WO2021208230A1 - 智能装配控制*** - Google Patents

智能装配控制*** Download PDF

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Publication number
WO2021208230A1
WO2021208230A1 PCT/CN2020/097229 CN2020097229W WO2021208230A1 WO 2021208230 A1 WO2021208230 A1 WO 2021208230A1 CN 2020097229 W CN2020097229 W CN 2020097229W WO 2021208230 A1 WO2021208230 A1 WO 2021208230A1
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WO
WIPO (PCT)
Prior art keywords
deep learning
sliding table
workpiece
vibration isolation
learning camera
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PCT/CN2020/097229
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English (en)
French (fr)
Inventor
杨皓
张伯强
方宇
陶翰中
周志峰
吴明晖
Original Assignee
上海工程技术大学
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Application filed by 上海工程技术大学 filed Critical 上海工程技术大学
Publication of WO2021208230A1 publication Critical patent/WO2021208230A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23P—METAL-WORKING NOT OTHERWISE PROVIDED FOR; COMBINED OPERATIONS; UNIVERSAL MACHINE TOOLS
    • B23P21/00—Machines for assembling a multiplicity of different parts to compose units, with or without preceding or subsequent working of such parts, e.g. with programme control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/0081—Programme-controlled manipulators with master teach-in means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1602—Programme controls characterised by the control system, structure, architecture
    • B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1628—Programme controls characterised by the control loop
    • B25J9/1633—Programme controls characterised by the control loop compliant, force, torque control, e.g. combined with position control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1674—Programme controls characterised by safety, monitoring, diagnostic
    • B25J9/1676—Avoiding collision or forbidden zones
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1679—Programme controls characterised by the tasks executed
    • B25J9/1687—Assembly, peg and hole, palletising, straight line, weaving pattern movement

Definitions

  • the invention relates to the technical field of intelligent manufacturing, in particular to an intelligent assembly control system.
  • robot environment perception and modeling methods based on information fusion such as vision and force have the problems of low efficiency, difficulty in cross-scale, and weak anti-interference ability; at the level of robot assembly motion planning, How to realize the autonomous planning and assembly of "machine-environment" with force position servo sensing to adapt to the narrow and brittle environment in the assembly of precision devices is an urgent problem to be solved. Therefore, the study of key technologies such as precision sensing and compliance control of high-reflective device assembly robots is of great significance to solving technical problems in industry applications.
  • the purpose of the present invention is to provide an intelligent assembly control system to solve the problem that the existing robot environment perception and modeling method cannot operate the operating objects in the same operating space and different field of view ranges.
  • the intelligent assembly control system includes a mobile robot, a precision dual-frequency damped vibration isolation optical platform, a five-degree-of-freedom electric sliding table, a line laser scanner, and a first depth Learning camera, second deep learning camera, ball screw, first robotic arm, second robotic arm and host computer, among them:
  • the second robot arm is installed on the mobile robot, and the second deep learning camera is installed at the end of the second robot arm; the mobile robot performs omni-directional scanning in the working area to construct map information, and set Determine the target area, working area, target position and working position of the workpiece to be tested;
  • the second robot arm is moved to the target position by teaching, and the second deep learning camera takes pictures of the workpiece to be measured, and extracts the features of the workpiece to be measured Point information to identify the workpiece to be tested, and transmit the identification data to the host computer for processing to obtain the relative position relationship between the second deep learning camera and the workpiece to be tested;
  • the positional relationship between the second robot arm and the workpiece to be measured is calculated through the robot motion processing matrix, and the converted coordinates of the workpiece to be measured are sent to the second robot arm, and the second robot arm performs Posture adjustment and grasping the workpiece to be measured;
  • the mobile robot moves to the working area, and the first deep learning camera above the five-degree-of-freedom electric sliding table takes pictures of the precision dual-frequency damping vibration isolation optical platform, and sends the platform information to the
  • the second mechanical arm places and fixes the workpiece to be tested on a precision dual-frequency damping and vibration isolation optical platform according to the platform information;
  • the first robotic arm and the first deep learning camera perform hand-eye calibration, and the second deep learning camera takes pictures of the fixed workpiece to be tested, and converts the fixed data into the position information of the assembly point. Perform hand-eye calibration, and send the position information to the first robotic arm, and the vacuum chuck at the end of the first robotic arm installs the parts under the visual guidance of the first deep learning camera;
  • the five-degree-of-freedom electric sliding table transports the installed workpiece under the line laser scanner to perform omnidirectional and multi-angle detection, and generate point cloud data of each part of the workpiece to be tested.
  • the line laser scanner The point cloud data is transmitted to the host computer for processing, and the processed point cloud data model is compared with the CAD model of the workpiece to analyze specific dimensional errors and defects of the workpiece to be tested, and judge whether the workpiece to be tested is qualified or not;
  • the upper computer sends a detection completion signal to the mobile robot, and the mobile robot moves to a new target area, grabs the workpiece, and places it in a designated position.
  • the five-degree-of-freedom electric sliding table is installed in the central area of the precision dual-frequency damping and vibration isolation optical platform, and is integral to the precision dual-frequency damping and vibration isolation optical platform. Placed in a vertical state, and connected with the precision dual-frequency damping vibration isolation optical platform through a thread;
  • the line laser scanner is located above the central axis of the five-degree-of-freedom electric sliding table, and is parallel to the precision dual-frequency damping vibration isolation optical platform, and there is a fixed frame above the line laser scanner;
  • the ball screw is installed on a profile placed perpendicular to the precision dual-frequency damped vibration isolation optical platform, and is located on the right side of the line laser scanner;
  • the host computer is located on the precision dual-frequency damped vibration isolation optical platform, and is connected to the motion control card, the cable of the line laser scanner, the first mechanical arm, and the first deep learning camera;
  • the first mechanical arm is installed on the precision dual-frequency damping vibration isolation optical platform, and is located directly behind the guide rail of the five-degree-of-freedom electric sliding table;
  • the first deep learning camera is located directly above the five-degree-of-freedom electric sliding table, parallel to the precision dual-frequency damping vibration isolation optical platform, and the first deep learning camera is fixed on the camera frame.
  • the mobile robot includes an AGV vehicle and a motion control cabinet, wherein:
  • the quota load of the AGV vehicle is 60-80 kilograms, the AGV vehicle has map construction and autonomous navigation functions, the AGV vehicle has a safety laser sensor, and is positioned by a safety laser sensor based on environment mapping, and autonomously selects a route;
  • the motion control cabinet is located above the AGV vehicle, and the second mechanical arm is located above the motion control cabinet;
  • the motion control cabinet is connected to the host computer through a wireless network, and the motion control cabinet receives the mobile robot status information and movement instructions sent by the host computer; the motion control cabinet is connected to the safety laser sensor for real-time Obtain the positioning data of the safety laser sensor.
  • each joint of the first mechanical arm and the second mechanical arm has a force sensor, and the force sensor has a collision detection function;
  • the first mechanical arm and The second mechanical arm can realize dragging and teaching operation;
  • the mechanical arm and the host computer are connected through the TCP/IP protocol, and the script command string sent by the host computer is received, and the received script command is executed to complete the specified action ;
  • Both the first deep learning camera and the second deep learning camera have an intelligent random sorting module, which integrates 3D structured light, image analysis, and robot arm motion control. It can quickly identify different objects in three dimensions through 3D structured light. The position and posture of the spatial placement can accurately guide the first robotic arm and the second robotic arm to pick and place.
  • the precision dual-frequency damping vibration isolation optical platform includes a table, a bracket, a dual-frequency damping vibration isolation mechanism, a height adjustment mechanism, and brake silent casters;
  • the table top is located above the support, and is used to carry the first mechanical arm, the five-degree-of-freedom electric sliding table, the line laser scanner, and the first deep learning camera;
  • the bracket is a supporting structure, and the four brackets are connected by two trusses in pairs;
  • the dual-frequency damping vibration isolation mechanism is located between the table and the support for vibration isolation;
  • a height adjustment mechanism and brake silent casters are provided under the bracket.
  • the five-degree-of-freedom electric sliding table includes an X-axis electric linear sliding table, an X-axis electric swing sliding table, a Y-axis electric linear sliding table, and a Y-axis electric swing sliding table.
  • electric rotary sliding table includes an X-axis electric linear sliding table, an X-axis electric swing sliding table, a Y-axis electric linear sliding table, and a Y-axis electric swing sliding table.
  • the X-axis electric linear sliding table and the Y-axis electric linear sliding table are both composed of a dust cover, a sliding table ball screw, a linear slider guide rail, a coupling, a U-shaped base plate, and a servo motor; the sliding table ball wire
  • the bar is installed in the middle of the U-shaped bottom plate;
  • the dust cover is installed above the U-shaped bottom plate, which is made of stainless steel;
  • the linear slider guide rail moves on the ball screw of the sliding table under the control of the servo motor;
  • the X-axis electric swing slide table and the Y-axis electric swing slide table are both composed of a first base, a first worm gear, an arc-shaped V-shaped guide rail, and a stepping motor; the arc-shaped V-shaped guide rail is located above the first base, Swinging around the first worm gear driven by the stepping motor;
  • the electric rotary sliding table is composed of a second base, a second worm gear, a backlash adjustment structure, and a cross ball collar; the cross ball collar can be used horizontally, vertically, and upside down; the backlash adjustment structure is used to reduce backlash .
  • the line laser scanner is composed of a blue laser sensor, a cylindrical objective lens, a CMOS sensor, and a connector; the blue laser sensor emits a blue laser and passes through the column The surface objective lens is processed to realize the uniform distribution of light; the CMOS sensor is located inside the line laser scanner; the connector is located at the tail of the line laser scanner, which is used to connect the line laser scanner and the cable.
  • the ball screw is composed of a spiral dial, a lead screw, a nut, a slider, and a slide rail; the spiral dial has a calibrated size range, which can visually display the rotating distance; the lead screw adopts an external circulation transmission, The lead screw is the active body, and the nut converts the rotary motion into linear motion with the rotation angle of the lead screw.
  • the slider moves repeatedly on the slide rail to realize the vertical movement of the line laser scanner; ball screw and line laser scanner It is fixed by the fixing frame.
  • the host computer is a computer, which is used to display the real-time status of the mobile robot, including the position information display of the mobile robot during the navigation process and the remote setting of the target;
  • the host computer is also used to control the trajectory planning of the five-degree-of-freedom electric sliding table
  • the host computer is also used to receive and process the three-dimensional point cloud data transmitted by the line laser scanner to obtain the test results of qualified or unqualified parts, and transmit the test results to the first robotic arm;
  • the host computer is also used to receive feedback information from the infrared sensor, and feed back the operating status and location of the five-degree-of-freedom electric sliding table;
  • the host computer is also used to process photos taken by the first deep learning camera, extract point information, and send the processed information to the first robotic arm.
  • the hand-eye calibration method is to perform hand-eye calibration on the first robotic arm and the first deep learning camera through the Tsai-Lenz algorithm, so that the first The end effector of the robotic arm fixes the calibration board and keeps the calibration board in the picture of the first deep learning camera.
  • the first deep learning camera shoots the calibration board to collect a series of pictures, and at the same time records the first robotic arm’s
  • the pose information is one-to-one correspondence, and the spatial relationship between the first deep learning camera and the first robot arm is solved through the correspondence between the visual information and the first robot arm's pose.
  • the odometer information is provided by the control system of the mobile robot.
  • the control system of the second manipulator receives it, the odometer data is transformed into the first Second, the displacement amount of the base coordinate system of the robot arm, and then according to the determined end pose provided by the workpiece to be tested and the displacement amount of the second robot arm base, the equivalent planning target after the corresponding update of the second robot arm is obtained, and the equivalent planning target is obtained.
  • the angle control target refined to each joint is obtained, and finally the joint angle is controlled according to the PID algorithm.
  • a system for automatically installing the backplane cable plug-in of a mobile phone is proposed. It can realize the full automation of the parts from the factory to the assembly and inspection process, so as to achieve the purpose of saving labor costs, improving production efficiency and verifying multiple technical means in a true sense.
  • the integrated system of full-automatic detection and intelligent assembly proposed by the present invention can realize full-automatic in the true sense. After the initial teaching operation, manual intervention is no longer required in the entire work flow, and at the same time, when someone enters the work area Later, the sensors equipped on the robotic arms and mobile robots will react to the approaching human body and stop moving, so that safety can also be guaranteed.
  • An integrated system of fully automatic inspection and intelligent assembly integrates the automatic assembly and inspection of workpieces, which improves production efficiency while ensuring production quality.
  • Each joint of the seven-degree-of-freedom manipulator is equipped with a force sensor, which can realize precise force control. At the same time, it can realize safe human-computer interaction, can accurately detect collisions, and ensure safety; it can realize dragging and teaching operation and assist programming software to improve programming efficiency.
  • Figure 1 is a schematic diagram of the overall structure of a fully automatic detection and intelligent assembly control system provided by a specific embodiment of the present invention
  • FIG. 2 is a schematic structural diagram of a precision dual-frequency damping vibration isolation optical platform provided by a specific embodiment of the present invention
  • Figure 3 is a schematic structural diagram of a five-degree-of-freedom electric sliding table provided by a specific embodiment of the present invention.
  • FIG. 4 is a schematic structural diagram of a line laser scanner provided by a specific embodiment of the present invention.
  • FIG. 5 is a schematic diagram of the structure of a ball screw and a profile provided by a specific embodiment of the present invention.
  • FIG. 6 is a schematic diagram of the structure of a first mechanical arm and a second mechanical arm (seven degrees of freedom mechanical arm) provided by a specific embodiment of the present invention
  • Fig. 7 is a schematic diagram of a mobile robot provided by a specific embodiment of the present invention.
  • FIG. 8 is a block diagram of the overall system structure provided by a specific embodiment of the present invention.
  • Figure 9 is a schematic diagram of a mobile robot control system provided by a specific embodiment of the present invention.
  • FIG. 10 is a technical road map of parts identification and positioning provided by a specific embodiment of the present invention.
  • FIG. 11 is a motion planning route map of a mobile robot provided by a specific embodiment of the present invention.
  • orientation or positional relationship indicated by the terms “upper” and “lower” are based on the orientation or positional relationship shown in the drawings, or are habitually placed when the product of the present invention is used.
  • the orientation or position relationship, or the orientation or position relationship commonly understood by those skilled in the art is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation or a specific orientation.
  • the azimuth structure and operation cannot be understood as a limitation of the present invention.
  • the “first”, “second”, etc. in the present invention are only used for distinguishing in description, and have no special meaning.
  • the core idea of the present invention is to provide an intelligent assembly control system to solve the problem that the existing robot environment perception and modeling method cannot operate the operating objects in the same operating space and different field of view ranges.
  • the intelligent assembly control system includes a mobile robot, a precision dual-frequency damped vibration isolation optical platform, a five-degree-of-freedom electric sliding table, a line laser scanner, and a first depth Learning camera, second deep learning camera, ball screw, first manipulator, second manipulator and host computer, in which: the precision dual-frequency damping vibration isolation optical platform is built, the five-degree-of-freedom electric sliding table, The line laser scanner, the ball screw, the first deep learning camera, and the first mechanical arm are installed on the precision dual-frequency damping vibration isolation optical platform; the second mechanical arm is installed on the mobile On the robot, the second deep learning camera is installed at the end of the second mechanical arm; the mobile robot performs omni-directional scanning in the work area, constructs map information, and sets the target area, work area, and work area of the workpiece to be tested.
  • Target position and working position after the mobile robot reaches the target area, the second robot arm is moved to the target position through teaching, and the second deep learning camera takes pictures of the workpiece to be measured and extracts all
  • the feature point information of the workpiece to be tested is used to identify the workpiece, and the identification data is transmitted to the host computer for processing to obtain the relative positional relationship between the second deep learning camera and the workpiece to be tested;
  • the positional relationship between the second robot arm and the workpiece to be measured is calculated through the robot motion processing matrix, and the converted coordinates of the workpiece to be measured are sent to the second robot arm, and the second robot arm performs
  • the posture is adjusted and the workpiece to be measured is grasped; the mobile robot moves to the working area, and the precision dual-frequency damping is damped by the first deep learning camera above the five-degree-of-freedom electric sliding table
  • the vibration isolation optical platform takes pictures, and the platform information is sent to the mobile robot.
  • the second mechanical arm places the workpiece to be tested on the precision dual-frequency damping vibration isolation optical platform and fixes it according to the platform information;
  • a robotic arm performs hand-eye calibration with a first deep learning camera.
  • the second deep learning camera takes pictures of a fixed workpiece to be tested, converts the fixed data into position information of assembly points, and performs hand-eye calibration on the position information , And send the position information to the first robotic arm, and the vacuum suction cup at the end of the first robotic arm will install the parts under the visual guidance of the first deep learning camera; the five-degree-of-freedom electric sliding table will be installed
  • the workpiece to be tested is transported to the line laser scanner for omnidirectional and multi-angle detection to generate point cloud data of each part of the workpiece to be tested, and the line laser scanner transmits the point cloud data to the host computer
  • the point cloud data model formed after processing is compared with the CAD model of the workpiece to analyze specific dimensional errors and defects of the workpiece to be tested, and to judge whether the workpiece to be tested is
  • This embodiment provides an integrated system of fully automatic precision inspection and intelligent assembly, including a first mechanical arm 1, a ball screw 2, a line laser scanner 3, a precision dual-frequency damped vibration isolation optical platform 4, and a five-degree-of-freedom electric Slide table 5, camera stand 6, first deep learning camera 7, mobile robot 8, motion control card, upper computer.
  • the mobile robot 8 scans the work area in all directions while constructing map information, and sets the target position and work position of the workpiece to be tested. After reaching the position of the workpiece to be measured, the second robot arm 8-1 is taught to move to the target area where the workpiece is located.
  • the second deep learning camera mounted on the end of the robot arm on the mobile robot takes pictures of the workpiece to be measured and extracts features Point information, identify the workpiece to be tested, transmit the data to the host computer for processing, and obtain the relative positional relationship between the second deep learning camera and the workpiece, and then calculate the relationship between the second robot arm and the workpiece through the mobile robot motion processing matrix Send the converted workpiece coordinates to the second manipulator 8-1, and the second manipulator 8-1 adjusts the position and posture and grabs the workpiece.
  • the mobile robot 8 continues to move to the working position, the first deep learning camera 7 above the five-degree-of-freedom electric sliding table 5 takes pictures of the stage, and sends the position information to the mobile robot 8, and the second robotic arm 8-1 will be tested
  • the workpiece is placed on the table and fixed.
  • the first robotic arm 1 and the first deep learning camera 7 perform hand-eye calibration.
  • the first deep learning camera 7 takes a picture of the fixed workpiece, and converts the data into position information of the assembly point, and then calibrates this through the hand-eye relationship. Position, so that the first robot arm 1 can accurately formulate actions, and send the position information to the first robot arm 1.
  • the first robot arm 1 is guided by the first deep learning camera 7 through the vacuum suction cup at the end to perform the wiring Install.
  • the five-degree-of-freedom electric sliding table 5 transports the installed workpiece to the line laser scanner 3 to perform omni-directional and multi-angle detection to generate point cloud data of each part of the part, and the line laser scanner 3 transmits the point cloud data to the host computer Process, compare the processed point cloud data model with the workpiece CAD model, analyze the specific size error and defect of the workpiece, and judge whether the workpiece is qualified or not.
  • the upper computer sends a signal to the mobile robot 8, and the mobile robot 8 moves to a new working position, grabs the workpiece, and places it in a designated position.
  • the five-degree-of-freedom electric sliding table 5 is installed on a precision dual-frequency damping vibration isolation optical platform, placed in a vertical state with the precision dual-frequency damping vibration isolation optical platform 4, located in the middle area of the platform 4, and the precision dual-frequency damping vibration isolation optical platform
  • the frequency damping and vibration isolation optical platform 4 is connected by threads.
  • the motion control card is located under the precision dual-frequency damping vibration isolation optical platform 4, and is connected to the sliding table joint cable while being connected to the upper computer.
  • the line laser scanner 3 is located above the central axis of the five-degree-of-freedom electric sliding table 5, and is parallel to the precision dual-frequency damping vibration isolation optical platform 4, and there is a fixed frame above the line laser scanner 3.
  • the ball and ball screw 2 is installed on a profile placed perpendicular to the precision dual-frequency damping and vibration isolation optical platform 4, and is located on the right side of the line laser scanner 3.
  • the host computer is located outside the working area, and is connected to the motion control card, the line laser scanner 3 cable, the first mechanical arm 1 and the first deep learning camera 7.
  • the first mechanical arm 1 is installed on the precision dual-frequency damping and vibration isolation optical platform 4, and is located directly behind the guide rail of the five-degree-of-freedom electric sliding table 5.
  • the first deep learning camera 7 is located directly above the five-degree-of-freedom electric sliding table 5, parallel to the precision dual-frequency damping vibration isolation optical platform 4, and the first deep learning camera 7 is fixed on the camera frame.
  • the deep learning camera at the end of the robotic arm is installed at the end of the second robotic arm 8-1, and is connected to the robotic arm 8-1 through a connecting piece.
  • the mobile robot 8 includes an AGV vehicle 8-4, a seven-degree-of-freedom manipulator 8-1, and a motion control cabinet 8-3.
  • the AGV vehicle 8-4 has a load of up to 60 kg and is equipped with a safety laser sensor, has map construction and autonomous navigation functions, and uses a safety scanning laser sensor based on environment mapping for positioning and autonomous selection of a route.
  • the motion control cabinet 8-3 is located above the AGV vehicle 8-4, the seven-degree-of-freedom manipulator 8-1 is located above the motion control cabinet 8-3, and the three are connected by a profile connecting frame 8-2.
  • the controller and the upper computer are connected through a wireless network as shown in Figure 9 to receive the status information and movement instructions of the mobile robot sent by the upper computer; Ethernet is connected with the laser sensor module to obtain the data of the laser sensor in real time.
  • Each joint of the seven-degree-of-freedom manipulator arms 8-1 and 1 is equipped with a force sensor, which can realize precise force control. At the same time, it can realize safe human-computer interaction, can accurately detect collisions, and ensure safety; it can realize dragging and teaching operation and assist programming software to improve programming efficiency.
  • the robot arm 1 and the host computer are connected through the TCP/IP protocol, and the script command string sent by the host computer is received through a specific programming interface, and the received script command is executed to complete the specified action.
  • the precision dual-frequency damping vibration isolation optical platform 4 as a whole is a three-layer sandwich honeycomb structure, which is divided into a table 4-1, a bracket 4-3, a dual-frequency damping vibration isolation mechanism 4-2, a height adjustment mechanism 4-5, and a belt
  • the brake is composed of 4-4 silent casters.
  • the table top 4-1 is located at the top of the platform, and has a three-layer sandwich honeycomb structure inside, which uses ferromagnetic stainless steel, which has good corrosion resistance.
  • the dual-frequency damping vibration isolation mechanism 4-2 is located under the table 4-1, in the middle position of the table 4-1 and the bracket 4-3, and has the effect of vibration isolation.
  • the bracket 4-3 adopts an integral welding process.
  • the shape of the long hair body is a four-support structure.
  • the four supports are connected by two trusses, which have good rigidity and stability.
  • Below the supports are equipped with a height adjustment mechanism 4-5 and silent casters 4-4 with brakes.
  • the height adjustment mechanism 4-5 is under each support leg, and the bottom is oblate, which increases the contact area with the ground. By adjusting the upper and lower distance of the height adjustment mechanism 4-5, the problem of bracket distortion and deformation caused by uneven ground can be solved.
  • the silent caster 4-4 is located below the lower truss, and is connected to the truss by four bolts, which facilitates movement and handling.
  • the precision dual-frequency damped vibration isolation optical platform provides good rigidity and Vibration isolation performance.
  • the five-degree-of-freedom electric sliding table 5 consists of four parts, namely the electric linear sliding table 5-2 in the X-axis direction, the electric swing sliding table 5-1 in the X-axis swing direction, and the electric linear sliding table in the Y-axis direction. 5-4, Y-axis swing direction electric swing slide 5-4, and electric rotary slide 5-5.
  • the X-axis electric linear sliding table 5-2 is composed of a dust cover, a sliding table ball screw, a linear slider guide rail, a coupling, a U-shaped bottom plate, and a servo motor.
  • the U-shaped bottom plate is made of aluminum alloy and the surface is oxidized.
  • the X-axis electric swing sliding table 5-1 and the Y-axis electric swing sliding table 5-4 are composed of a base, a worm gear, an arc-shaped V-shaped guide rail, and a stepping motor.
  • the base is made of aluminum alloy and the surface has been oxidized; the arc V-shaped guide rail is located above the base and has a strong load capacity. It swings around the worm wheel and worm driven by a stepping motor with high positioning accuracy.
  • the electric rotary sliding table 5-5 is composed of a base, a worm gear, a clearance adjustment structure, and a cross ball collar.
  • the base is made of hard aluminum alloy, which has good wear resistance.
  • the worm wheel is made of tin bronze material, and the worm is made of steel material, which has high hardness and good rigidity; the guiding mechanism adopts a cross ball collar, which can be used horizontally, vertically, and upside down; the clearance structure effectively reduces the backlash and ensures smooth operation.
  • the five-degree-of-freedom electric sliding table 5 can perform real-time scanning and detection of parts from multiple angles and all directions, improving the molding efficiency and scanning accuracy of the parts, making the overall outline of the parts clearer, and facilitating the judgment and analysis of part errors.
  • the motion control card adopts the pulse output type of pulse + direction (PUL+DIR), can realize multi-axis independent motion, and has the functions of acceleration and deceleration, point position, and trajectory motion planning.
  • PUL+DIR pulse output type of pulse + direction
  • the line laser scanner 3 is composed of a blue laser sensor, a cylindrical objective lens, a CMOS sensor, and a connector.
  • the blue laser sensor emits blue laser light, which is processed by the cylindrical objective lens to realize the uniform distribution of light;
  • the CMOS sensor is located inside the line laser scanner, which has high speed and high dynamic range;
  • the connector is located at the tail of the line laser scanner for Connect the line laser scanner and cable.
  • the rolling ball screw 2 is composed of a spiral dial 2-4, a screw 2-7, a nut, a ball, a pre-compression piece, a slide rail 2-2, a reverser, and a dustproof device.
  • a calibrated size range on the spiral dial 2-4 which can visually display the distance rotated; the screw 2-7 adopts external circulation transmission to ensure the overall transmission technology.
  • the screw is the active body, and the nut is with the screw.
  • the rotation angle of ⁇ converts the rotational motion into linear motion, and the slider 2-5 moves repeatedly on the slider rail 2-2 to realize the vertical movement of the line laser scanner 3 up and down.
  • the ball screw 2 and the line laser scanner 3 are fixed by a fixing frame 2-6.
  • the first deep learning camera 7 has a smart random sorting module, which integrates 3D structured light, image analysis, and robot arm motion control. It can quickly identify the position and posture of different objects in three-dimensional space through the 3D structured light. , Can accurately guide the robot arm to pick and place.
  • the host computer is a computer, used to display the real-time status of the robot, including the position information display of the mobile robot 8 during the navigation process, and the remote setting of the target; used to control the trajectory planning of the five-degree-of-freedom electric sliding table 5; Receive and process the three-dimensional point cloud data transmitted by the line laser scanner 3 to obtain the qualified or unqualified test results of the parts, and transmit the test results to the robotic arm 8-1; used to receive the feedback information from the infrared sensor and feed back the electric sliding table 5
  • the operating status and location of the camera used to process the photos taken by the first deep learning camera 7, extract point information, and send the processed information to the robotic arm 1.
  • the hand-eye calibration method is to perform hand-eye calibration of the robotic arm 1 and the first deep learning camera 7 through the Tsai-Lenz algorithm, so that the end effector of the robotic arm 1 is fixed to the calibration board, and the calibration board is kept on the camera screen.
  • the first deep learning camera 7 takes a series of pictures taken by the calibration board, and records the pose information of the robotic arm at the same time, and matches them one by one.
  • the camera 7 is compared with the corresponding relationship between the visual information and the pose 1 of the robotic arm. Solve the spatial relationship with robotic arm 1.
  • Figure 10 shows the information transfer process between the deep learning camera and the robotic arm.
  • the movement plan of the mobile robot 8 is shown in Fig. 11.
  • the control system of the mobile robot 8 provides the odometer information.
  • the odometer data is transformed into a machine by coordinate transformation.
  • the angle control target refined to each joint is obtained, and finally the joint angle is controlled according to the PID algorithm.
  • the system is refreshed at a certain frequency to ensure the flexibility and accuracy of mobile operations.
  • the clamping jaws at the end of the robotic arm can be replaced according to requirements, and are not limited to one type; the clamps on the electric sliding table can be replaced according to the type of the workpiece to be tested, and are not limited to one type; the mobile machinery The deep learning camera mounted on the end of the arm can be replaced with different models according to needs, and it is not limited to one.
  • the above embodiments describe in detail the different configurations of the intelligent assembly control system.
  • the present invention includes but is not limited to the configurations listed in the above embodiments, and any configuration is performed on the basis of the configurations provided in the above embodiments.
  • the content of the change belongs to the protection scope of the present invention. Those skilled in the art can draw inferences based on the content of the above-mentioned embodiments.

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Abstract

一种智能装配控制***，具体为一种全自动精密检测与智能装配一体化***，包括移动机器人（8）、精密双频阻尼隔振光学平台（4）、五自由度电动滑台（5）、线激光扫描仪（3）、第一深度学习相机（7）、第二深度学习相机、滚珠丝杠（2）、第一机械臂（1）、第二机械臂（8-1）及上位机，该***能够自动安装手机背板排线插件，实现零件从出厂到装配、检测流程全自动化，节省人工成本、提高生产效率以及实现拖动示教操作。

Description

智能装配控制*** 技术领域
本发明涉及智能制造技术领域，特别涉及一种智能装配控制***。
背景技术
随着机器人领域的不断发展，智能化装配与高精密检测设备逐渐普及，人们在生产中节省了大量的人工成本并大幅度提高了生产效率。
然而，目前由于3C等行业对于复杂造型的广泛应用，传统机器人感知与智能控制无法满足日益复杂的作业要求，如曲面玻璃的检测与装配、OLED柔性屏的装配与测试、大幅面屏幕的精密测量与装配等，自动化程度仍然不够高，很多环节都需要人工干预，这样就存在着装配及检测精度不够、工作环境安全性无法得到确实保证的问题。
对于同一操作空间不同视野范围中的操作对象，基于视觉、力觉等信息融合的机器人环境感知与建模方法存在效率低、跨尺度难、抗干扰能力弱的问题；在机器人组装运动规划层面，如何实现具备力位伺服感知的“机-环境”自主规划与组装，以适应精密器件组装中的狭小质脆环境，是亟待解决的问题。因此，研究高反光器件组装机器人精密感知与柔顺控制等关键技术，对解决行业应用的技术难题具有重要意义。
发明内容
本发明的目的在于提供一种智能装配控制***，以解决现有的机器人环境感知与建模方法无法操作同一操作空间不同视野范围中的操作对象的问题。
为解决上述技术问题，本发明提供一种智能装配控制***，所述智能装配控制***包括移动机器人、精密双频阻尼隔振光学平台、五自由度电动滑台、线激光扫描仪、第一深度学习相机、第二深度学习相机、滚珠丝 杠、第一机械臂、第二机械臂及上位机，其中：
搭建所述精密双频阻尼隔振光学平台，所述五自由度电动滑台、所述线激光扫描仪、所述滚珠滚珠丝杠、所述第一深度学***台上；
所述第二机械臂安装于所述移动机器人上，所述第二深度学习相机安装于所述第二机械臂的末端；所述移动机器人在工作区域内进行全方位扫描，构建地图信息，设定待测工件的目标区域、工作区域、目标位置及工作位置；
所述移动机器人到达所述目标区域后，通过示教使所述第二机械臂移动至所述目标位置，由所述第二深度学习相机对待测工件进行拍照，提取所述待测工件的特征点信息以识别所述待测工件，将识别数据传输给所述上位机进行处理，得出所述第二深度学习相机与所述待测工件之间的相对位置关系；
通过机器人动作处理矩阵计算出所述第二机械臂与所述待测工件之间的位置关系，将转换后的待测工件坐标发送给所述第二机械臂，由所述第二机械臂进行位姿调整并对所述待测工件进行抓取；
所述移动机器人移动至所述工作区域，由所述五自由度电动滑台上方的所述第一深度学***台进行拍照，将平台信息发送至所述移动机器人，所述第二机械臂根据所述平台信息将待测工件置于精密双频阻尼隔振光学平台上并进行固定；
所述第一机械臂与第一深度学习相机进行手眼标定，所述第二深度学习相机对固定好的待测工件拍照，并将固定数据转化为装配点位的位置信息，对所述位置信息进行手眼标定，并将所述位置信息发送至所述第一机械臂，第一机械臂末端的真空吸盘在第一深度学习相机的视觉引导下对零件进行安装；
所述五自由度电动滑台将安装好的待测工件运送至所述线激光扫描仪下，进行全方位多角度检测，生成待测工件各个部分零件的点云数据，所述线激光扫描仪传输所述点云数据至所述上位机进行处理，处理后形成的点云数据模型与工件CAD模型对比，以分析待测工件特定尺寸误差与缺 陷，判断待测工件合格与否；
检测完成后上位机将检测完成信号发送给所述移动机器人，并由移动机器人移动至新的目标区域，对工件进行抓取，放置于指定位置。
可选的，在所述的智能装配控制***中，所述五自由度电动滑台安装于所述精密双频阻尼隔振光学平台的中心区域，与所述精密双频阻尼隔振光学平台成垂直状态放置，与所述精密双频阻尼隔振光学平台通过螺纹连接；
所述智能装配控制***还包括运动控制卡，所述运动控制卡位于精密双频阻尼隔振光学平台的下方，所述运动控制卡连接所述五自由度电动滑台的接头线缆，且连接上位机，上位机向运动控制卡发出指令控制所述五自由度电动滑台的运动；所述运动控制卡采用脉冲结合方向的脉冲输出类型实现多轴独立运动，具有加减速、点位、轨迹运动规划功能；
所述线激光扫描仪位于五自由度电动滑台的中心轴线上方，且与所述精密双频阻尼隔振光学平台平行，所述线激光扫描仪上方有固定架；
所述滚珠滚珠丝杠安装在与所述精密双频阻尼隔振光学平台垂直放置的型材上，位于线激光扫描仪的右侧；
所述上位机位于所述精密双频阻尼隔振光学平台上，连接所述运动控制卡、线激光扫描仪的线缆、第一机械臂以及第一深度学习相机；
所述第一机械臂安装在所述精密双频阻尼隔振光学平台上，位于五自由度电动滑台导轨的正后方；
所述第一深度学***台平行，所述第一深度学习相机固定于相机架上。
可选的，在所述的智能装配控制***中，所述移动机器人包括AGV车及运动控制柜，其中：
所述AGV车的额度负载为60～80千克，所述AGV车具有地图构建以及自主导航功能，所述AGV车具有安全激光传感器，通过基于环境映射的安全激光传感器进行定位，自主选择路径；
所述运动控制柜位于所述AGV车上方，所述第二机械臂位于所述运动控制柜上方；
所述运动控制柜与所述上位机通过无线网络进行连接，所述运动控制柜接收上位机发送的移动机器人状态信息以及移动指令；所述运动控制柜与所述安全激光传感器连接，用于实时获取安全激光传感器的定位数据。
可选的，在所述的智能装配控制***中，所述第一机械臂及所述第二机械臂的各个关节具有力传感器，所述力传感器具有碰撞检测功能；所述第一机械臂及所述第二机械臂能够实现拖动示教操作；机械臂与上位机之间通过TCP/IP协议进行连接，接收上位机发送的脚本指令字符串，并运行接收到的脚本指令以完成指定动作；
所述第一深度学习相机与所述第二深度学习相机均具有智慧随机分拣模块，集成3D结构光、影像分析及机器人手臂运动控制为一体，能够透过3D结构光快速辨识不同物件在三维空间摆放的位置与姿态，以精准导引第一机器臂及第二机械臂进行取放。
可选的，在所述的智能装配控制***中，所述精密双频阻尼隔振光学平台包括台面、支架、双频阻尼隔振机构、高度调整机构、刹车静音脚轮；
所述台面位于所述支架上方，用于承载所述第一机械臂、五自由度电动滑台、线激光扫描仪及第一深度学习相机；
所述支架为支撑结构，四个支架之间两两由两段桁架相连；
所述双频阻尼隔振机构位于所述台面与所述支架之间，用于隔振；
所述支架下方具有高度调整机构和刹车静音脚轮。
可选的，在所述的智能装配控制***中，所述五自由度电动滑台包括X轴电动直线滑台，X轴电动摆动滑台，Y轴电动直线滑台，Y轴电动摆动滑台及电动旋转滑台；
所述X轴电动直线滑台及Y轴电动直线滑台均由防尘罩、滑台滚珠丝杠、线性滑块导轨、联轴器、U型底板、伺服电机组成；所述滑台滚珠丝杠安装在U型底板中间；U型底板上方安装有防尘罩，为不锈钢材质；线性滑块导轨在伺服电机驱动控制下在滑台滚珠丝杠上运动；
所述X轴电动摆动滑台及Y轴电动摆动滑台均由第一底座、第一蜗轮蜗杆、弧形V型导轨、步进电机组成；所述弧形V型导轨位于第一底座上方，在所述步进电机驱动下绕着第一蜗轮蜗杆摆动；
所述电动旋转滑台由第二底座、第二蜗轮蜗杆、调隙结构、交叉滚珠轴环组成；所述交叉滚珠轴环能够水平、竖直、倒置使用；调隙结构用于减小背隙。
可选的，在所述的智能装配控制***中，所述线激光扫描仪由蓝色激光传感器、柱面物镜、CMOS传感器、连接器组成；所述蓝色激光传感器发射蓝色激光，经过柱面物镜处理，实现光量的均匀分布；CMOS传感器位于线激光扫描仪内部；连接器位于线激光扫描仪尾部，用于连接线激光扫描仪与电缆。
所述滚珠丝杠由螺旋刻度盘、丝杠、螺母、滑块、滑块滑轨组成；螺旋刻度盘上有标定的尺寸范围，能够直观显示所转动的距离；丝杠采用外循环式传动，丝杠作为主动体，螺母随丝杠的转动角度将旋转运动转化为直线运动，滑块在滑块滑轨上反复运动，实现线激光扫描仪的上下垂直移动；滚珠丝杠与线激光扫描仪通过所述固定架固定。
可选的，在所述的智能装配控制***中，所述上位机为计算机，用于显示移动机器人的实时状态，包括移动机器人在导航过程中的位置信息显示、目标的远程设定；
所述上位机还用于控制五自由度电动滑台的轨迹规划；
所述上位机还用于接收线激光扫描仪传输的三维点云数据并处理，得到零件合格或不合格的检测结果，将检测结果传输到第一机械臂；
所述上位机还用于接收红外线传感器的反馈信息，反馈五自由度电动滑台的运行状况以及所在位置；
所述上位机还用于处理所述第一深度学习相机拍摄的照片，提取点位信息，将处理后的信息发送至所述第一机械臂。
可选的，在所述的智能装配控制***中，所述手眼标定方法为通过Tsai-Lenz算法来对所述第一机械臂和所述第一深度学习相机进行手眼标定，让所述第一机械臂的末端执行器固定着标定板，并将标定板保持在第一深度学习相机的画面之中，第一深度学习相机拍摄标定板采集一系列图片，并与此同时记录第一机械臂的位姿信息，将其一一对应，通过视觉信息与第一机械臂位姿间的对应关系对第一深度学习相机与第一机械臂空间 关系进行求解。
可选的，在所述的智能装配控制***中，由移动机器人的控制***提供里程计信息，当第二机械臂的控制***接收到之后，先对里程计的数据进行坐标变换，转化为第二机械臂的底座坐标系的位移量，再根据待测工件所能提供的确定的末端位姿和第二机械臂底座的位移量，得到第二机械臂对应更新后得等效规划目标，得到一个更新的末端位姿；
通过第二机械臂的逆运动学求解，得到细化到各个关节的角度控制目标，最后根据PID算法对关节角度进行控制。
在本发明提供的智能装配控制***中，提出一种自动安装手机背板排线插件的***。能够实现零件从出厂到装配、检测流程全自动化，从而真正意义上达到节省人工成本、提高生产效率以及验证多种技术手段的目的。本发明提出的一种全自动检测与智能装配一体化***可以实现真正意义上的全自动，在进行初始示教操作后，整个工作流程中将不再需要人工进行干预，同时当有人进入工作区域后，机械臂和移动机器人上配备的传感器将会对接近的人体做出反应并停止运动，使得安全性也可以得到保障。一种全自动检测与智能装配一体化***将工件的自动化装配与检测集成与一体，在保证生产质量同时也提高了生产效率。所述七自由度机械臂的每个关节处都配有力传感器，可以实现精确力控。同时能够实现安全的人机交互，对碰撞能够精确检测，保证安全性；能够实现拖动示教操作，辅助编程软件从而提高编程效率。
附图说明
图1为本发明具体实施例提供的一种全自动检测与智能装配控制***的整体结构示意图；
图2为本发明具体实施例提供的精密双频阻尼隔振光学平台的结构示意图；
图3为本发明具体实施例提供的五自由度电动滑台的结构示意图；
图4为本发明具体实施例提供的线激光扫描仪的结构示意图；
图5为本发明具体实施例提供的滚珠丝杠与型材的结构示意图；
图6为本发明具体实施例提供的第一机械臂与第二机械臂(七自由度机械臂)的结构示意图；
图7为本发明具体实施例提供的移动机器人示意图；
图8为本发明具体实施例提供的整体***结构框图；
图9为本发明具体实施例提供的移动机器人控制***示意图；
图10为本发明具体实施例提供的零件识别定位技术路线图；
图11为本发明具体实施例提供的移动机器人运动规划路线图；
图中所示：1第一机械臂；2滚珠丝杠；3线激光扫描仪；4精密双频阻尼隔振光学平台；5五自由度电动滑台；6相机架；7第一深度学***台台面；4-2双频阻尼隔振机构；4-3支架；4-4刹车静音脚轮；4-5高度调整机构；5-1X轴摆动方向滑台结构；5-2X轴直线方向滑台结构；5-3旋转滑台结构；5-4Y轴直线方向与摆动方向滑台结构；8-1第二机械臂；8-2型材架；8-3控制柜；8-4AGV车。
具体实施方式
以下结合附图和具体实施例对本发明提出的智能装配控制***作进一步详细说明。根据下面说明和权利要求书，本发明的优点和特征将更清楚。需说明的是，附图均采用非常简化的形式且均使用非精准的比例，仅用以方便、明晰地辅助说明本发明实施例的目的。
在本发明的描述中，需要理解的是，术语“上”、“下”等指示的方位或位置关系为基于附图所示的方位或位置关系，或者是本发明产品使用时惯常摆放的方位或位置关系，或者是本领域技术人员惯常理解的方位或位置关系，仅是为了便于描述本发明和简化描述，而不是指示或暗示所指的设备或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本发明的限制。本发明的“第一”、“第二”等，仅仅用于在描述上加以区分，并没有特殊的含义。在本发明的描述中，还需要说明的是，除非另 有明确的规定和限定，术语“设置”、“安装”应做广义理解，例如，可以是固定连接，也可以是可拆卸连接，或一体地连接；可以是直接相连，也可以通过中间媒介间接相连。对于本领域的普通技术人员而言，可以具体情况理解上述术语在本发明中的具体含义。
本发明的核心思想在于提供一种智能装配控制***，以解决现有的机器人环境感知与建模方法无法操作同一操作空间不同视野范围中的操作对象的问题。
为实现上述思想，本发明提供了一种智能装配控制***，所述智能装配控制***包括移动机器人、精密双频阻尼隔振光学平台、五自由度电动滑台、线激光扫描仪、第一深度学***台，所述五自由度电动滑台、所述线激光扫描仪、所述滚珠丝杠、所述第一深度学***台上；所述第二机械臂安装于所述移动机器人上，所述第二深度学***台进行拍照，将平台信息发送至所述移动机器人，所述第二机械臂根据所述平台信息将待测工件置于精密双频阻尼隔振光学平台上并进行固定；所述第一机械臂与第一深度学习相机进行手眼标定，所述第二深度学习相机对固定好的待测工件拍照，并将固定数据转化为装配点位的位置信息，对所述位置信息进行手眼 标定，并将所述位置信息发送至所述第一机械臂，第一机械臂末端的真空吸盘在第一深度学习相机的视觉引导下对零件进行安装；所述五自由度电动滑台将安装好的待测工件运送至所述线激光扫描仪下，进行全方位多角度检测，生成待测工件各个部分零件的点云数据，所述线激光扫描仪传输所述点云数据至所述上位机进行处理，处理后形成的点云数据模型与工件CAD模型对比，以分析待测工件特定尺寸误差与缺陷，判断待测工件合格与否；检测完成后上位机将检测完成信号发送给所述移动机器人，并由移动机器人移动至新的目标区域，对工件进行抓取，放置于指定位置。
<实施例一>
本实施例提供一种全自动精密检测与智能装配一体化***，包括第一机械臂1、滚珠滚珠丝杠2、线激光扫描仪3、精密双频阻尼隔振光学平台4、五自由度电动滑台5、相机架6、第一深度学***台搭建完成后，移动机器人8在工作区域内进行全方位扫描同时构建地图信息，设定待测工件目标位置及工作位置。在到达待测工件所在位置后，先通过示教让第二机械臂8-1移动至工件所在目标区域，由移动机器人上机械臂末端搭载的第二深度学习相机对待测工件进行拍照，提取特征点信息，识别待测工件，将数据传输给上位机进行处理，得出第二深度学习相机与工件之间的相对位置关系之后再通过移动机器人动作处理矩阵计算出第二机械臂与工件之间的位置关系，将转换后的工件坐标发送给第二机械臂8-1，由第二机械臂8-1进行位姿调整并对工件进行抓取。移动机器人8继续运动至工作位置，由五自由度电动滑台5上方的第一深度学习相机7对置物台进行拍照，将位置信息发送至移动机器人8，第二机械臂8-1将待测工件置于置物台并进行固定。第一机械臂1与第一深度学习相机7进行手眼标定，完成后，第一深度学习相机7对固定好的工件拍照，并将数据转化为装配点位的位置信息，再通过手眼关系标定该位置，令第一机械臂1能够准确制定动作，并将位置信息发送给第一机械臂1，第一机械臂1在第一深度学习相机7的视觉引导下通过末端的真空吸盘对排线进行安装。五自由度电动滑台5将安装好的工件运送至线激光扫描仪3下，进行全方位多角度的检测，生成零件各个部分的点云数 据，线激光扫描仪3传输点云数据至上位机进行处理，处理后的点云数据模型与工件CAD模型对比，分析工件特定尺寸误差与缺陷，判断工件合格与否。检测完成后上位机将信号发送给移动机器人8，并由移动机器人8移动至新的工作位置，对工件进行抓取，放置于指定位置。
所述五自由度电动滑台5安装在精密双频阻尼隔振光学平台上，与所述精密双频阻尼隔振光学平台4成垂直状态放置，位于平台4的中间区域，与所述精密双频阻尼隔振光学平台4通过螺纹连接。
所述运动控制卡位于精密双频阻尼隔振光学平台4的下方，一边连接滑台接头线缆，一边连接上位机。
所述线激光扫描仪3位于五自由度电动滑台5的中心轴线上方，与所述精密双频阻尼隔振光学平台4平行，线激光扫描仪3上方有固定架。
所述滚珠滚珠丝杠2安装在与所述精密双频阻尼隔振光学平台4垂直放置的型材上，位于线激光扫描仪3的右侧。
所述上位机位于工作区域外，连接运动控制卡、线激光扫描仪3线缆、第一机械臂1以及第一深度学习相机7。
所述第一机械臂1安装在所述精密双频阻尼隔振光学平台4上，位于五自由度电动滑台5导轨的正后方。
所述第一深度学***台4平行，第一深度学习相机7固定于相机架上。
所述机械臂末端深度学习相机安装于第二机械臂8-1末端，通过连接件和机械臂8-1相连。
所述移动机器人8包括AGV车8-4、七自由度机械臂8-1以及运动控制柜8-3。所述AGV车8-4负载可达60kg并配有安全激光传感器，具有地图构建以及自主导航功能，通过基于环境映射的安全扫描激光传感器进行定位，自主选择路径。所述运动控制柜8-3位于AGV车8-4上方，所述七自由度机械臂8-1位于运动控制柜8-3上方，三者由型材连接架8-2进行连接。其中控制器与上位机之间如图9所示，通过无线网络进行连接，接收上位机发送的移动机器人状态信息以及移动指令；与激光传感器模块进行Ethernet连接，用于实时获取激光传感器的数据。
所述七自由度机械臂8-1和1的每个关节处都配有力传感器，可以实现精确力控。同时能够实现安全的人机交互，对碰撞能够精确检测，保证安全性；能够实现拖动示教操作，辅助编程软件从而提高编程效率。机械臂1与上位机之间通过TCP/IP协议进行连接，通过特定的编程接口接收上位机发送的脚本指令字符串，并运行接收到的脚本指令，从而完成指定动作。
所述精密双频阻尼隔振光学平台4整体为三层夹心式蜂窝结构，分为台面4-1、支架4-3、双频阻尼隔振机构4-2、高度调整机构4-5、带刹车的静音脚轮4-4组成。所述台面4-1位于所述平台的最上方，内部为三层夹心式蜂窝结构，采用铁磁不锈钢，具有很好的耐腐蚀性能。所述双频阻尼隔振机构4-2处于台面4-1下面，处于台面4-1与支架4-3中间位置，起到隔振的效果，所述支架4-3采用整体焊接工艺，呈长发体形状，为四支撑结构，四支架之间两两由两段桁架相连，具有良好的刚性和稳定性，支架下方具有带高度调整机构4-5和带刹车的静音脚轮4-4，高度调整机构4-5在每个支撑腿下方，底部呈现扁圆体，加大与地面的接触面积，通过调节高度调整机构4-5的上下距离可解决地面不平引起的支架扭曲、变形的问题，静音脚轮4-4位于下端桁架的下方，与桁架为四个螺栓相连，方便了移动和搬运动作，所述精密双频阻尼隔振光学平台为零件的检测与分拣提供了良好的刚性和隔振性能。
所述五自由度电动滑台5由四个部分组成，分别是X轴方向的电动直线滑台5-2，X轴摆动方向的电动摆动滑台5-1，Y轴方向的电动直线滑台5-4，Y轴摆动方向的电动摆动滑台5-4，以及电动旋转滑台5-5。所述X轴电动直线滑台5-2由防尘罩、滑台滚珠丝杠、配合线性滑块导轨、联轴器、U型底板、伺服电机组成U型底板采用铝合金材质，表面经过氧化处理，耐磨性好；滑台滚珠丝杠安装在U型底板中间，定位精度高；U型底板上方安装有防尘罩，为不锈钢材质；线性滑块导轨在伺服电机控制下驱动导轨在滑台滚珠丝杠上运动。所述X轴电动摆动滑台5-1、Y轴电动摆动滑台5-4由底座、蜗轮蜗杆、弧形V型导轨、步进电机组成。底座采用铝合金材料，表面经过氧化处理；弧形V型导轨位于底座上方，负载能力强， 在步进电机驱动下绕着蜗轮蜗杆摆动，定位精度高。所述电动旋转滑台5-5由底座、蜗轮蜗杆、调隙结构、交叉滚珠轴环组成。底座采用硬质铝合金，具有良好的耐磨性。蜗轮采用锡青铜材料，蜗杆采用钢制材料，硬度高、刚性好；导向机构采用交叉滚珠轴环，可水平、竖直、倒置使用；调隙结构有效减小了了背隙，保证运行顺畅。
所述五自由度电动滑台5，能从多角度、全方位对零件进行实时扫描检测，提高零件的成型效率和扫描精度，使得零件的整体轮廓更为清晰，有利于零件误差的判断分析。
所述运动控制卡采用脉冲+方向(PUL+DIR)的脉冲输出类型，可实现多轴独立运动，具有加减速、点位、轨迹运动规划功能。
所述线激光扫描仪3由蓝色激光传感器、柱面物镜、CMOS传感器、连接器组成。蓝色激光传感器发射蓝色激光，经过柱面物镜的处理，实现光量的均匀分布；CMOS传感器位于线激光扫描仪内部，具有高速性与高动态范围；连接器位于线激光扫描仪尾部，用于连接线激光扫描仪与电缆。
所述滚动滚珠丝杠2由螺旋刻度盘2-4、丝杠2-7、螺母、滚珠、预压片、滑块滑轨2-2、反向器、防尘器组成。螺旋刻度盘2-4上有标定的尺寸范围，可直观显示所转动的距离；丝杠2-7采用外循环式传动，保证了整体的传动工艺性，丝杠作为主动体，螺母随丝杠的转动角度将旋转运动转化为直线运动，滑块2-5在滑块滑轨2-2上反复运动，实现线激光扫描仪3的上下垂直移动。滚珠丝杠2与线激光扫描仪3通过固定架2-6固定。
所述第一深度学习相机7具有智慧随机分拣模块，集成了3D结构光、影像分析及机器人手臂运动控制为一体，能够透过3D结构光快速辨识不同物件在三维空间摆放的位置与姿态，得以精准导引机器手臂进行取放。
所述上位机为计算机，用于显示机器人的实时状态，包括移动机器人8在导航过程中的位置信息显示、目标的远程设定；用于控制五自由度电动滑台5的轨迹规划；用于接收线激光扫描仪3传输的三维点云数据并处理，得到零件合格或不合格的检测结果，将检测结果传输到机械臂8-1；用于接收红外线传感器的反馈信息，反馈电动滑台5的运行状况以及所在位置；用于处理第一深度学习相机7拍摄的照片，提取点位信息，将处理后 的信息发送至机械臂1。
所述手眼标定方法为通过Tsai-Lenz算法来对机械臂1和第一深度学习相机7进行手眼标定，让机械臂1的末端执行器固定着标定板，并将标定板保持在相机的画面之中，第一深度学习相机7拍摄标定板采集一系列图片，并与此同时记录机械臂的位姿信息，将其一一对应，通过视觉信息与机械臂1位姿间的对应关系对相机7与机械臂1空间关系进行求解。如图10所示为深度学习相机与机械臂之间进行的信息传递过程。
所述移动机器人8的移动规划如图11所示，首先由移动机器人8的控制***提供里程计信息，当机械臂的控制***接收到之后，先对里程计的数据进行坐标变换，转化为机械臂的底座坐标系的位移量，再根据待测工件所能提供的确定的末端位姿和机械臂底座的位移量，得到机械臂对应更新后得等效规划目标，得到一个更新的末端位姿。通过机械臂的逆运动学求解，得到细化到各个关节的角度控制目标，最后根据PID算法对关节角度进行控制。***以一定的频率刷新，从而保证移动操作的柔顺性和准确性。
优选地，所述机械臂末端夹爪可以根据需求进行更换，并不仅限于一种；所述电动滑台上的夹具可以根据待测工件的类别进行更换，并不仅限于一种；所述移动机械臂末端搭载的深度学习相机可以根据需求更换不同的型号，并不仅限于一种。
综上，上述实施例对智能装配控制***的不同构型进行了详细说明，当然，本发明包括但不局限于上述实施中所列举的构型，任何在上述实施例提供的构型基础上进行变换的内容，均属于本发明所保护的范围。本领域技术人员可以根据上述实施例的内容举一反三。
上述描述仅是对本发明较佳实施例的描述，并非对本发明范围的任何限定，本发明领域的普通技术人员根据上述揭示内容做的任何变更、修饰，均属于权利要求书的保护范围。

Claims (10)

  1. 一种智能装配控制***，其特征在于，所述智能装配控制***包括移动机器人、精密双频阻尼隔振光学平台、五自由度电动滑台、线激光扫描仪、第一深度学习相机、第二深度学习相机、滚珠滚珠丝杠、第一机械臂、第二机械臂及上位机，其中：
    搭建所述精密双频阻尼隔振光学平台，所述五自由度电动滑台、所述线激光扫描仪、所述滚珠滚珠丝杠、所述第一深度学***台上；
    所述第二机械臂安装于所述移动机器人上，所述第二深度学习相机安装于所述第二机械臂的末端；所述移动机器人在工作区域内进行全方位扫描，构建地图信息，设定待测工件的目标区域、工作区域、目标位置及工作位置；
    所述移动机器人到达所述目标区域后，通过示教使所述第二机械臂移动至所述目标位置，由所述第二深度学习相机对待测工件进行拍照，提取所述待测工件的特征点信息以识别所述待测工件，将识别数据传输给所述上位机进行处理，得出所述第二深度学习相机与所述待测工件之间的相对位置关系；
    通过机器人动作处理矩阵计算出所述第二机械臂与所述待测工件之间的位置关系，将转换后的待测工件坐标发送给所述第二机械臂，由所述第二机械臂进行位姿调整并对所述待测工件进行抓取；
    所述移动机器人移动至所述工作区域，由所述五自由度电动滑台上方的所述第一深度学***台进行拍照，将平台信息发送至所述移动机器人，所述第二机械臂根据所述平台信息将待测工件置于精密双频阻尼隔振光学平台上并进行固定；
    所述第一机械臂与第一深度学习相机进行手眼标定，所述第二深度学习相机对固定好的待测工件拍照，并将固定数据转化为装配点位的位置信息，对所述位置信息进行手眼标定，并将所述位置信息发送至所述第一机械臂，第一机械臂末端的真空吸盘在第一深度学习相机的视觉引导下对零件进行安装；
    所述五自由度电动滑台将安装好的待测工件运送至所述线激光扫描仪下，进行全方位多角度检测，生成待测工件各个部分零件的点云数据，所述线激光扫描仪传输所述点云数据至所述上位机进行处理，处理后形成的点云数据模型与工件CAD模型对比，以分析待测工件特定尺寸误差与缺陷，判断待测工件合格与否；
    检测完成后上位机将检测完成信号发送给所述移动机器人，并由移动机器人移动至新的目标区域，对工件进行抓取，放置于指定位置。
  2. 如权利要求1所述的智能装配控制***，其特征在于，所述五自由度电动滑台安装于所述精密双频阻尼隔振光学平台的中心区域，与所述精密双频阻尼隔振光学平台成垂直状态放置，与所述精密双频阻尼隔振光学平台通过螺纹连接；
    所述智能装配控制***还包括运动控制卡，所述运动控制卡位于精密双频阻尼隔振光学平台的下方，所述运动控制卡连接所述五自由度电动滑台的接头线缆，且连接上位机，上位机向运动控制卡发出指令控制所述五自由度电动滑台的运动；所述运动控制卡采用脉冲结合方向的脉冲输出类型实现多轴独立运动，具有加减速、点位、轨迹运动规划功能；
    所述线激光扫描仪位于五自由度电动滑台的中心轴线上方，且与所述精密双频阻尼隔振光学平台平行，所述线激光扫描仪上方有固定架；
    所述滚珠滚珠丝杠安装在与所述精密双频阻尼隔振光学平台垂直放置的型材上，位于线激光扫描仪的右侧；
    所述上位机位于所述精密双频阻尼隔振光学平台上，连接所述运动控制卡、线激光扫描仪的线缆、第一机械臂以及第一深度学习相机；
    所述第一机械臂安装在所述精密双频阻尼隔振光学平台上，位于五自由度电动滑台导轨的正后方；
    所述第一深度学***台平行，所述第一深度学习相机固定于相机架上。
  3. 如权利要求1所述的智能装配控制***，其特征在于，所述移动机器人包括AGV车及运动控制柜，其中：
    所述AGV车的额度负载为60～80千克，所述AGV车具有地图构建以 及自主导航功能，所述AGV车具有安全激光传感器，通过基于环境映射的安全激光传感器进行定位，自主选择路径；
    所述运动控制柜位于所述AGV车上方，所述第二机械臂位于所述运动控制柜上方；
    所述运动控制柜与所述上位机通过无线网络进行连接，所述运动控制柜接收上位机发送的移动机器人状态信息以及移动指令；所述运动控制柜与所述安全激光传感器连接，用于实时获取安全激光传感器的定位数据。
  4. 如权利要求1所述的智能装配控制***，其特征在于，所述第一机械臂及所述第二机械臂的各个关节具有力传感器，所述力传感器具有碰撞检测功能；所述第一机械臂及所述第二机械臂能够实现拖动示教操作；机械臂与上位机之间通过TCP/IP协议进行连接，接收上位机发送的脚本指令字符串，并运行接收到的脚本指令以完成指定动作；
    所述第一深度学习相机与所述第二深度学习相机均具有智慧随机分拣模块，集成3D结构光、影像分析及机器人手臂运动控制为一体，能够透过3D结构光快速辨识不同物件在三维空间摆放的位置与姿态，以精准导引第一机器臂及第二机械臂进行取放。
  5. 如权利要求1所述的智能装配控制***，其特征在于，所述精密双频阻尼隔振光学平台包括台面、支架、双频阻尼隔振机构、高度调整机构、刹车静音脚轮；
    所述台面位于所述支架上方，用于承载所述第一机械臂、五自由度电动滑台、线激光扫描仪及第一深度学习相机；
    所述支架为支撑结构，四个支架之间两两由两段桁架相连；
    所述双频阻尼隔振机构位于所述台面与所述支架之间，用于隔振；
    所述支架下方具有高度调整机构和刹车静音脚轮。
  6. 如权利要求1所述的智能装配控制***，其特征在于，所述五自由度电动滑台包括X轴电动直线滑台，X轴电动摆动滑台，Y轴电动直线滑台，Y轴电动摆动滑台及电动旋转滑台；
    所述X轴电动直线滑台及Y轴电动直线滑台均由防尘罩、滑台滚珠丝杠、线性滑块导轨、联轴器、U型底板、伺服电机组成；所述滑台滚珠丝 杠安装在U型底板中间；U型底板上方安装有防尘罩，为不锈钢材质；线性滑块导轨在伺服电机驱动控制下在滑台滚珠丝杠上运动；
    所述X轴电动摆动滑台及Y轴电动摆动滑台均由第一底座、第一蜗轮蜗杆、弧形V型导轨、步进电机组成；所述弧形V型导轨位于第一底座上方，在所述步进电机驱动下绕着第一蜗轮蜗杆摆动；
    所述电动旋转滑台由第二底座、第二蜗轮蜗杆、调隙结构、交叉滚珠轴环组成；所述交叉滚珠轴环能够水平、竖直、倒置使用；调隙结构用于减小背隙。
  7. 如权利要求1所述的智能装配控制***，其特征在于，所述线激光扫描仪由蓝色激光传感器、柱面物镜、CMOS传感器、连接器组成；所述蓝色激光传感器发射蓝色激光，经过柱面物镜处理，实现光量的均匀分布；CMOS传感器位于线激光扫描仪内部；连接器位于线激光扫描仪尾部，用于连接线激光扫描仪与电缆。
    所述滚珠丝杠由螺旋刻度盘、丝杠、螺母、滑块、滑块滑轨组成；螺旋刻度盘上有标定的尺寸范围，能够直观显示所转动的距离；丝杠采用外循环式传动，丝杠作为主动体，螺母随丝杠的转动角度将旋转运动转化为直线运动，滑块在滑块滑轨上反复运动，实现线激光扫描仪的上下垂直移动；滚珠滚珠丝杠与线激光扫描仪通过所述固定架固定。
  8. 如权利要求1所述的智能装配控制***，其特征在于，所述上位机为计算机，用于显示移动机器人的实时状态，包括移动机器人在导航过程中的位置信息显示、目标的远程设定；
    所述上位机还用于控制五自由度电动滑台的轨迹规划；
    所述上位机还用于接收线激光扫描仪传输的三维点云数据并处理，得到零件合格或不合格的检测结果，将检测结果传输到第一机械臂；
    所述上位机还用于接收红外线传感器的反馈信息，反馈五自由度电动滑台的运行状况以及所在位置；
    所述上位机还用于处理所述第一深度学习相机拍摄的照片，提取点位信息，将处理后的信息发送至所述第一机械臂。
  9. 如权利要求1所述的智能装配控制***，其特征在于，所述手眼标 定方法为通过Tsai-Lenz算法来对所述第一机械臂和所述第一深度学习相机进行手眼标定，让所述第一机械臂的末端执行器固定着标定板，并将标定板保持在第一深度学习相机的画面之中，第一深度学习相机拍摄标定板采集一系列图片，并与此同时记录第一机械臂的位姿信息，将其一一对应，通过视觉信息与第一机械臂位姿间的对应关系对第一深度学习相机与第一机械臂空间关系进行求解。
  10. 如权利要求1所述的智能装配控制***，其特征在于，由移动机器人的控制***提供里程计信息，当第二机械臂的控制***接收到之后，先对里程计的数据进行坐标变换，转化为第二机械臂的底座坐标系的位移量，再根据待测工件所能提供的确定的末端位姿和第二机械臂底座的位移量，得到第二机械臂对应更新后得等效规划目标，得到一个更新的末端位姿；
    通过第二机械臂的逆运动学求解，得到细化到各个关节的角度控制目标，最后根据PID算法对关节角度进行控制。
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