Modularized intelligent visual industrial mechanical arm and implementation method thereof

Abstract

The invention belongs to the field of multi-degree-of-freedom mechanical arms, and provides a modularized intelligent visual industrial mechanical arm and an implementation method thereof.The modularized intelligent visual industrial mechanical arm comprises a mechanical arm body, a central control case and a fixed operation table; the mechanical arm body comprises a first motor, a second motor, a third motor, a fourth motor, a fifth motor, a sixth motor, a mechanical arm main board, a mechanical arm base, a display screen, a mechanical arm power switch, mechanical arm keys, a camera module and a flexible clamping jaw module. The central control case comprises a case shell, a case power panel, a board card, a voice module, a case base, a case emergency stop switch and a case power switch; the fixed operation table comprises an operation table bottom plate, a tray and foot pads; through virtual model simulation and real linkage of a real mechanical arm, a software and hardware integrated architecture is realized, the man-machine interaction performance is improved, and auxiliary support of teaching tasks in a teaching scene is facilitated.

Description

Technical Field

[0001] This invention relates to the field of multi-degree-of-freedom robotic arms, and in particular to a modular intelligent vision industrial robotic arm and its implementation method. Background Technology

[0002] In professional multi-degree-of-freedom robotic arm research and teaching projects, we address the shortcomings in teaching aids, content, experimental platforms, and methods. We provide a robotic arm programming teaching experimental environment, enrich teaching content, and design high-performance, multi-tasking-oriented teaching experimental platforms. Our intelligent force-controlled robotic arm is based on the N+1 degree-of-freedom force-controlled high-precision robotic arm design specifications to meet customer requirements for high-precision, industrial-grade robotic arm teaching products. Compared to ordinary robotic arms, force-controlled robotic arms emphasize precise monitoring of forces or torques at multiple joints, enabling real-time response to force changes and mechanical compensation, thereby achieving compliant control of the robotic arm.

[0003] Currently available robotic arm structures are difficult to manufacture and costly. Summary of the Invention

[0004] In order to overcome the shortcomings of the existing technology, the purpose of this invention is to provide a modular intelligent vision industrial robotic arm and its implementation method, so as to solve the problems of high processing difficulty and high cost of existing robotic arm structures.

[0005] To achieve the above objectives, the present invention provides the following solution:

[0006] A modular intelligent vision industrial robotic arm includes: a robotic arm body, a central control chassis, and a fixed operating table; the robotic arm body includes: first to sixth motors, a robotic arm motherboard, a robotic arm base, a display screen, a robotic arm power switch, robotic arm buttons, a camera module, and a flexible gripper module; the central control chassis includes: a chassis shell, a chassis power board, circuit boards, a voice module, a chassis base, a chassis emergency stop switch, and a chassis power switch; the fixed operating table includes: an operating table base plate, a tray, and feet;

[0007] The robotic arm body is fixed to the fixed operating platform; the robotic arm body is connected to the central control chassis; the first motor, second motor, third motor, fourth motor, fifth motor, and sixth motor are connected in sequence; the robotic arm mainboard is fixed to the operating platform base plate; the first motor is fixed inside the robotic arm base; the display screen is fixed to the side of the robotic arm base; the robotic arm base is fixed to the robotic arm mainboard; the second motor is fixed to the upper side of the robotic arm base; the robotic arm power switch is located on the robotic arm base; the camera module and the flexible gripper module are both located at the end of the sixth motor; the chassis power board, the circuit board, and the voice module are all located inside the chassis shell; the chassis shell is fixed to the lower side of the chassis base; the chassis emergency stop switch and the chassis power switch are both fixed to the chassis base; the feet are fixed to the four corners of the lower side of the operating platform base plate; the tray is located on the operating platform base plate; the robotic arm buttons are located on the robotic arm base.

[0008] The board is used for motion control, image processing, simulation processing, and model inference; the camera module is used to acquire depth and color images; and the voice module is used for voice interaction.

[0009] Preferably, a method for implementing a modular intelligent vision industrial robotic arm includes:

[0010] The target task is decomposed into several subtasks using the MTC task builder; each subtask includes: a generator, a propagator, and a connector;

[0011] During the execution of the subtask, the D2C algorithm is used to perform depth and color sensor difference compensation processing, intrinsic and extrinsic parameter difference unification processing, and depth image and color image resolution alignment processing on the preset camera to obtain depth data.

[0012] During the execution of the subtask, the coordinate pose of the preset robotic arm end effector and the preset camera is processed using a hand-eye calibration algorithm based on the depth data to obtain object position information and robotic arm end pose information.

[0013] Based on the object's position information and the robotic arm's end-effector pose information, the joint angles of the robotic arm are calculated using spatial kinematics and motion transformation equations to obtain control commands, which are then used to control the operation of the preset robotic arm.

[0014] The present invention discloses the following technical effects:

[0015] This invention provides a modular intelligent vision industrial robotic arm and its implementation method, which solves the problems of high processing difficulty and high cost of existing robotic arm structures and realizes an integrated hardware and software architecture. Attached Figure Description

[0016] Figure 1 A modular intelligent vision industrial robotic arm structure diagram provided for embodiments of the present invention;

[0017] Figure 2 A structural diagram of the robotic arm motherboard provided in an embodiment of the present invention;

[0018] Figure 3 This is a structural diagram of a display screen provided in an embodiment of the present invention;

[0019] Figure 4 This is a structural diagram of the robotic arm body base provided in an embodiment of the present invention;

[0020] Figure 5 This is a structural diagram of motor No. 2 / motor No. 4 provided in an embodiment of the present invention;

[0021] Figure 6 This is a structural diagram of motor No. 3 provided in an embodiment of the present invention;

[0022] Figure 7 This is a structural diagram of motor No. 5 provided in an embodiment of the present invention;

[0023] Figure 8 The diagram shows the connection structure of motors 2, 3, 4, and 5 provided in the embodiment of the present invention.

[0024] Figure 9 Structural diagrams provided for embodiments of the present invention;

[0025] Figure 10 This is a chain structure diagram of the robotic arm body provided in an embodiment of the present invention;

[0026] Figure 11 This is a structural diagram of motor No. 6 provided in an embodiment of the present invention;

[0027] Figure 12 A structural diagram of the mechanical claw base provided in an embodiment of the present invention;

[0028] Figure 13 This is a structural diagram of the slider module provided in an embodiment of the present invention;

[0029] Figure 14 A structural diagram of the flexible finger module provided in an embodiment of the present invention;

[0030] Figure 15 This is a structural diagram of the guide rail module provided in an embodiment of the present invention;

[0031] Figure 16This is a structural diagram of a depth camera module provided in an embodiment of the present invention;

[0032] Figure 17 This is a diagram of the mechanical claw base fixing structure provided in an embodiment of the present invention;

[0033] Figure 18 A structural diagram of the front end of the mechanical claw provided in an embodiment of the present invention;

[0034] Figure 19 A diagram of the flexible gripper structure of the robotic arm body provided in an embodiment of the present invention;

[0035] Figure 20 This is a diagram of the USB structure provided in an embodiment of the present invention;

[0036] Figure 21 This is a structural diagram of a power board module provided in an embodiment of the present invention;

[0037] Figure 22 This is a first oblique view of the chassis base module provided in an embodiment of the present invention;

[0038] Figure 23 This is a second oblique view of the chassis base module provided in an embodiment of the present invention;

[0039] Figure 24 This is a third oblique view of the chassis base module provided in an embodiment of the present invention;

[0040] Figure 25 This is a first structural diagram of the chassis cover module provided in an embodiment of the present invention;

[0041] Figure 26 This is a second structural diagram of the chassis cover module provided in an embodiment of the present invention;

[0042] Figure 27 This is a first oblique view of the chassis provided in an embodiment of the present invention;

[0043] Figure 28 This is a second oblique view of the chassis provided in an embodiment of the present invention;

[0044] Figure 29 This is a third oblique view of the chassis provided in an embodiment of the present invention;

[0045] Figure 30 This is a first structural diagram of the operating table provided in an embodiment of the present invention;

[0046] Figure 31 This is a second structural diagram of the operating table provided in an embodiment of the present invention;

[0047] Figure 32 This is a schematic diagram of the operating console provided in an embodiment of the present invention;

[0048] Figure 33This is a schematic diagram of the interface of the visual teaching simulation platform provided in an embodiment of the present invention;

[0049] Figure 34 A schematic diagram of an MTC task builder provided in an embodiment of the present invention;

[0050] Figure 35 This is a schematic diagram of D2C alignment and image correction of an RGBD camera provided in an embodiment of the present invention.

[0051] Explanation of reference numerals in the attached figures:

[0052] 1-First motor, 2-Second motor, 3-Third motor, 4-Fourth motor, 5-Fifth motor, 6-Sixth motor, 7-Robot arm motherboard, 8-Robot arm base, 9-Display screen, 10-Robot arm power switch, 11-Robot arm button, 12-Camera module, 13-Flexible gripper module, 14-Chassis shell, 15-Chassis power board, 16-Board, 17-Voice module, 18-Chassis base, 19-Chassis emergency stop switch, 20-Chassis power switch, 21-Operating table base plate, 22-Tray, 23-Foot pad. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] The purpose of this invention is to provide a modular intelligent vision industrial robotic arm and its implementation method, which solves the problems of high processing difficulty and high cost of existing robotic arm structures.

[0055] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0056] Figure 1 A modular intelligent vision industrial robotic arm structure diagram provided for embodiments of the present invention, such as... Figure 1As shown, the present invention provides a modular intelligent vision industrial robotic arm, comprising: a robotic arm body, a central control chassis, and a fixed operating table; the robotic arm body includes: first to sixth motors 6, a robotic arm mainboard 7, a robotic arm base 8, a display screen 9, a robotic arm power switch 10, robotic arm buttons 11, a camera module 12, and a flexible gripper module 13; the central control chassis includes: a chassis shell 14, a chassis power board 15, a circuit board 16, a voice module 17, a chassis base 18, a chassis emergency stop switch 19, and a chassis power switch 20; the fixed operating table includes: an operating table base plate 21, a tray 22, and feet 23;

[0057] The robotic arm body is fixed to the fixed operating platform; the robotic arm body is connected to the central control box; the first motor 1, the second motor 2, the third motor 3, the fourth motor 4, the fifth motor 5, and the sixth motor 6 are connected in sequence; the robotic arm main board 7 is fixed to the operating platform base plate 21; the first motor 1 is fixed inside the robotic arm base 8; the display screen 9 is fixed to the side of the robotic arm base 8; the robotic arm base 8 is fixed to the robotic arm main board 7; the second motor 2 is fixed to the upper side of the robotic arm base 8; the robotic arm power switch 10 is located on the robotic arm base. The camera module 12 and the flexible gripper module 13 are both located at the end of the sixth motor 6; the power board 15, the circuit board 16, and the voice module 17 are all located inside the outer casing 14; the outer casing 14 is fixed to the lower side of the chassis base 18; the emergency stop switch 19 and the power switch 20 are both fixed to the chassis base 18; the feet 23 are fixed to the four corners of the lower side of the operating table base plate 21; the tray 22 is located on the operating table base plate 21; the robotic arm button 11 is located on the robotic arm base.

[0058] The board 16 is used for motion control, image processing, simulation processing, and model inference; the camera module 12 is used to acquire depth images and color images; and the voice module 17 is used for voice interaction.

[0059] Furthermore, a method for implementing a modular intelligent vision industrial robotic arm includes:

[0060] The target task is decomposed into several subtasks using the MTC task builder; each subtask includes: a generator, a propagator, and a connector;

[0061] During the execution of the subtask, the D2C algorithm is used to perform depth and color sensor difference compensation processing, intrinsic and extrinsic parameter difference unification processing, and depth image and color image resolution alignment processing on the preset camera to obtain depth data.

[0062] During the execution of the subtask, the coordinate pose of the preset robotic arm end effector and the preset camera is processed using a hand-eye calibration algorithm based on the depth data to obtain object position information and robotic arm end pose information.

[0063] Based on the object's position information and the robotic arm's end-effector pose information, the joint angles of the robotic arm are calculated using spatial kinematics and motion transformation equations to obtain control commands, which are then used to control the operation of the preset robotic arm.

[0064] refer to Figure 1 A modular intelligent vision industrial robotic arm includes a robotic arm body, a chassis, and an operating table. The robotic arm body is composed of a first motor 1, a second motor 2, a third motor 3, a fourth motor 4, a fifth motor 5, and a sixth motor 6 connected in sequence. Its end is equipped with a flexible gripper module 13 and a depth camera. The base is equipped with a display screen 9 and a motherboard for communication interaction. The chassis contains a power board, a board card 16, a voice module 17, and a switch. The operating table includes an operating table base plate 21, a tray 22, and foot pads.

[0065] Specifically, the robotic arm itself. (Reference) Figure 2 The motherboard is fixed to the motherboard base with M2.5x12 double studs, M2.5x6 countersunk Phillips head screws, and M2.5x6 hex socket screws, forming a whole, namely the motherboard module.

[0066] refer to Figure 3 The display screen 9 is fixed to the outer shell of the display screen 9 with countersunk Phillips head self-tapping M2x6 screws to form a whole, namely the display screen 9 module.

[0067] refer to Figure 4 The first motor 1 is fixed to the base with countersunk hexagon M3x8 screws, the main board module is fixed to the base with countersunk Phillips M2.5x6 screws, the display screen 9 module is fixed to the base with round head Phillips M2x6 screws, and the robotic arm power switch 10 and buttons are fixed to the base with their own nuts. The base has a hollow structure, which can protect the internal main board, motor and other parts, and also provide solid stability and overall rigidity for the robotic arm body. The first motor 1 is fixed to the base, which can minimize vibration and shaking and ensure the motion accuracy of the end of the entire robotic arm chain structure.

[0068] refer to Figure 5 The robotic arm body has a chain structure, with each motor connected together through the arm support and the motor support to form a multi-degree-of-freedom joint structure. The second motor 2 and the fourth motor 4 are clamped by the motor support side plate a and the motor support side plate b, and fixed by countersunk hexagonal M3x8 screws. Then, bearings are installed to form a whole, namely the second motor 2 module or the fourth motor 4 module.

[0069] refer to Figure 6 The third motor 3 is clamped by arm brackets c and d and fixed with countersunk hexagonal M3x8 screws. A double through stud M4x55 is used as support between arm brackets c and d and fixed with hexagonal M4x10 screws. Then, a bearing is put on arm bracket c and clamped by arm brackets a and b and fixed with countersunk hexagonal M3x8 screws. A double through stud M4x60 is used as support between arm brackets a and b and fixed with hexagonal M4x10 screws, forming a whole, namely the third motor 3 module.

[0070] refer to Figure 7 The fifth motor 5 is equipped with a motor connection lock - male, which is fixed by an M3x8 hex screw. The motor bracket b is also fixed to the fifth motor 5 with an M3x8 hex screw, forming a whole, namely the fifth motor 5 module.

[0071] refer to Figure 8 The second motor module 2 and the fourth motor module 4 are mounted on the third motor module 3 as shown in the figure and are fixed by M3x10 hex screws. The fifth motor module 5 is fixed to the fourth motor module 4 by countersunk M4x10 hex screws.

[0072] refer to Figure 9 The arm harness housing is fixed to the arm bracket by an internal hexagonal self-tapping M2.6x8 socket, which can hide the harness inside, providing both aesthetic appeal and protection for the harness.

[0073] refer to Figure 10 First, fix the motor bracket a to the base of the robotic arm body with M3x8 hex screws. Then, fix the chain structure to the motor bracket a with M4x10 countersunk hex screws. In this way, the entire chain structure can achieve horizontal rotation.

[0074] refer to Figure 11 Use countersunk hexagon M3x8 screws to fix the motor connection lock-nut to the sixth motor 6. Similarly, use countersunk hexagon M3x8 screws to fix the drive gear base to the sixth motor 6. Finally, put the gear on the drive gear base and fix it with the set screw to form a whole, namely the sixth motor 6 module.

[0075] refer to Figure 12 Use M3x8 hex screws to fix the bearing housing to the base plate of the mechanical claw, and then fix the set screw positioning pin to the base plate to form a whole, namely the mechanical claw base module.

[0076] refer to Figure 13Use round-head Phillips M2x8 screws to fix the finger connecting block to the slider, then use countersunk Phillips M2.5x14 screws to fix the rack connecting block to the finger connecting block, and finally fix the rack to the rack connecting block with hexagon M2.5x12 screws to form a whole, namely the slider module.

[0077] refer to Figure 14 The flexible finger is fixed to the finger base using round-headed M3x25 hex screws and M3 anti-slip nuts to form a flexible finger module.

[0078] refer to Figure 15 Slide the slider modules into the linear guide rail from both sides, and then fix the flexible finger modules to the slider modules on both sides with M2.5x10 hex screws to form a new whole, namely the guide rail module.

[0079] refer to Figure 16 Insert the depth camera into the dust cover, and then use round-headed Phillips head self-tapping M2x6 screws to fix the depth camera back cover onto the dust cover to press the depth camera firmly. Then use round-headed Phillips head self-tapping M2x6 screws to fix the depth camera lens onto the dust cover to protect the depth camera lens. This forms a whole, namely the depth camera module 12.

[0080] refer to Figure 17 and Figure 18 The sixth motor module 6 is secured to the mechanical gripper base module using countersunk M3x8 hex screws. The guide rail module is then secured to the mechanical gripper base module using round-head M2x8 Phillips head screws. Finally, the depth camera module 12 and dust cover are secured to the mechanical gripper base module using M2.5x8 self-tapping hex screws, thus forming a complete mechanical gripper module. Driven by the sixth motor 6, and through the engagement of gears and racks, the fingers slide on the guide rails, thereby gripping objects. Because the fingers are flexible, they can tightly grip the objects to prevent slippage.

[0081] refer to Figure 19 The mechanical gripper module is fixed to the chain structure with M3x8 hex screws, thus forming the main body of the robotic arm.

[0082] Specifically, the chassis features an aluminum alloy frame, offering advantages in both lightweight design and stability. Anti-slip feet are mounted on the chassis base 18 to ensure stability and prevent slippage. Internally, it houses a circuit board 16, a voice module 17, a USB module, and a power supply module. The power switch is conveniently located at the top of the chassis base 18. (Reference) Figure 20 The USB female extension cable is clamped by two USB mounting brackets and then secured with round-head Phillips self-tapping M2x8 screws.

[0083] refer to Figure 21The double-through nylon pillar M2.5x12 is fixed to the power board 15 of the chassis with M2.5x6 hex screws to form a whole, namely the power board module.

[0084] refer to Figures 22 to 24 The chassis shell 14 and chassis base plate are fixed together by connecting and fixing with square nuts and round head M3x6 hex screws; then the chassis interface panel is fixed to the frame with M2.5x6 hex screws; finally, the single-headed stud M3x6+6 is fixed to the frame with M3 anti-slip nuts, all four corners; thus forming a whole, namely the chassis base 18 module.

[0085] refer to Figure 25 and Figure 26 The top cover and top plate of the chassis are fixed together with round-headed M3x8 hex screws and M3 anti-slip nuts, with a dustproof mesh sandwiched in between to prevent dust. Then, the anti-slip feet of the chassis are put on the feet of the top cover to prevent the chassis from slipping. The speaker and microphone are then fixed to the top cover of the chassis with screws and nuts to enable voice interaction. Finally, the emergency stop switch and power switch are installed in their respective positions, thus forming a whole unit, namely the chassis top cover module.

[0086] refer to Figures 27 to 29 Embed the board 16 into the board 16 mounting slot, and then fix it to the chassis base module 18 with M2.6x8 self-tapping hex screws; again, fix the USB module to the chassis base module 18 with M2.6x8 self-tapping hex screws, and then fix the power board module to the chassis base module 18 with M2.5x6 hex screws; then fix the chassis top cover module and chassis base module 18 together with M3x8 round-head hex screws, and finally fix the four feet of the chassis top cover module with M3x8 round-head hex screws to make it more secure.

[0087] Specifically, see the chassis diagram for reference. Figure 30 The work surface is made of honeycomb aluminum panel, which has the advantages of being lightweight and flexible in installation; the feet are fixed to the work surface with round head Phillips M4x16 screws, which can protect the entire work surface from shock.

[0088] refer to Figure 31 The positioning pin is fixed to the operating table, and the tray 22 is embedded in the positioning pin. Identification tools can be placed on the tray 22.

[0089] refer to Figure 32 The robotic arm body is fixed to the operating table with M6x12 hex screws, ensuring safety and sturdiness.

[0090] Preferably, the visual simulation interface, based on MTC-designed robotic arm control software, contains a task structure (Task) that comprises containers of multiple Stages, describing the logical sequence of the entire task. Each Stage is a step in the task and can include input states, output states, constraints, and planning logic. Stages can have individually defined constraints, such as joint restrictions, collision detection, and object dynamics constraints. Finally, the solver generates the path and state. Its main contents include the following:

[0091] Motion Planning Solver (OMPL);

[0092] Collision detector (FCL);

[0093] Inverse Kinematics Solver (KDL);

[0094] Throughout the task planning process, MTC allows the use of different solvers at different stages to meet the needs of complex tasks. Each Stage is an independent module, easily reusable and modifiable, and custom Stage types can be added as needed. MTC can easily handle complex constraints, such as multi-object collaboration, dynamic constraints, and obstacle avoidance. Through the ROS Rviz plugin, users can view the task planning process in real time, including the inputs and outputs of each stage, such as... Figure 33 As shown.

[0095] Furthermore, a model-predicted target grasping method is employed. This embodiment uses model prediction to achieve flexible robotic arm grasping tasks through whole-machine modeling and predictive task planning. The core architecture is based on the MTC (MoveIt TaskConstructor) task constructor, referencing... Figure 34Complex tasks are broken down into manageable subtasks, each consisting of multiple stages. These stages are categorized into three types: Generators, Propagators, and Connectors, arranged in any order and hierarchy, with explicit constraints on the direction of result propagation. **Generator Stage:** Calculates results independently of adjacent stages and can propagate results in both directions, forward and backward. It is typically used to create possible solutions, such as initial points for pose sampling and motion planning. For example, an inverse kinematics (IK) sampler is a generator stage that generates possible poses for the end effector, which can then be used as input for subsequent stages. **Propagator Stage:** Receives a result from an adjacent stage, solves a subproblem, and then propagates the result to the adjacent stage. It calculates paths based on the initial or target state. For example, it calculates a Cartesian path from the current robot state to the target state, or calculates approach and placement poses based on the grasping posture. **Connector Stage:** Does not propagate any results but attempts to bridge the gap between two adjacent states. Purpose: The connector phase is used to solve the transition problem from one given state to another, which often involves motion planning. For example, calculating a smooth motion path from a grasping posture to a placing posture, or moving from an initial position to a target position while avoiding collisions. Figure 34 The meanings of the Chinese and English parts are as follows: Generator stage: Generates and propagates interface states to adjacent stages, examples: pose sampler (+IK solver), fixed landmark state, output / verification of the current state; Propagator stage: Receives input interface states, solves a problem, and propagates it to the next interface, examples: (relative) Cartesian motion, proximity motion planning, scene operations (attach / detach objects, ACM), filter / verifier state; Connector stage: Connects the interface states of two adjacent stages, examples: free motion planning between the starting state and the target state.

[0096] Preferably, 3D vision inspection based on an RGBD camera, with reference to Figure 35 This embodiment designs a Depth-to-Color (D2C) algorithm based on an RGBD camera and an Eye-in-hand calibration algorithm for the robotic arm, used for aligning depth and color images and calibrating the spatial relationship between the robotic arm and the camera, respectively. D2C alignment maps the depth image to the coordinate system of the color image, thus achieving pixel alignment between the two. This facilitates subsequent fusion calculations based on depth and color information (point cloud generation, precise target detection). The D2C alignment workflow consists of the following three steps:

[0097] 1) Compensation for differences between depth and color sensors:

[0098] Depth and color images from a depth camera come from different sensors, resulting in differences in their field of view (FOV), resolution, and position. The depth map is distance information obtained from the depth sensor, while the color image is captured by an RGB sensor, and the difference is compensated based on this characteristic.

[0099] 2) Unify the differences between internal and external references:

[0100] Camera intrinsic parameters are parameters such as the sensor's focal length and principal point, used to describe the projection of the image onto the physical world. Camera extrinsic parameters are parameters relating the relative position and rotation of the depth sensor and the RGB sensor. Depth cameras and RGB cameras resolve these differences using publicly available calibration algorithms and OpenCV correction methods, aligning image distortion at the pixel level and restoring physical arrangement properties.

[0101] 3) Alignment of depth image and color image resolution:

[0102] Based on the calibration extrinsic parameters of the depth and color sensors, points in the depth map are projected onto the color image coordinate system. The depth values ​​are converted into a point cloud using the intrinsic parameters of the depth sensor. The point cloud is then mapped to the RGB camera coordinate system using the extrinsic parameters, and finally mapped back to the pixel coordinates of the color image using the RGB intrinsic parameters.

[0103] Robotic arm hand-eye calibration:

[0104] Hand-eye calibration aims to determine the pose relationship between the camera and the robotic arm's end-effector and solve for the transformation matrix. This involves transforming the camera relative to the robotic arm's end-effector, the end-effector relative to the base (provided by the robotic arm), and the camera coordinate system relative to the robotic arm base. A checkerboard calibration method is used to perform the calibration task. The end-effector pose of each acquisition point is obtained from the robotic arm controller, and the Tsai-Lenz or Dual Quaternion method is used to solve for the matrix. Finally, the calibration results are applied to new test locations to verify the correspondence between the measurement points in the camera and robotic arm coordinate systems. This technical solution enables the robotic arm to accurately and efficiently perform decision-making and control tasks in complex scenarios. Based on the MTC task construction system, spatial kinematics and motion transformation equations are used to achieve full-process monitoring of the robotic arm's end-effector pose localization, motion planning, trajectory control, target object grasping and delivery. Visual simulation and control are achieved using Rviz2 under the ROS2 system, facilitating efficient and advanced teaching tasks in CDIO teaching scenarios.

[0105] The beneficial effects of this invention are as follows:

[0106] This invention achieves an integrated hardware and software architecture through virtual model simulation and real-world linkage with a physical robotic arm, improving human-computer interaction performance and facilitating the support of teaching tasks in educational settings.

[0107] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0108] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A modular, intelligent, vision industrial robotic arm, characterized in that, Include: Mechanical arm body, central control machine box, fixed operation platform, the mechanical arm body includes: first to sixth motor, mechanical arm mainboard, mechanical arm base, display screen, mechanical arm power switch, mechanical arm button, camera module, flexible clamp jaw module, the central control machine box includes: machine box shell, machine box power board, board card, voice module, machine box base, machine box emergency stop switch, machine box power switch, the fixed operation platform includes: operation platform bottom plate, tray, foot pad, The mechanical arm body is fixed on the fixed operation platform, the mechanical arm body is connected with the central control machine box, the first motor, the second motor, the third motor, the fourth motor, the fifth motor, the sixth motor are connected in turn, the mechanical arm mainboard is fixed on the operation platform bottom plate, the first motor is fixed in the mechanical arm base, the display screen is fixed on the side of the mechanical arm base, the mechanical arm base is fixed on the mechanical arm mainboard, the second motor is fixed on the upper side of the mechanical arm base, the mechanical arm power switch is arranged on the mechanical arm base, the camera module and the flexible clamp jaw module are arranged at the end of the sixth motor, the machine box power board, the board card and the voice module are arranged in the machine box shell, the machine box shell is fixed on the lower side of the machine box base, the machine box emergency stop switch and the machine box power switch are fixed on the machine box base, the foot pad is fixed at the four corners of the lower side of the operation platform bottom plate, the tray is arranged on the operation platform bottom plate, the mechanical arm button is arranged on the mechanical arm base, The board card is used for motion control, image processing, simulation processing and model reasoning, the camera module is used for collecting depth image and color image, and the voice module is used for voice interaction.

2. The modular, smart vision industrial robotic arm of claim 1, wherein, The mechanical arm mainboard includes: control mainboard, mainboard base, the display screen includes: screen main body, screen shell, The control mainboard is fixed on the mainboard base through double-pass stud M2.5x12, countersunk cross M2.5x6 screw, internal hexagonal M2.5x6 screw, the screen main body is fixed on the screen shell through countersunk cross self-tapping M2x6 screw.

3. The modular, smart vision industrial robotic arm of claim 1, wherein, The mechanical arm body further includes: motor support side plate a, motor support side plate b, bearing, arm support a, arm support b, arm support c, arm support d, motor support b, motor connection lock buckle-male, motor connection lock buckle-female, driving tooth base, gear, motor support a; The mechanical arm base adopts a hollow structure; the first motor is fixed on the mechanical arm base through a countersunk internal hexagonal M3x8 screw; the mechanical arm mainboard is fixed on the mechanical arm base through a countersunk cross M2.5x6 screw; the display screen is fixed on the mechanical arm base through a round head cross M2x6 screw; a group of motor support side plates a and b are arranged on the two sides of the second motor and the fourth motor; the second motor is fixed in the middle of the motor support side plate a and the motor support side plate b through a countersunk internal hexagonal M3x8 screw; the fourth motor is fixed in the middle of the motor support side plate a and the motor support side plate b through a countersunk internal hexagonal M3x8 screw; the two sides of the second motor and the fourth motor are provided with the bearing; the two sides of the third motor are respectively provided with the arm support a, the arm support b, the arm support c and the arm support d through a countersunk internal hexagonal M3x8 screw; the arm support a and the arm support c are located on the same side; the arm support b and the arm support d are located on the same side; the arm support a is arranged on the outer side of the arm support c; the arm support b is arranged on the outer side of the arm support d; the arm support a and the arm support b are fixedly connected in the middle through a double-pass stud M4x60 and an internal hexagonal M4x10 screw; the arm support c and the arm support d are fixedly connected in the middle through a double-pass stud M4x55 and an internal hexagonal M4x10 screw; the motor support b is fixed on the fifth motor through an internal hexagonal M3x8 screw; the motor connection lock buckle-male is fixed on the fifth motor through an internal hexagonal M3x8 screw; the motor connection lock buckle-female is fixed on the sixth motor through a countersunk internal hexagonal M3x8 screw; the driving tooth base is fixed on the sixth motor through a countersunk internal hexagonal M3x8 screw; the gear sleeve is arranged on the driving tooth base; the first motor is fixed on the motor support a through a countersunk internal hexagonal M4x10 screw; the motor support a is fixed on the mechanical arm base through an internal hexagonal M3x8 screw.

4. The modular, smart vision industrial robotic arm of claim 1, wherein, The flexible gripper module comprises a linear guide rail and two groups of finger units arranged on the linear guide rail; the finger unit comprises a fixed rack, a rack connecting block, a sliding block, a finger connecting block, a finger base and a flexible finger; The finger connecting block is fixed on the sliding block through a round head cross M2x8 screw; the rack connecting block is fixed on the finger connecting block through a countersunk cross M2.5x14 screw; the fixed rack is fixed on the rack connecting block through an internal hexagonal M2.5x12 screw; the finger base is fixed on the sliding block through an internal hexagonal M2.5x10 screw; the flexible finger is fixed on the finger connecting block through a round head internal hexagonal M3x25 screw and a M3 anti-slip nut; the sliding block is arranged on the linear guide rail.

5. The modular, smart vision industrial robotic arm of claim 1, wherein, The camera module comprises a camera rear cover, a depth camera, a dust cover and a camera lens; The camera lens is fixed on the dust cover through a round head cross self-tapping M2x6 screw; the camera rear cover, the depth camera and the dust cover are fixedly connected through a round head cross self-tapping M2x6 screw.

6. A method of implementing a modular, intelligent, vision industrial robotic arm, comprising: The method is applied to the modular intelligent visual industrial robot of claim 1, and comprises: a target task is decomposed into a plurality of subtasks by using an MTC task constructor; each subtask comprises a generator, a propagator and a connector; during execution of the subtasks, a D2C algorithm is used to perform depth and color sensor difference compensation processing, internal parameter and external parameter difference unification processing, and depth image and color image resolution alignment processing on a preset camera to obtain depth data; during execution of the subtasks, a hand-eye calibration algorithm is used to perform coordinate pose change processing on a preset robot end effector and the preset camera according to the depth data to obtain object position information and robot end effector pose information; according to the object position information and the robot end effector pose information, a spatial kinematics and motion transformation equation group are used to calculate robot joint angles to obtain control instructions, and the preset robot is controlled to operate by using the control instructions.

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