Intelligent path planning device and method for industrial mechanical arm

A path planning and industrial machinery technology, applied in the direction of manipulators, program-controlled manipulators, manufacturing tools, etc., can solve the problems of reduced industrial production efficiency, affecting processing accuracy, efficiency, and defective products, so as to improve processing quality and efficiency, Guarantee the effect of processing quality

Inactive Publication Date: 2021-04-13
HUNAN INT ECONOMICS UNIV +1
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Problems solved by technology

However, the result of manual debugging is the reduction of industrial production efficiency and motion accuracy, and even the superposition of pr...
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Abstract

The invention relates to the field of industrial mechanical arms, in particular to an intelligent path planning device and method for an industrial mechanical arm. The device comprises a machined workpiece, a visual system, an intelligent control system, a mechanical arm and a workstation. The visual system comprises a visual module, an A/D converter and a rapid calibration module. The intelligent control system comprises an image learning module, a path planning module, a coordinate conversion module, an inverse kinematics module and a motor control module. The workstation module comprises a work server and a displayer. The mechanical arm module comprises a base, N joints, N motors matched with the joints and a machining device. The visual system is configured to collect surface information of the machined workpiece through the visual module, form point cloud from profile three-dimensional information of the machined workpiece through a three-dimensional visual technology and then form three-dimensional profile data. The intelligent control system is configured to control the action of the mechanical arm based on the information collected by the visual system. The work server is configured to be used for mechanical arm parameter adjustment, mechanical arm control platform software is arranged in the work server and used for controlling a mechanical platform, and the displayer is used for displaying controllable parameters. According to the industrial mechanical arm, the work automation and the machining efficiency and precision of an existing robot are improved, and the intelligence of mechanical arm path planning is achieved.

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  • Intelligent path planning device and method for industrial mechanical arm
  • Intelligent path planning device and method for industrial mechanical arm

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Example Embodiment

[0035]The technical solutions of the present invention will be further described below with reference to the accompanying drawings.
[0036]The drawings are for exemplary description, which is merely a schematic diagram, rather than the experiment, and is not to be understood to be in this patent; in order to better illustrate the embodiments of the invention, there will be omitted, Enlarge or shrink does not represent the size of the actual product; some well-known structures and descriptions thereof may be understood in the drawings in the drawings.
[0037]The present invention specifically uses the following technical solutions to achieve the above technique:
[0038]Such asfigure 1 As shown, an industrial robotic arm intelligent path planning device includes processing workpieces, visual systems, intelligent control systems, robotic arms, and workstations.
[0039]The visual system includes a visual module, a / d converter, and a fast calibration module;
[0040]The intelligent control system includes an image learning module, a path planning module, a coordinate conversion module, a reverse kinematic module, a motor control module,
[0041]The workstation includes a work server and a display;
[0042]The robot arm includes a base, a n type, a n motor, a processed device, and a processing device.
[0043]The visual system is configured to collect the surface information of the workpiece by the visual module, forming a dot cloud through three-dimensional visual techniques, and then forms three-dimensional surface data, and point cloud data refers to a three-dimensional coordinate system. A set of vector in a set of vector, these vectors are typically represented in the form of x, y, z, and generally mainly used to represent an outer surface shape of an object; specifically, the three-dimensional type by the A / D converter The surface data is transmitted to the fast calibration module, the fast calibration module compares the three-dimensional surface data with a pre-stored machining model profile data and converts the three-dimensional surface data with the pre-stored machining model profile data. The difference is converted to the sample set of pretreated;
[0044]The intelligent control system is configured to control the operation of the robot arm based on the information acquired by the visual system, in particular, the output of the fast calibration module connects the image learning module input, and inputs the sample set as input to The image learning module is judged by the image recognition model built by the image learning module; the output of the image learning module connects the input of the path planning module, the path planning module based on The information of the above judgment forms a new motion path, and outputs the new motion path to the coordinate conversion module, the coordinate conversion module compares the new motion path with the last machined motion path, and calculates The compensation value of the processing curve is transmitted to the inverse kinematic module, forming a joint motion compensation amount; the joint motion compensation amount is transmitted to the motor control module, and a compensation control signal is formed by the motor control module. ;
[0045]The working server is configured for robotic argument adjustment, its built-in robot arm control platform software, is used to control the mechanical platform, and the display is used to display a controllable parameter;
[0046]The robot arm module is configured to perform a robotic arm motion path, the base placed on the base, and the N motor corresponds to one or one, and the N motor is all Connecting to the output of the motor control module, the electromagnetic signal emitted by the motor control module controls the motion of the motor and the joint, and changes in the torque, the rotational speed, and the angle of rotation are achieved.
[0047]In some embodiments, the rapid calibration module is calibrated with a C ++ language, and the specific calibration formula is: σL = σL1-L2Where L1For pre-stored processing spline functions, L2Processing spline functions for actual processing point cloud data.
[0048]In some embodiments, the image learning module has a built-in neural network to judge the sample set, and the image learning module develops a language of Python.
[0049]In some embodiments, the processing curve compensation control signal calculation formula is: ΔJ = j-1ΣL1-L2Where △ j is a compensation signal, J-1For the Jacques inverse matrix of coordinates and joint coordinates.
[0050]In some embodiments, the number N n of the motor and joint is 6, the compensation control signal control rule is: the joint 1 is a longitudinal compensation signal, and the joint 2 is a transverse compensation signal, and the joint 3 is a rotary compensation signal, joint 4 To the joint 6 is the compensation location of the end path.
[0051]In some embodiments, the machining workpiece unit is a metal piece or a non-metal part, such as alloy, iron, copper, plastic, etc., the motor is an AC brushless servant motor; the arm electromagnetic control signal Both step pulse signals; the visual module is a CCD or an industrial rapid camera; the processing apparatus is preferably a tool.
[0052]In some embodiments, such as with the wear of the tool, the tool size is reduced, the pattern of the workpiece increases or reduces, and the change in this size can cause the part to fail to avoid or decrease This dimension varies, in the present invention, the industrial rapid phase chance of the visual system will take photos of each workpiece, the photographs are transmitted to the image learning module, compare the photo decomposition, compare the set reference, in this comparison Based on the difference, the difference between the difference information is converted to the movement of the arm, which is specifically through the motor or other power device to drive the joint action to correct the deviation of this size.
[0053]Such asfigure 2As shown, the present invention also includes a processing method, and the specific scheme is as follows:
[0054]The industrial robotic arm intelligent path planning method includes the following steps:
[0055]Step S1, the image acquisition: take the workpiece processing surface using the CCD camera, convert the image signal to point cloud data, generate real-time three-dimensional surface;
[0056]Step S2, the image calibration: The generated three-dimensional surface is coincident with the machining reference surface of the preset machining model, calculate the difference between the processing spline of the real-time pattern and the preset surface, forming sample data;
[0057]Step S3: Data learning: Sending the sample data to the image learning module, using the RNN depth learning module to train the sample data, output the type surface difference between the image and the input model, and determine the profile Whether the difference exceeds the set threshold, if yes, jump to step S7; if not, jump to step S4;
[0058]Step S4, the path planning: form a motion path corresponding to the sample data, based on the difference between the real-time processing type surface motion path and the preset path, calculates the processing path compensation amount;
[0059]Step S5, inverse motion planning: By the built-in reverse kinematics control algorithm, convert the machining path compensation amount into the motion compensation value of each joint, transmitted to the motor control module;
[0060]Step S6, the motor control: By converting the resulting joint compensation amount into electromagnetic signals, the motor is transmitted to each motor unit, and the motor is controlled to compensate the set path signal;
[0061]Step S7, the control ends.
[0062]Preferably, the number of learning samples of the RNN depth learning algorithm in step S3 is 10000.
[0063]Preferably, the inverse kinematic control algorithm in step S5 is realized by the built-in module in the CAM control platform of the robotic arm; the number of the motor and the joint is 6, the compensation control signal control rule is: joint 1 is a longitudinal compensation signal, the joint 2 is a transverse compensation signal, and the joint 3 is a rotation compensation signal, and the joint 4 to joint 6 is a compensation location of the end path.
[0064]Preferably, the processing curve compensation signal calculation formula is: ΔJ = j-1ΣL1-L2Where △ j is the compensation signal, J-1 is the Jacques inverse matrix of the machining coordinates and joint coordinates.
[0065]Advantageous effects of the present invention: The industrial robot arm is decomposed by automatically collecting the workpiece, and when the processing type surface is decomposed, when the processing type surface and the set reference gap exceeds the threshold, the machining action of the mechanical motor and joints can be controlled. Conducting, do not need manual debugging, so that the quality of processing is guaranteed, greatly improves processing quality and processing efficiency, suitable for high quality processing of various workpieces.
[0066]It is to be declared that the above specific embodiments are merely preferred embodiments of the invention and the techniques used. Those skilled in the art will appreciate that various modifications, equivalents, changes, and the like can also be made to the present invention. However, these transformations should be within the scope of the invention as long as they do not depart from the spirit of the invention. In addition, some of the terms used in the present application and the claims are not limited, just for convenience of description.
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