure that the system has sufficient memory resources to support the grasping operation of the robotic arm 20. In addition, the displayed IP address can help the operator quickly identify the network configuration of the system, facilitate network connection and communication settings, and when network problems occur, the IP address is also important information for troubleshooting.

[0035] In one embodiment, a protective shell 80 is installed in the area of ​​the base 10 located at the Linux main control board 30 and the robotic arm control board 50 .

[0036] Specifically, the primary function of the protective case 80 is to provide physical protection, preventing the Linux main control board 30 and the robotic arm control board 50 from external physical damage. During the operation of the robotic arm 20, it may encounter various complex environments and conditions, such as dust, vibration, and impact. The protective case 80 effectively isolates these external factors, ensuring that the electronic components and circuit boards within the Linux main control board 30 and the robotic arm control board 50 are not damaged, thereby extending the service life of the Linux main control board 30 and the robotic arm control board 50.

[0037] In one embodiment, the protective shell 80 is further connected to a speech synthesis and announcement module 90 , and the speech synthesis and announcement module 90 is electrically connected to the robotic arm control board 50 .

[0038] Specifically, the speech synthesis and announcement module 90 can broadcast status information or system prompts on the robot arm control panel 50 in real-time voice form. For example, when the robot arm 20 completes a grasping task, the system can use the speech synthesis and announcement module 90 to announce the prompt "grasping successful" to the operator, allowing the operator to promptly understand the working status of the robot arm 20. In addition, through the speech synthesis and announcement module 90, the operator can more intuitively understand the operation of the robot arm 20 without having to constantly pay attention to the displayed information on the robot arm control panel 50. This interactive method reduces reliance on vision, allowing the operator to clearly obtain system information even in more complex or noisy environments. At the same time, voice announcements also provide a more user-friendly interactive method, enhancing the ease of use and friendliness of the system.

[0039] In one embodiment, the protective shell 80 is further connected to a voice recognition module 100 , and the voice recognition module 100 is electrically connected to the robotic arm control board 50 .

[0040] Specifically, the core function of the voice recognition module 100 is to recognize the operator's voice commands and convert them into electrical signals for transmission to the robot arm control panel 50. This enables the operator to control the movement and grasping operation of the robot arm 20 through voice without having to manually operate the robot arm control panel 50 or buttons. For example, the operator can say commands such as "grab an object" or "move to a specified position", and the voice recognition module 100 will recognize these commands and transmit them to the robot arm control panel 50. The robot arm control panel 50 then drives the robot arm 20 to perform the corresponding action. In addition, the application of the voice recognition module 100 greatly improves the convenience of operating the robot arm 20 system. The operator does not need to directly contact the robot arm control panel 50 or other operating devices. The robot arm 20 can be remotely controlled by voice commands. This not only simplifies the operating process but also reduces the operator's labor intensity. In addition, the voice recognition module 100 makes the system more flexible, and the operator can adjust the working status and parameters of the robotic arm 20 at any time through voice commands according to actual conditions and needs; for example: when grasping objects of different shapes and sizes, the operator can adjust the grasping force and angle of the robotic arm 20 through voice commands to adapt to different grasping tasks.

[0041] In one embodiment, the protective shell 80 is further connected to a touch screen display 110 , and the touch screen display 110 is electrically connected to the Linux main control board 30 .

[0042] Specifically, the touch screen display 110 can display the control process effect of the robot arm 20 in real time, so that the operator can intuitively see the movement trajectory, grasping status and work progress of the robot arm 20. This visual display method helps the operator to better understand the operating status of the robot arm 20 and promptly discover and solve problems. In addition, the operator can also directly control the movement and grasping operations of the robot arm 20 by touching the buttons, sliders and other controls on the screen, without having to operate through traditional buttons or knobs. This touch method not only simplifies the operation process, but also improves the accuracy and flexibility of the operation. In addition, the touch screen display 110 provides the operator with a more intuitive and natural interaction method. The operator can interact with the robot arm 20 in real time through the touch screen, such as adjusting the grasping force, angle or speed of the robot arm 20. This interaction method not only enhances the ease of use of the system, but also improves the operator's sense of participation and satisfaction.

[0043] In one embodiment, the 3D depth camera 40 is fixed to the robotic arm 20 via a bracket 120 .

[0044] Specifically, the 3D depth camera 40 is securely attached to the robotic arm 20 via the bracket 120, effectively preventing image blur or distortion caused by camera shake during the capture process. This stability is crucial for 3D visual recognition systems because it directly affects the system's accuracy in identifying and locating objects. Furthermore, the secure connection between the 3D depth camera 40 and the robotic arm 20 ensures the reliability of the entire system. When the robotic arm 20 is performing high-speed movements or complex grasping tasks, if the 3D depth camera 40 shakes or falls off, it could cause the system to crash or the task to fail. Therefore, securely attaching the 3D depth camera 40 to the robotic arm 20 via the bracket 120 ensures stable system operation under various operating conditions.

[0045] In one embodiment, the base 10 is further connected to a plurality of suction cups 130 .

[0046] Specifically, the suction cup member 130 can fit tightly on the contact surface through its adsorption force, providing stable support for the device. This support is crucial to ensuring the stability of the device and preventing it from moving or tipping over during use. In particular, in application scenarios that require precise control and positioning, stable support is the basis for ensuring the normal operation of the device. In addition, in addition to providing support, the suction cup member 130 can also firmly fix the device on the contact surface through its strong adsorption force. This fixing effect helps prevent the device from shaking or displacing due to external forces during use, thereby ensuring the stability and accuracy of the device. In addition, the fixing effect of the suction cup member 130 can also effectively prevent the device from being damaged by accidental collisions or impacts.

[0047] In one embodiment, the robotic arm 20 is fixed to the base 10 via a mounting base 140 .

[0048] Specifically, one of the main functions of the mounting base 140 is to raise the working height of the robotic arm 20. By mounting the robotic arm 20 on a mounting base 140 of a certain height, the gripper at its end can reach a higher position, thereby being able to handle or grasp objects located at a higher position. This is particularly important for the robotic arm 20 that needs to cross obstacles or work in complex environments. In addition, the design of the mounting base 140 also helps to reduce the blind spots of the robotic arm 20 and the depth camera. When the robotic arm 20 is in a lower position, the depth camera's line of sight may be limited by the ground or low objects, resulting in an inability to clearly observe or identify certain areas. By raising the height of the robotic arm 20, the depth camera's line of sight can be made wider, thereby reducing blind spots and improving the accuracy and efficiency of grasping tasks.

[0049] Among them, the Linux main control board 30 adopts existing public technology, and can also be a Jetson series motherboard, which will not be elaborated in detail here. Similarly, the mechanical arm 20 and the mechanical arm control board 50 also adopt existing public technology.

[0050] In one embodiment, the workflow of the robotic arm controlled grasping system based on three-dimensional visual recognition is as follows:

[0051] Step 1: Use the RGBD depth camera to obtain color images and depth images, and then perform image recognition to obtain the center coordinates of the object and the depth value of the center coordinates;

[0052] Specifically, an open source image recognition library is used to identify specific objects. In the open source image recognition library, a recognition model for a specific object is selected or trained, and the aligned color image is input into the recognition model. The model will identify and classify the objects in the image, and the recognition model will output the object's bounding box, category label and other information; then, based on the bounding box information output by the recognition model, the center coordinates of the object are calculated. The center coordinates can be obtained by a simple calculation of the upper left and lower right coordinates of the bounding box; in the depth image, the corresponding depth value is found according to the center coordinates of the object. Since each pixel value in the depth image represents the actual distance measured by the sensor to the object, the pixel value corresponding to the center coordinate can be directly read as the depth value.

[0053] Step 2: Use the depth camera to obtain the depth information of the object. Combined with the image processing algorithm to obtain the pixel coordinates of the object and some built-in parameters of the camera, the coordinate system can be converted to convert the position of the object in the image coordinate system to the position in the camera coordinate system. Then, the position of the object in the camera coordinate system can be converted to the position in the coordinate system of the end of the robot arm 20.

[0054] Specifically, the depth camera can measure the distance between the object and the camera, provide the depth information of the object, and then through the image processing algorithm, the pixel coordinates of the object in the image coordinate system can be converted into the three-dimensional coordinates in the camera coordinate system. This conversion process requires the use of the camera's built-in parameters, such as focal length, optical center position, etc., and then through hand-eye calibration and other technologies, the conversion relationship between the camera coordinate system and the coordinate system of the end of the robotic arm 20 can be established, thereby realizing the conversion of the position of the object in the camera coordinate system into the position in the coordinate system of the end of the robotic arm 20.

[0055] Step 3: Enter the voice code corresponding to the specific command in advance and conduct voice interaction training;

[0056] Specifically, voice interaction training is performed through the speech synthesis and announcement module 90 and the speech recognition module 100 to obtain a training set for subsequent command control. By entering the voice code corresponding to a specific command in advance, a voice command library can be established. This library contains all the voice commands that may be issued by the user and their corresponding machine-recognizable codes. In addition, training is performed using the speech synthesis and announcement module 90 and the speech recognition module 100 so that the system can accurately recognize and understand the user's voice commands. During the training process, the system will continuously learn and optimize its processing and recognition capabilities for voice signals. After a lot of training, the system will generate a training set containing a variety of voice commands and their corresponding recognitions. This training set is the basis for subsequent command control and is used to achieve accurate matching of voice commands with machine actions.

[0057] Step 4: By issuing voice commands to control the gripper of the robotic arm 20 to reach the specified preset position, the grasping task or recognition task can be performed. After obtaining the grasping command, the Linux main control board 30 will call the depth camera through the robotic arm 20 to analyze the object position. After obtaining the accurate spatial coordinates, the Linux main control board 30 issues a grasping command to enable the gripper of the robotic arm 20 to grasp the object.

[0058] Specifically, the user can control the movement of the robotic arm 20 through simple voice commands without the need for complex manual operations or programming, which allows non-professionals to easily use the robotic arm 20 to perform grasping or recognition tasks. In addition, the user can set the preset positions that the grippers of the robotic arm 20 need to reach in advance. Through voice commands, the robotic arm 20 can automatically move to these preset positions and perform corresponding tasks. In addition, the Linux main control board 30 will call the depth camera to analyze the position information of the object. The depth camera can provide three-dimensional coordinate information of the object, allowing the robotic arm 20 to locate the object more accurately. After obtaining the accurate spatial coordinates of the object, the Linux main control board 30 will send a grasping instruction (i.e., a control instruction) to the robotic arm control board 50. The grippers of the robotic arm 20 accurately grasp the object according to the grasping instruction transmitted to the robotic arm control board 50, reducing errors and collisions during the grasping process.

[0059] Among them, the robotic arm control and grasping system based on three-dimensional visual recognition is highly intelligent and integrates three-dimensional visual recognition, voice recognition, voice broadcast and touch display functions. At the same time, it can replace a variety of high-performance main controls to adapt to the needs of complex scene recognition. In addition to controlling the robotic arm 20 through the touch display screen 110 integrated in the fuselage, it can also use the voice recognition module 100 and the voice synthesis broadcast module 90 to perform voice interaction to control the depth camera to scan the space in three dimensions and perceive objects, thereby realizing the robotic arm 20 tracking and adaptively clamping objects. Compared with the two-dimensional visual recognition robotic arm solution, the spatial scanning perception capability is enhanced, and the target space coordinates are obtained more accurately. Compared with the three-dimensional visual recognition robotic arm solution, it is more intelligent and more integrated. It can be interactively controlled with the robotic arm through voice, and the touch screen supports finger touch control of the robotic arm movement.

[0060] The above embodiments are preferred implementation schemes of the present invention. In addition, the present invention can also be implemented in other ways. Any obvious replacement without departing from the concept of the present technical solution is within the scope of protection of the present invention.

Claims

1. A robotic arm controlled grasping system based on three-dimensional visual recognition, characterized in that: include: A base, a robotic arm, a Linux main control board, a robotic arm control board and a three-dimensional depth camera, wherein the robotic arm, the robotic arm control board and the Linux main control board are installed on the base, the three-dimensional depth camera is installed on the robotic arm and is consistent with the gripper direction of the robotic arm, the robotic arm control board and the three-dimensional depth camera are electrically connected to the Linux main control board, the robotic arm is electrically connected to the robotic arm control board, the three-dimensional depth camera is used to obtain three-dimensional spatial information and transmit it to the Linux main control board, the Linux main control board is used to parse the three-dimensional spatial information and issue control instructions to the robotic arm control board, and the robotic arm is used to perform a grasping operation according to the control instructions transmitted to the robotic arm control board.

2. The robotic arm control grasping system based on three-dimensional visual recognition according to claim 1 is characterized in that: The Linux main control board is also connected to a wireless communication module.

3. The robotic arm control grasping system based on three-dimensional visual recognition according to claim 1, characterized in that: The robotic arm control board is also connected to an OLED screen module.

4. The robotic arm control grasping system based on three-dimensional visual recognition according to claim 1, characterized in that: The base is provided with a protective shell in the area of ​​the Linux main control board and the robotic arm control board.

5. The robotic arm control grasping system based on three-dimensional visual recognition according to claim 4 is characterized in that: The protective shell is also connected to a speech synthesis and broadcasting module, and the speech synthesis and broadcasting module is electrically connected to the robotic arm control board.

6. The robotic arm control grasping system based on three-dimensional visual recognition according to claim 4, characterized in that: The protective shell is also connected to a voice recognition module, and the voice recognition module is electrically connected to the robotic arm control board.

7. The robotic arm control grasping system based on three-dimensional visual recognition according to claim 4, characterized in that: The protective shell is also connected to a touch screen, and the touch screen is electrically connected to the Linux main control board.

8. The robotic arm control grasping system based on three-dimensional visual recognition according to claim 1, characterized in that: The three-dimensional depth camera is fixed to the robotic arm through a bracket.

9. The robotic arm control grasping system based on three-dimensional visual recognition according to claim 1, characterized in that: The base is also connected to a plurality of suction cup members.

10. The robotic arm control grasping system based on three-dimensional visual recognition according to claim 1, characterized in that: The robotic arm is fixed to the base via a mounting base.

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