CN109318228B - Desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system - Google Patents
Desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system Download PDFInfo
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Abstract
The invention discloses a desktop-level rapid control prototype experimental system for a six-degree-of-freedom mechanical arm, which comprises the six-degree-of-freedom mechanical arm, a rapid control prototype controller and a main control computer, wherein a software platform of the main control computer comprises the following functional modules: the device comprises a human-computer interaction interface module, a dongle module, an experiment management module, a camera module, an image processing module, a starting disc configuration module, a variable management module, an algorithm design module, a waveform display module and a system log module. The desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system has high universality, compatibility and openness.
Description
Technical Field
The invention relates to the technical field of automatic control, in particular to a desktop-level rapid control prototype experiment system for a six-degree-of-freedom mechanical arm.
Background
The german hannover industry exposition of 2013 promoted the fourth industrial revolution mainly based on artificial intelligence, clean energy, robotics, quantum information technology, virtual reality and biotechnology. From now on, in China, robotics has become an object of constant pursuit in the field of advanced manufacturing. Due to subjective judgment and physical conditions of workers, the quality of products is poor, the sizes are unqualified, and the assembly progress of subsequent products is tired. In order to reduce labor cost, shorten product manufacturing time and improve product quality and consistency, a mechanical arm technology is used as a core part of a robot technology, and replaces repeated work such as material handling, product processing, equipment assembly and the like with accurate actions, and the application range of the mechanical arm technology is gradually covered in the fields of ground excavation, sea-bottom exploration, space exploration and the like.
Because the industrial mechanical arm is huge in size, is applied to repeated continuous operation, is high in danger, expensive in physical equipment, has the risk of causing equipment damage, is high in power consumption, and is inconvenient for carrying out field control experiments in a laboratory. Because each application field has higher specification to the control of the removal precision and the stability of arm, guarantee the precision of arm steady operation and operation, become the important problem that needs to solve at present urgently. Therefore, experts in domestic and foreign fields provide a plurality of control strategies for advanced control on the track of the research mechanical arm, but most of the control strategies are verified through mathematical simulation, the confidence coefficient of the experimental effect is low, too much time is spent on achieving the target through compiling the control algorithm through hardware, and the algorithm research progress is delayed. The rapid control prototype system can solve the problems, but the rapid control prototype system on the market is expensive, and foreign famous brands are sold only for colleges and universities, which is not beneficial to personal purchasing research. To realize accurate grabbing of a target object, the mechanical arm is required to accurately sense the pose of the target object besides realizing accurate control of the mechanical arm, and the object positioning is realized by adopting visual positioning at present, but a visual algorithm verification system is not designed for the existing mechanical arm control platform so as to improve the grabbing precision of the mechanical arm.
In summary, the problems of the existing six-degree-of-freedom mechanical arm experimental system mainly include:
1. for the verification of the control algorithm, the control system based on the mathematical model is verified, and the confidence coefficient is not high. The control algorithm is loaded on an actual microprocessing unit (MCU), an external drive circuit is called, a mechanical arm is controlled, a whole set of bottom layer drive codes need to be compiled, and an upper computer for collecting data needs to be designed. Therefore, a research and development person is required to be not only proficient in the development of the underlying driver codes, but also familiar with the design of desktop software, and the research and development period of the control system is greatly delayed.
2. Due to technical monopoly and product protection, the rapid control prototype system is high in foreign purchasing price, purchasing channels are only limited to education of colleges and universities, private enterprise companies cannot purchase the rapid control prototype system, and after-sale technical support is difficult to follow. The design of a rapid control prototype system by domestic companies is mostly biased to the automotive electronics field and motor control, and desktop-level mechanical arm control is not involved, so that a desktop-level mechanical arm implementation system based on rapid control prototypes is urgently needed to be provided for college and university local students or researchers to carry out experimental research.
3. The existing mechanical arm control platform does not relate to mechanical arm platform visual positioning algorithm verification so as to improve mechanical arm grabbing precision.
The existing industrial mechanical arms are different in structure, and a control system cannot well integrate the computer technology and the advanced control technology. Therefore, the development of a desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system with good universality, high confidence coefficient and high cost performance by utilizing the latest design concept and technology is of great research significance and practical application value.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the art described above. Therefore, the invention aims to provide a desktop-level six-degree-of-freedom mechanical arm rapid control prototype experiment system which has high universality, compatibility and openness.
In order to achieve the purpose, the invention provides a desktop-level rapid control prototype experimental system for a six-degree-of-freedom mechanical arm, which comprises the six-degree-of-freedom mechanical arm, a rapid control prototype controller and a main control computer, wherein a software platform of the main control computer comprises the following functional modules: the human-computer interaction interface module is used for designing a visual interface for each other functional module; the dongle module realizes encryption protection through timing detection; the system comprises an experiment management module, a data processing module and a data processing module, wherein the experiment management module is used for creating a project management file, creating a mechanical arm control algorithm file under the project, providing functions of adding, deleting, modifying, importing and exporting the file, and further has the functions of connecting, loading an algorithm program and running control; the camera module is used for connecting the camera according to the input camera connection configuration information and carrying out testing; the image processing module is used for calling the camera to shoot a target picture by selecting a to-be-called calculation engine Matlab or Python, and designing a deep learning algorithm to calculate the pose of a target object; the starting disc configuration module is used for providing a real-time calculation engine for the rapid control prototype controller and configuring a corresponding IP address and a corresponding equipment port number; the variable management module is used for providing functions of parameter adjustment, real-time display and management of running state variables, and realizing the algorithm output value of the image processing module and modifying the algorithm input value in the rapid control prototype controller; the system comprises an algorithm design module, a data processing module and a data processing module, wherein the algorithm design module is used for calling a Simulink algorithm design environment, editing and compiling a control algorithm file, configuring a Matlab/Simulink running environment and customizing commands of an algorithm library installation and compiling the control algorithm file; the waveform display module is used for storing the variable group selected from the variable management bar into a data trend display window, acquiring data once every preset time and displaying a waveform so as to allow a user to visually analyze and control the algorithm effect; and the system log module is used for recording user operation information and saving the user operation information to a system file by a date name.
According to the desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system, the desktop-level six-degree-of-freedom mechanical arm and a rapid control prototype are combined, the research and development cost is reduced, the algorithm debugging time is shortened, the visual positioning function is added, a deep learning algorithm can be effectively applied to a mechanical arm grabbing experiment, the system has high universality, compatibility and openness, is very suitable for experiment teaching of a student and a researcher of related automatic subjects and subject research of an algorithm researcher, and has very wide development prospect.
In addition, the experiment system for the desktop-level six-degree-of-freedom mechanical arm rapid control prototype provided by the embodiment of the invention can also have the following additional technical characteristics:
the desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system further comprises a camera, a power supply, a digital steering engine and a grid white board.
The camera is Kinect motion camera, power supply is direct current 6V power supply, the mesh blank precision is 5 mm.
The rapid control prototype controller is composed of an industrial personal computer mainboard with a PCI slot, a 2G internal memory, a 1G mobile storage disk, a direct current stabilized voltage power supply and a data acquisition card with multiple functions, wherein the 1G mobile storage disk is used as a starting disk for storing a real-time operation engine, when the rapid control prototype controller is started, a CPU (central processing unit) firstly reads and writes a program in the mobile disk into the internal memory, waits for burning of an algorithm application program, designs a driving module for the data acquisition card and provides a device driving script for a code generator, so that when the rapid control prototype controller operates, the data acquisition card is driven by the device driving script, and external environment information is accessed.
The desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system is used for carrying out verification experiments of a mechanical arm track control algorithm on a control loop layer, and the verification experiment process of the mechanical arm track control algorithm is as follows: step 1: checking whether the wiring of the mechanical arm is normal, inserting a dongle, opening a desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system, entering a starting disc configuration label window, configuring an IP (Internet protocol) and a port of a rapid control prototype controller, inserting the starting disc into the rapid control prototype controller, connecting a network cable, and electrifying; step 2: setting the IP of the main control computer and the IP of the rapid control prototype controller in the same network segment, checking whether the connection is normal or not by testing a connection key, and checking whether the network connection and the IP configuration are correct or not if the connection is abnormal; and step 3: entering an experiment management label window, newly building a control algorithm project, opening a Simulink model file, designing a mechanical arm track control algorithm, and verifying algorithm feasibility through a mathematical model; and 4, step 4: on the premise of successful mathematical simulation, the mathematical model is changed into a corresponding driving module, a low-pass filtering module is added on the angle sampling module to filter signal interference, and a correction deviation module is added for a measurement signal of each joint, so that errors generated in the assembly aspect of the mechanical arm can be corrected conveniently; and 5: the designed and modified mechanical arm track control algorithm is called, a real-time controller is connected, and the algorithm is compiled and loaded; step 6: entering a variable management note window, adding a pose variable, an algorithm parameter and a concerned running state quantity to a label management column from a signal/parameter browser, adding the concerned running state variable to a running observation window, running a control algorithm, judging whether a gripper at the tail end of the mechanical arm reaches a target pose through a grid white board, and repeatedly adjusting the algorithm parameter to enable the control algorithm to achieve an expected effect.
The desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system is used for carrying out a target object grabbing experiment based on depth vision on an image processing layer, and the target object grabbing experiment process based on the depth vision is as follows: step 1: inputting a designed mechanical arm track control algorithm and adjusted parameters, calling a camera to obtain pictures, designing target object grabbing position detection based on deep learning through an image processing module, and performing a target object grabbing experiment based on deep vision; step 2: designing a target detection algorithm based on deep learning, and recording the position and classification of a target object; and step 3: according to the classification detection result, a mechanical arm tail end pose algorithm based on deep learning is designed, and the obtained position and the posture of the mechanical arm tail end gripper are transmitted to a rapid control prototype controller, so that the mechanical arm can accurately grip a target; and 4, step 4: and analyzing the experimental data, and adjusting an algorithm to enable the mechanical arm to accurately grab the target object, so that the experiment is finished.
Drawings
Fig. 1 is a frame diagram of a desktop-level six-dof robotic arm rapid control prototype experimental system according to an embodiment of the present invention;
FIG. 2 is a hardware block diagram of a fast control prototype controller according to one embodiment of the present invention;
FIG. 3 is a functional module distribution diagram of a software platform according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating communication between functional modules of a software platform according to one embodiment of the present invention;
fig. 5 is a structure and a flowchart of a desktop-level six-dof robotic arm rapid control prototype experimental system according to an embodiment of the present invention;
fig. 6 is an experimental flow diagram of a desktop-level six-dof robotic arm rapid control prototype experimental system according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a verification experiment process of a robot arm trajectory control algorithm according to an embodiment of the present invention;
fig. 8 is a schematic diagram of a process of an objective grabbing experiment based on depth vision according to an embodiment of the invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The following describes a desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system according to an embodiment of the present invention with reference to the accompanying drawings.
As shown in fig. 1, the desktop-level six-degree-of-freedom robot arm rapid control prototype experimental system according to the embodiment of the present invention includes a six-degree-of-freedom robot arm 1, a rapid control prototype controller 2, and a main control computer 3.
Further, as shown in fig. 1, the table-top-level six-degree-of-freedom mechanical arm rapid control prototype experimental system may further include a camera 4, a power supply 5, a digital steering engine 6, and a grid whiteboard 7. In one embodiment of the invention, the camera is a Kinect motion camera, the power supply is a direct current 6V power supply, and the precision of the grid whiteboard is 5 mm.
In one embodiment of the invention, the rapid control prototype controller is composed of an industrial personal computer mainboard with a PCI slot, a 2G internal memory, a 1G mobile storage disk, a direct current stabilized voltage power supply and a multifunctional data acquisition card, wherein the 1G mobile storage disk is used as a starting disk for storing a real-time operation engine, when the rapid control prototype controller is started, a CPU firstly reads and writes a program in the mobile disk into the internal memory, waits for burning of an algorithm application program, designs a driving module for the data acquisition card, and provides a device driving script for a code generator, so that when the rapid control prototype controller operates, the data acquisition card is driven by the device driving script, and external environment information is accessed.
In an embodiment of the present invention, a hardware structure of the rapid control prototype controller is as shown in fig. 2, a real-time operation engine may be placed in a start-up disk, an industrial control motherboard is configured as a mobile storage to start, and a CPU reads a real-time operation engine code from the mobile storage and places the real-time operation engine code in an internal memory, so that the rapid control prototype controller operates in a DOS system equipped with a simulink core to provide a solution engine for a robot arm control algorithm. The data acquisition card adopts the porphyrized PCI1716 and the PCI 1780U. The Tuhua PCI1716 has 16 paths of single-end or 8 paths of differential 16-bit high-precision AD conversion, 16 paths of digital input/output ports and 2 paths of 16-bit high-precision DA conversion, is enough to sample the rotation angle of the digital steering engine on each joint of the six-degree-of-freedom mechanical arm, and the sampling voltage range is set to be-5V- + 5V. The pulse generating module with 20ms period and 0.5-2.5 ms pulse width is designed for the time counting/counting card by using the Wharton PCI 178U. Taking PCI1780U as an example, the function configuration steps of the board card are as follows: the 10MHz clock source is converted into 1MHz pulse through frequency division for periodic counting, the count value of 20m period is 20000, the high level count is 500-2500, and the count value of the level is calculated according to the joint angle input by the corresponding channel of the formula module
(ChighHigh level count value, theta is digital steering engine rotation angle), the PCI1780U is configured in a J-type wave signal generator mode, the rapid control prototype controller calculates the rotation angle of each joint steering engine every other operation period, and 20000-C is written into Hold and Load registers of the PCI1780U respectivelyhighAnd ChighAnd when the C-MEXFanction is used for compiling a driving file of the data acquisition card, calling a related PCI communication interface access function provided by Simulink, and accessing a register address of the data acquisition card, so that the controller can control the data acquisition card, and further the desktop-level six-degree-of-freedom mechanical arm can be controlled. To realize data acquisitionThe card can be provided with a port, an m script is used, a human-computer interaction interface (GUI) is designed for each driving module of the data acquisition card, for example, an AD conversion driving module of a PCI1716, and two drop-down boxes are designed for selection respectively: the single-end/differential AD conversion and the AD voltage conversion range (plus or minus 10V, plus or minus 5V, plus or minus 2.5V, plus or minus 1.25V, plus or minus 0.625V) are set, and when one end of the single-end/differential AD conversion and the AD voltage conversion range is poor, a control pin can be changed through a GUI (graphical user interface), debugging is carried out again, and the debugging progress is not delayed.
The hardware parameters of the rapid control prototype controller according to the embodiment of the present invention are shown in table 1:
TABLE 1
In an embodiment of the present invention, as shown in fig. 3, the software platform of the host computer 3 mainly includes the following functional modules: the device comprises a human-computer interaction interface module, a dongle module, an experiment management module, a camera module, an image processing module, a starting disc configuration module, a variable management module, an algorithm design module, a waveform display module and a system log module.
As shown in fig. 3, the human-computer interaction interface module, the dongle module, the experiment management module, the camera module, the image processing module, the startup disk configuration module, the variable management module, the waveform display module, and the system log module are located in a management layer, and the algorithm design module is located in a control loop layer. The functions of the respective functional modules are described in detail below with reference to fig. 3 and 4.
The man-machine interaction interface module can design a visual interface for other functional modules, decorate and manage the functional modules in a label small window mode.
The dongle module can realize encryption protection through timing detection, specifically, a timer task can be started singly, the dongle is logged in every 10s, a key is read for comparison, if the dongle fails, the dongle module immediately exits from the software system, and the software system is prevented from being illegally called to a certain extent.
The experiment management module can be used for creating project management files, creating mechanical arm control algorithm files under the projects, providing functions of adding, deleting, modifying, importing and exporting the files, and further has functions of connecting, loading algorithm programs and running control. Specifically, a static class may be designed, for example, to create a project, and static methods createProject and createAlg are called to create an instance of the project and its arm control algorithm file, respectively, where the project class is composed of a String type project name, a project path, and a List < Alg > List class, and generates a. Alg is an algorithm class, which is composed of id of int type and algorithm name of String type, and the algorithm file is located under the folder corresponding to the algorithm file name under the current project file. Other operations of the experimental project are similar to the implementation mode, the functions of adding, deleting, changing, leading in and leading out are realized, and besides the functions, the functions also integrate controller connection, algorithm compiling and alarming control, algorithm downloading and controller operation commands.
The camera module can be connected with the camera according to the input camera connection configuration information and tests. Specifically, when the experiment enters a target object grabbing experiment based on the depth vision, the camera module is called, the camera is controlled to shoot images by calling the dynamic link library of the Kinect, and the images are captured and stored under the current algorithm folder for being analyzed by a rear image processing module.
The image processing module can be used for calling a camera to shoot a target picture by selecting a calculation engine Matlab or Python to be called, and designing a deep learning algorithm to calculate the pose (x, y, z) of the target object. Specifically, a Matlab engine and a Python engine can be packaged by using a static factory class, an editing interface is designed for a control algorithm, the module identifies a suffix name of an algorithm script, judges which calculation engine is used, carries out calling calculation, and transmits a result variable to a variable management column for parameter modification.
The boot disk configuration module may be used to provide a real-time computing engine for the fast control prototype controller and configure the corresponding IP address and device port number. Specifically, a static class can be used for setting an IP address and a communication port number of a rapid control prototype controller, storing the IP address and the communication port number into a system file by a controllfg.
The variable management module can be used for providing functions of parameter adjustment, real-time display and management of running state variables, and realizing the algorithm output value of the image processing module and the algorithm input value in the modified rapid control prototype controller. In particular, a VariantInfo class may be defined, consisting of the String type variable name varName, the variable value, the variable path varPath. Selecting variables from a 'parameter/signal browser' to be added to a variable management bar, collecting all variable parameters in the 'parameter/signal browser' by using a communication module when a program runs, reading corresponding values from a variable list by the variable management bar every 100ms, displaying the values on the variable management bar, selecting state variables to be displayed in a check box in the variable management bar, adding the state variables to a waveform display module, creating a database for the management variables, and storing the database.
The algorithm design module can be used for calling a Simulink algorithm design environment, editing and compiling a control algorithm file, configuring a Matlab/Simulink running environment (such as an algorithm execution period, an algorithm solver, a fixed-step solver and the like), and customizing an algorithm library to install and compile commands of the control algorithm file. The system comprises an algorithm library, a signal input module, an initialization configuration block, a mechanical arm track control algorithm block, an equipment driving block and the like, wherein the algorithm library provides the signal input block, the initialization configuration block, the mechanical arm track control algorithm block, the equipment driving block and the like, a user changes input information through the signal input module, the initialization configuration block is used for setting initial and end poses of a mechanical arm, an algorithm is designed in the mechanical arm track control algorithm block, and the design of a mechanical arm track control algorithm.
The waveform display module can be used for storing the variable group selected from the variable management bar into a data trend display window, acquiring data once every preset time, such as 200ms, and displaying a waveform, so that a user can visually analyze and control the algorithm effect. The waveform display module can call a third-party waveform control, the collected operation data is recorded in a variable list, and the data list is emptied every 2000 points.
And the system log module is used for recording user operation information and saving the user operation information to a system file by a date name. The method comprises the steps of recording the steps of using each function module by a user through the module, and presenting the latest calling information in a software state information column. And after the system quits, automatically saving the operation information of the current day under a system folder by taking the date plus.
In an embodiment of the present invention, referring to fig. 5 and 6, the desktop-level six-degree-of-freedom robot arm rapid control prototype experimental system according to the embodiment of the present invention may be implemented by a control engineer and an algorithm researcher, and the whole experiment may be completed in two stages, where the first stage is a verification experiment of a robot arm trajectory control algorithm performed in a control loop layer, and the second stage is a target object capture experiment performed in an image processing layer based on depth vision.
The experimental procedure of the first stage is described below with reference to fig. 5, 6 and 7.
The verification experiment process of the mechanical arm track control algorithm in the first stage is as follows:
step 1: checking whether the wiring of the mechanical arm is normal, inserting a dongle, opening a desktop-level six-degree-of-freedom mechanical arm rapid control prototype experiment system, entering a starting disc configuration label window, configuring an IP (Internet protocol) and a port of a rapid control prototype controller, inserting the rapid control prototype controller into the starting disc, connecting a network cable, electrifying, and finishing the real-time computation engine carrying.
Step 2: setting the main control computer IP and the rapid control prototype controller IP in the same network segment, checking whether the connection is normal or not by testing the connection key, and checking whether the network connection and the IP configuration are correct or not if the connection is abnormal.
And step 3: entering an experiment management label window, newly building a control algorithm project, opening a Simulink model file, designing a mechanical arm track control algorithm, and verifying algorithm feasibility through a mathematical model. After hardware connection is carried out and an experiment management window is entered, a blank engineering project file is newly established, a Simulink algorithm file is newly established under the project file menu, a six-degree-of-freedom mechanical arm track control algorithm is established under the file, a six-degree-of-freedom mechanical arm mathematical model is led in from a driving library matched with the system, the model utilizes a solid works integrated 3D visualization module, the control effect can be visually observed, the mechanical arm track planning algorithm is preliminarily adjusted through mathematical simulation, and the rationality of the algorithm is proved from the theoretical simulation level.
And 4, step 4: on the premise of successful mathematical simulation, the mathematical model is changed into a corresponding driving module, a low-pass filtering module is added on the angle sampling module to filter signal interference, and a correction deviation module is added for a measurement signal of each joint, so that errors generated in the assembly aspect of the mechanical arm can be corrected conveniently.
And 5: and (4) connecting a real-time controller by calling the designed and modified mechanical arm track control algorithm, compiling and loading the algorithm. The mathematical model of the six-degree-of-freedom mechanical arm can be replaced by a corresponding hardware driving module, a C source code is generated by using a code generation technology, and is compiled into an executable binary file by using a VC + + compiler, connected and controlled, and loaded into a real-time controller.
Step 6: entering a variable management note window, adding a pose variable, an algorithm parameter and a concerned running state quantity to a label management column from a signal/parameter browser, adding the concerned running state variable to a running observation window, running a control algorithm, judging whether a gripper at the tail end of the mechanical arm reaches a target pose through a grid white board, and repeatedly adjusting the algorithm parameter to enable the control algorithm to achieve an expected effect.
After the software loads the executable algorithm file, the software enters a variable management window, a 'signal/parameter browser' sub-window pops up on the right side, the state quantity to be observed and the adjusting parameter are selected from the sub-window, a popup menu is clicked to the right, the state quantity to be observed and the adjusting parameter are selected and added to a variable management column, a variable renaming window pops up, the variable is renamed, the adjusting parameter is selected, the variable is clicked to the right for selection and modification, and a new parameter is input into a popped up modified parameter window for modification. When the image processing module is enabled, the function is disabled, the menu is grayed out, a check box exists in the first column of the variable management column, the menu can be selected by right clicking, and the menu is popped up and added to the database and the oscillogram. And repeatedly changing the input coordinate parameters, observing the operation result, and adjusting the algorithm parameters, so that the tail end of the mechanical arm can quickly and accurately achieve the arrival of the target point. And selecting all the adjusting variables, selectively exporting the adjusting variables in a right-click menu, and storing the algorithm parameters to the corresponding control algorithm path to complete the first-stage experiment.
The experimental procedure of the second stage is described below with reference to fig. 5, 6 and 8.
The second stage of the target object grabbing experiment process based on the depth vision is as follows:
step 1: inputting a designed mechanical arm track control algorithm and adjusted parameters, calling a camera to obtain pictures, designing target object grabbing position detection based on deep learning through an image processing module, and carrying out a target object grabbing experiment based on deep vision. And on the basis of the completion of the first stage, connecting the camera, entering a camera window to shoot pictures, storing the pictures under the current algorithm path, and providing the pictures for the image processing module to process.
Step 2: and designing a target detection algorithm based on deep learning, and recording the position and classification of the target.
And step 3: and designing a mechanical arm tail end pose algorithm based on deep learning according to the classification detection result, and transmitting the obtained position and the posture of the mechanical arm tail end gripper to a rapid control prototype controller to enable the mechanical arm to accurately grip the target.
And 4, step 4: and analyzing the experimental data to achieve the design target of the user algorithm, and ending the experiment.
The method comprises the steps of establishing a new algorithm for positioning the grabbed target object, storing a corresponding operation script file, reading an algorithm script input parameter and a target object picture by an image processing module, calling a corresponding calculation engine, calculating to obtain a target pose (an output quantity name exists in a variable management column), modifying a pose parameter of a mechanical arm track control algorithm in a control loop layer by a variable management module, and realizing a visual grabbing experiment of the mechanical arm. And if the experimental effect meets the design requirement, the design of the visual detection and positioning algorithm is correct.
In conclusion, according to the desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system provided by the embodiment of the invention, the desktop-level six-degree-of-freedom mechanical arm and a rapid control prototype are combined, the research and development cost is reduced, the algorithm debugging time is shortened, the visual positioning function is added, a deep learning algorithm can be effectively applied to a mechanical arm grabbing experiment, the system has high universality, compatibility and openness, is very suitable for experiment teaching of a student and a researcher who automate related disciplines and subject research of an algorithm researcher, and has a very wide development prospect.
In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise. In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the present invention, unless otherwise expressly stated or limited, the first feature "on" or "under" the second feature may be directly contacting the first and second features or indirectly contacting the first and second features through an intermediate. Also, a first feature "on," "over," and "above" a second feature may be directly or diagonally above the second feature, or may simply indicate that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature may be directly under or obliquely under the first feature, or may simply mean that the first feature is at a lesser elevation than the second feature.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (5)
1. A desktop-level rapid control prototype experimental system for a six-degree-of-freedom mechanical arm is characterized by comprising the six-degree-of-freedom mechanical arm, a rapid control prototype controller and a main control computer, wherein the rapid control prototype controller is composed of an industrial control computer main board with a PCI slot, a 2G memory, a 1G mobile storage disc, a direct current stabilized power supply and a data acquisition card with multiple functions, the 1G mobile storage disc is used as a starting disc for storing a real-time operation engine, when the rapid control prototype controller is started, a CPU (central processing unit) firstly reads and writes a program in the mobile disc into the memory, waits for an algorithm application program to be burnt, designs a driving module for the data acquisition card, and provides an equipment driving script for a code generator, so that the rapid control prototype controller can drive the data acquisition card through the equipment driving script and access external environment information when running;
the software platform of the main control computer comprises the following functional modules:
the human-computer interaction interface module is used for designing a visual interface for each other functional module;
the dongle module realizes encryption protection through timing detection;
the system comprises an experiment management module, a data processing module and a data processing module, wherein the experiment management module is used for creating a project management file, creating a mechanical arm control algorithm file under the project, providing functions of adding, deleting, modifying, importing and exporting the file, and further has the functions of connecting, loading an algorithm program and running control;
the camera module is used for connecting the camera according to the input camera connection configuration information and carrying out testing;
the image processing module is used for calling the camera to shoot a target picture by selecting a to-be-called calculation engine Matlab or Python, and designing a deep learning algorithm to calculate the pose of a target object;
the starting disc configuration module is used for providing a real-time calculation engine for the rapid control prototype controller and configuring a corresponding IP address and a corresponding equipment port number;
the variable management module is used for providing functions of parameter adjustment, real-time display and management of running state variables, and realizing the algorithm output value of the image processing module and modifying the algorithm input value in the rapid control prototype controller;
the system comprises an algorithm design module, a data processing module and a data processing module, wherein the algorithm design module is used for calling a Simulink algorithm design environment, editing and compiling a control algorithm file, configuring a Matlab/Simulink running environment and customizing commands of an algorithm library installation and compiling the control algorithm file;
the waveform display module is used for storing the variable group selected from the variable management bar into a data trend display window, acquiring data once every preset time and displaying a waveform so as to allow a user to visually analyze and control the algorithm effect;
and the system log module is used for recording user operation information and saving the user operation information to a system file by a date name.
2. The desktop-level rapid control prototype experimental system of a six-degree-of-freedom mechanical arm according to claim 1, further comprising a camera, a power supply, a digital steering engine and a grid whiteboard.
3. The desktop-level rapid control prototype experimental system of six-degree-of-freedom mechanical arm according to claim 2, wherein the camera is a Kinect motion camera, the power supply is a direct current 6V power supply, and the grid whiteboard precision is 5 mm.
4. The desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system according to claim 3, wherein the desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system is used for performing verification experiments of a mechanical arm trajectory control algorithm on a control loop layer, and the verification experiment processes of the mechanical arm trajectory control algorithm are as follows:
step 1: checking whether the wiring of the mechanical arm is normal, inserting a dongle, opening a desktop-level six-degree-of-freedom mechanical arm rapid control prototype experimental system, entering a starting disc configuration label window, configuring an IP (Internet protocol) and a port of a rapid control prototype controller, inserting the starting disc into the rapid control prototype controller, connecting a network cable, and electrifying;
step 2: setting the IP of the main control computer and the IP of the rapid control prototype controller in the same network segment, checking whether the connection is normal or not by testing a connection key, and checking whether the network connection and the IP configuration are correct or not if the connection is abnormal;
and step 3: entering an experiment management label window, newly building a control algorithm project, opening a Simulink model file, designing a mechanical arm track control algorithm, and verifying algorithm feasibility through a mathematical model;
and 4, step 4: on the premise of successful mathematical simulation, the mathematical model is changed into a corresponding driving module, a low-pass filtering module is added on the angle sampling module to filter signal interference, and a correction deviation module is added for a measurement signal of each joint, so that errors generated in the assembly aspect of the mechanical arm can be corrected conveniently;
and 5: the designed and modified mechanical arm track control algorithm is called, a real-time controller is connected, and the algorithm is compiled and loaded;
step 6: entering a variable management note window, adding a pose variable, an algorithm parameter and a concerned running state quantity to a label management column from a signal/parameter browser, adding the concerned running state variable to a running observation window, running a control algorithm, judging whether a gripper at the tail end of the mechanical arm reaches a target pose through a grid white board, and repeatedly adjusting the algorithm parameter to enable the control algorithm to achieve an expected effect.
5. The desktop-level six-degree-of-freedom robotic arm rapid control prototype experimental system according to claim 4, wherein the desktop-level six-degree-of-freedom robotic arm rapid control prototype experimental system is used for performing the depth vision-based target object grabbing experiment in the image processing layer, and the depth vision-based target object grabbing experiment process is as follows:
step 1: inputting a designed mechanical arm track control algorithm and adjusted parameters, calling a camera to obtain pictures, designing target object grabbing position detection based on deep learning through an image processing module, and performing a target object grabbing experiment based on deep vision;
step 2: designing a target detection algorithm based on deep learning, and recording the position and classification of a target object;
and step 3: according to the classification detection result, a mechanical arm tail end pose algorithm based on deep learning is designed, and the obtained position and the posture of the mechanical arm tail end clamping device are transmitted to a rapid control prototype controller, so that the mechanical arm can accurately clamp the target;
and 4, step 4: and analyzing the experimental data to achieve the design target of the user algorithm, and ending the experiment.
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| CN112338903A (en) * | 2020-10-21 | 2021-02-09 | 西安工程大学 | Mechanical arm control method based on model design |
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