Virtual practical training system construction method based on robot simulation software

Abstract

The invention provides a virtual training system construction method based on robot simulation software. According to the invention, a virtual practical training model of the robot is established; packaging the robot model to obtain a packaged virtual practical training scene model; performing simulation adjustment and optimization on the packaging virtual practical training model to obtain an optimized packaging virtual practical training model; and establishing a virtual controller based on the model corresponding to the robot, and establishing a data interaction and mapping relationship between the virtual controller and the optimized packaging virtual practical training model to obtain a virtual practical training system. Compared with the prior art, the robot in the virtual practical training system is controlled by operating the virtual demonstrator to carry out demonstration and programming, so that practical training is completed, and students can carry out robot practical training anytime and anywhere and carry out repeated practice aiming at weak knowledge points in this way, so that the practical training efficiency is improved. Therefore, the problems of few practical operation opportunities, high safety risk and disjunction between teaching content and actual work are effectively solved.

Description

Technical Field

[0001] The present invention is applicable to the technical field of robots, and in particular relates to a method for constructing a virtual training system based on robot simulation software. Background Art

[0002] With the rapid development of industrial automation and intelligent manufacturing, industrial robots are gradually becoming key supporting equipment in the manufacturing industry. Therefore, there is a growing demand for professionals who are proficient in robot operation, programming, maintenance and troubleshooting skills. Robot training is a key link in cultivating the practical operation capabilities of future engineers and technicians in the field of automation and robotics. Practical training not only provides a safe environment for trainees to practice and make mistakes without risk, but also ensures that they can master the necessary skills to adapt to the ever-changing technological environment. In addition, practical training also helps to improve trainees' problem-solving ability, teamwork ability and innovative thinking. Through practical training, trainees can better understand the connection between theoretical knowledge and practical applications, thus laying a solid foundation for their careers.

[0003] However, there are many problems with robot practical training at present. On the one hand, due to the high cost of industrial robot equipment, many schools are short of funds, and the practical training equipment cannot meet the requirements of teaching and training, and there are safety risks, resulting in high practical training costs and limited practical opportunities for students, which affects the development of students' professional skills. On the other hand, traditional practical training methods are inefficient, and some practical training content may be too theoretical and out of touch with actual work scenarios, making it difficult for students to apply what they have learned to actual work. In addition, some practical training projects have little correlation with the actual projects of the enterprise, and the knowledge points and skill points are single, making it difficult for students to learn in depth, and their abilities cannot meet the requirements of the company's positions. These problems limit the effectiveness of robot practical training.

[0004] The current robot training teaching has the following problems:

[0005] Insufficient training equipment, high teaching costs and high risks. As industrial robot equipment is expensive, many schools are short of funds, and the training equipment cannot meet the requirements of teaching and training, and there are safety risks, resulting in high training costs, limited practical opportunities for students, and affecting the development of students' professional skills.

[0006] Teaching content is out of touch with reality. Traditional practical training teaching methods are inefficient, and some practical training content may be too theoretical and out of touch with actual work scenarios, making it difficult for students to apply what they have learned to actual work. In addition, some practical training projects have little relevance to actual corporate projects, and the knowledge and skill points are single, making it difficult for students to learn in depth, and their abilities cannot meet the requirements of corporate positions.

[0007] In recent years, some inventions have focused on building virtual teaching devices for robot virtual training, but this method also has the following disadvantages:

[0008] High development cost. Currently, the teaching pendants of major robot manufacturers are closed source. To develop a virtual teaching pendant, one can only reverse-engineer the real teaching pendant and develop it from scratch, which has a long development cycle and high cost.

[0009] The accuracy of the virtual teach pendant cannot be ensured. Since the teach pendants and controllers of major robot manufacturers are closed source, it is impossible to clarify the underlying operating logic of the teach pendant and the controller, that is, it is impossible to ensure that the developed virtual teach pendant is completely consistent with the real teach pendant, which may lead to cognitive errors during the training process.

[0010] Therefore, there is an urgent need for a new method for constructing a virtual training system based on robot simulation software to solve the above technical problems. Summary of the invention

[0011] The present invention provides a method for constructing a virtual training system based on robot simulation software, comprising the following steps:

[0012] S1. Establish a virtual training model of the robot;

[0013] S2, encapsulating the virtual training model to obtain an encapsulated virtual training scene model;

[0014] S3, performing simulation adjustment and optimization on the packaging virtual training model to obtain an optimized packaging virtual training model;

[0015] S4. Establish a virtual controller based on the model corresponding to the robot, and establish data interaction and mapping relationship between the virtual controller and the optimized packaged virtual training model to obtain a virtual training system.

[0016] Preferably, the virtual training module includes a robot body model, a robot tool model and a training environment model.

[0017] Preferably, packaging the robot body model comprises the following steps:

[0018] Constructing a joint kinematic chain according to the joints and connecting rods of the robot body model;

[0019] Correcting the joint kinematic chain based on standard size parameters and DH parameters corresponding to the robot;

[0020] A kinematic system of the robot body model is constructed.

[0021] Preferably, the virtual training system includes an interaction layer, a business layer and a data layer. The interaction layer is used to display the robot's virtual training courses, training tasks and simulation results and interact with them. The business layer is used to perform data interaction, user management, course management and assessment scoring in the virtual training system. The data layer is used to store and manage data in the virtual training system.

[0022] Compared with the prior art, the present invention establishes a virtual training model of the robot; encapsulates the robot model to obtain an encapsulated virtual training scene model; simulates, adjusts and optimizes the encapsulated virtual training model to obtain an optimized encapsulated virtual training model; establishes a virtual controller based on the model corresponding to the robot, and establishes data interaction and mapping relationship between the virtual controller and the optimized encapsulated virtual training model to obtain a virtual training system. In this way, the robot in the virtual training system is controlled by operating the virtual teaching pendant to perform teaching and programming, thereby completing the training. In this way, students can conduct robot training anytime and anywhere, and repeatedly practice weak knowledge points, thereby effectively solving the problems of few practical operation opportunities, high safety risks, and the disconnection between teaching content and actual work. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention will be described in detail below in conjunction with the accompanying drawings. The above and other aspects of the present invention will become clearer and easier to understand through the detailed description made in conjunction with the following drawings. In the accompanying drawings:

[0024] Figure 1 It is a flowchart of a method for constructing a virtual training system based on robot simulation software provided by an embodiment of the present invention;

[0025] Figure 2 It is a schematic diagram of a virtual training model encapsulation process of a virtual training system construction method based on robot simulation software provided by an embodiment of the present invention;

[0026] Figure 3 It is a schematic diagram of the data interaction process of a method for constructing a virtual training system based on robot simulation software provided by an embodiment of the present invention;

[0027] Figure 4 It is a schematic diagram of a virtual training system architecture of a method for constructing a virtual training system based on robot simulation software provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0029] Please refer to Figure 1-Figure 4The present invention provides a method for constructing a virtual training system based on robot simulation software, comprising the following steps:

[0030] S1. Establish a virtual training model of the robot;

[0031] In an embodiment of the present invention, the virtual training module includes a robot body model, a robot tool model and a training environment model.

[0032] Specifically, according to the robot training scenario, use 3D modeling software such as SolidWorks, Unigraphics NX, 3DStudio Max, etc. to build a virtual training model of the robot training scenario, including but not limited to the robot body, tools and training environment, etc. The model should maintain the kinematic relationship corresponding to the real object, that is, each moving part needs to be independently modeled and assembled in sequence according to the kinematic chain.

[0033] The established virtual training model is imported into the 3D scene of the development platform. This development platform can be a 3D rendering engine development tool or manufacturing simulation software. 3D rendering engines such as Unity, Unreal Engine, JMonkeyEngine and Three.js are tools for generating 3D scene images, and their development tools are computer software specifically used to support the development of these rendering engines. Manufacturing simulation software such as Visual Component, PDPS and Demo3d are computer software specifically used for industrial manufacturing scene simulation.

[0034] S2, encapsulating the virtual training model to obtain an encapsulated virtual training scene model;

[0035] In an embodiment of the present invention, encapsulating the robot body model comprises the following steps:

[0036] Constructing a joint kinematic chain according to the joints and connecting rods of the robot body model;

[0037] Correcting the joint kinematic chain based on standard size parameters and DH parameters corresponding to the robot;

[0038] A kinematic system of the robot body model is constructed.

[0039] Specifically, the joints and connecting rods of the robot body model are split into sub-models, and the child-parent relationship between the joints and connecting rods of the robot is obtained according to the mechanical structure and motion characteristics of the robot, and the joint motion chain of the robot is constructed. Then, the motion chain is corrected according to the standard size parameters or DH parameters in the robot technical manual, so that the relative positions of the joints fully meet the requirements and reduce the size error between the virtual robot and the real robot.

[0040] Secondly, encapsulate the robot functions and give the robot model the ability to move, including building the robot's forward and inverse kinematics algorithms, encapsulating motion methods and animation interpolation algorithms, etc. If the development platform is manufacturing simulation software, since this type of software usually has the above functions built in, it is only necessary to define the robot according to the specific operation methods of different software. If a three-dimensional rendering engine development tool is used as a development platform, these functions need to be implemented manually. According to the robot's DH parameters, a forward kinematics algorithm is constructed to calculate the position and posture of the end effector through the known robot joint posture; at the same time, an inverse kinematics algorithm is constructed to infer the joint posture through the known end effector posture. Among them, the inverse kinematics algorithm includes but is not limited to analytical methods (algebraic methods, geometric methods) and numerical methods, but the analytical method should be used first to obtain a faster solution speed. Then construct the robot's motion trajectory interpolation algorithm and axis motion interpolation algorithm, encapsulate the robot's joint motion, linear motion, circular motion, absolute position motion and other motion methods, so that the robot's motion can be controlled by calling these motion methods.

[0041] Finally, encapsulate the data update response method. Encapsulate the robot joint angle data update response method. When the data is updated, call the joint movement method to move to the target joint angle data within the data collection interval. Encapsulate the robot IO data update response method. When the data is updated, set the corresponding attribute or signal to the updated value.

[0042] The robot tool model and the training scene model are encapsulated at the same time. The process of encapsulating the robot tool and the training scene on the development platform is similar to the process of encapsulating the robot body.

[0043] Firstly, the robot tool model and the training scenario model are processed, the moving parts are split into sub-models, and the motion chain of the robot tool model and the training scenario model is constructed according to the mechanical structure and motion characteristics of the mechanism.

[0044] Secondly, encapsulate the motion and interaction functions, and give the model the ability to move and interact with other models in the scene. The interactions in practical training usually include functions such as grabbing, releasing, adsorbing, pushing, dropping, stacking, and assembling workpieces, the effects of drawing lines and welding of tools, and the functions of various sensors. If the development platform is manufacturing simulation software, since this type of software usually has the above functions, it is only necessary to define the motion and interaction functions of the model according to the specific operation methods of different software. If a 3D rendering engine development tool is used as a development platform, it is necessary to first encapsulate linear and rotational motion interpolation algorithms and motion methods, and then combine the physical engine to encapsulate specific interactive behaviors.

[0045] Finally, encapsulate the data update response method. Robot tools and training scenarios are generally controlled by Boolean signals. The signals need to be encapsulated so that when the data is updated, the model's motion method is called to perform corresponding actions.

[0046] S3, performing simulation adjustment and optimization on the packaging virtual training model to obtain an optimized packaging virtual training model;

[0047] In an embodiment of the present invention, according to the robot training scenario, the encapsulated robot motion method is called, and the corresponding data of the robot tool and the training scenario are set to simulate the actual operation process of the robot. During the simulation process, it can be observed whether the robot's motion meets expectations and whether it can accurately complete the specified task. If any problems or abnormalities are found, the encapsulated motion method or interactive behavior can be adjusted in time to ensure the final training effect. In addition, this step can also be used as a demonstration before training, so that trainees can more clearly understand the operation process, training objectives and precautions of the robot training scenario.

[0048] S4. Establish a virtual controller based on the model corresponding to the robot, and establish data interaction and mapping relationship between the virtual controller and the optimized packaged virtual training model to obtain a virtual training system.

[0049] In an embodiment of the present invention, according to the robot training scenario, the manufacturer and model of the robot used in the scenario are clarified, and the robot simulation software of the manufacturer is installed. For example, if an ABB robot is used, ABB's RobotStudio should be installed; if it is a KUKA robot, KUKA.Sim Pro needs to be installed; for Yaskawa robots, MotoSim is used; and Kawasaki robots correspond to K-Roset, etc. After installation, create a robot and a virtual controller of the corresponding model in the robot simulation software. The main purpose of this step is to ensure the operational consistency between the robot virtual training environment and the real environment, so as to provide an accurate training experience.

[0050] The data interaction process between the virtual training system and the robot simulation software is as follows: Figure 3As shown. A data interaction module is constructed in the virtual training system, and the robot joint angle data, output signal, operation status and other data are read from the virtual controller according to the specified frequency by calling the API interface of the robot simulation software. After these data are cleaned and parsed, they are written into the model of the virtual training scene according to the mapping table. At the same time, according to the specified frequency, the status of the sensor and other models are read from the virtual training scene. Through the data interaction module, the API interface of the robot simulation software is called to write these status data into the corresponding IO of the virtual controller. In this way, the data synchronization mapping between the virtual robot in the robot simulation software and the robot in the virtual training scene is completed.

[0051] When building a virtual training system, training verification is required. First, use the virtual teach pendant in the robot simulation software to perform a single test. Switch the robot to manual mode, manually manipulate the robot to move, and observe whether the robot in the virtual training scene moves correctly. Modify the robot IO data at a single point to observe whether the corresponding model in the scene responds correctly. This verifies the correctness of data interaction and mapping. Ensure the correctness and real-time performance of data interaction and mapping through single tests.

[0052] Secondly, use the virtual teaching pendant in the robot simulation software to teach and write programs to control the robot in the virtual training scene to complete the training tasks. This step is to verify the completeness of the entire virtual training system. Through actual operation and programming, it can be tested whether the system can work as expected and whether it can meet the training needs. If any problems or deficiencies are found, they can be adjusted and optimized in time to ensure that the final training effect is optimal.

[0053] In an embodiment of the present invention, the virtual training system includes an interaction layer, a business layer and a data layer. The interaction layer is used to display the robot's virtual training courses, training tasks and simulation results and interact with them. The business layer is used to perform data interaction, user management, course management and assessment scoring in the virtual training system. The data layer is used to store and manage data in the virtual training system.

[0054] Specifically, Figure 4As shown in the figure, the virtual training system is divided into three main layers: interaction layer, business layer and data layer. Each layer interacts closely through data and functional modules to ensure the integrity and efficiency of the system. The main function of the interaction layer is to interact with users, including the front-end interface and virtual training scenes, etc. It is responsible for presenting the functions of the system so that users can easily view training courses, training tasks and operate robots, view simulation results, etc. The main function of the business layer is to build the main functional modules of the system, including but not limited to data interaction module, user management module, course management module, assessment and scoring module, etc. The data layer is the foundation of the entire system and is responsible for storing and managing all data that may be used in system operation.

[0055] The virtual training system of the present invention can reduce the dependence on physical robots, reduce training costs, and provide more training opportunities. At the same time, virtual training allows trainees to learn at any time and any place without being restricted by physical space. This makes training more flexible and can adapt to the schedules and learning speeds of different trainees. In addition, robot operation training in a virtual environment can greatly reduce the risks in actual operation. Trainees can learn how to operate the robot without the risk of physical injury, which helps reduce the possibility of accidents.

[0056] Virtual training systems can create a variety of complex and extreme operating environments, as well as training environments that fit the actual needs of enterprises, which may be difficult or impossible to replicate in the real world. This helps trainees prepare for complex situations in the real world. At the same time, virtual training systems can monitor trainees' operations in real time and provide instant feedback. This helps trainees understand their performance and make adjustments when necessary. With the rapid development of robotics technology, continuous education has become essential. Virtual training platforms can be easily updated to include the latest technologies and operating procedures to ensure that trainees always learn the latest knowledge.

[0057] The present invention is developed based on the robot simulation software of major robot manufacturers, which greatly reduces the development cycle and difficulty, making the research and development and deployment process faster. Since the simulation software officially launched by the robot manufacturer is used, its virtual controller and virtual teach pendant are completely consistent with the actual equipment, thus ensuring that the effect of practical training through the virtual teach pendant is highly authentic and reliable.

[0058] Compared with the prior art, the present invention establishes a virtual training model of the robot; encapsulates the robot model to obtain an encapsulated virtual training scene model; simulates, adjusts and optimizes the encapsulated virtual training model to obtain an optimized encapsulated virtual training model; establishes a virtual controller based on the model corresponding to the robot, and establishes data interaction and mapping relationship between the virtual controller and the optimized encapsulated virtual training model to obtain a virtual training system. In this way, the robot in the virtual training system is controlled by operating the virtual teaching pendant to perform teaching and programming, thereby completing the training. In this way, students can conduct robot training anytime and anywhere, and repeatedly practice weak knowledge points, thereby effectively solving the problems of few practical operation opportunities, high safety risks, and the disconnection between teaching content and actual work.

[0059] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0060] The embodiments of the present invention are described above in conjunction with the accompanying drawings. What is disclosed is only the preferred embodiment of the present invention. However, the present invention is not limited to the above-mentioned specific implementation manner. The above-mentioned specific implementation manner is only illustrative rather than restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms and equivalent changes without departing from the scope of protection of the purpose of the present invention and the claims, all of which are within the protection of the present invention.

Claims

1. A method for constructing a virtual training system based on robot simulation software, characterized in that: The following steps are involved: S1. Establish a virtual training model of the robot; S2, encapsulating the virtual training model to obtain an encapsulated virtual training scene model; S3, performing simulation adjustment and optimization on the packaging virtual training model to obtain an optimized packaging virtual training model; S4. Establish a virtual controller based on the model corresponding to the robot, and establish data interaction and mapping relationship between the virtual controller and the optimized packaged virtual training model to obtain a virtual training system.

2. The method for constructing a virtual training system based on robot simulation software according to claim 1, characterized in that: The virtual training module includes a robot body model, a robot tool model and a training environment model.

3. The method for constructing a virtual training system based on robot simulation software according to claim 2, characterized in that: Packaging the robot body model includes the following steps: Constructing a joint kinematic chain according to the joints and connecting rods of the robot body model; Correcting the joint kinematic chain based on standard size parameters and DH parameters corresponding to the robot; A kinematic system of the robot body model is constructed.

4. The method for constructing a virtual training system based on robot simulation software according to claim 1, characterized in that: The virtual training system includes an interaction layer, a business layer and a data layer. The interaction layer is used to display the robot's virtual training courses, training tasks and simulation results and interact with them. The business layer is used to perform data interaction, user management, course management and assessment scoring in the virtual training system. The data layer is used to store and manage data in the virtual training system.

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