A method for building cross-platform industrial robot operating system image integration

Abstract

The present invention relates to the field of computer technology, and discloses a method for building an integrated image of a cross-platform industrial robot operating system, comprising the following steps: S1: industrial robot application scenario determination, S2: hardware platform selection; S3: robot function rapid description and configuration; S4: pre-installed applications and environment customization; S5: Yocto file system customization and lightweight; S6: image building and integration; S7: industrial robot operating system deployment; the present invention uses an integrated development environment to quickly build a controller image, thereby adapting to different hardware platforms, improving the modularity of the system, optimizing real-time response performance, achieving efficient construction of the controller environment, simplifying the development process and reducing development difficulty and cost. The design of the hardware abstraction layer enables the robot system to easily adapt to a variety of computing platforms and sensor combinations, improving the applicability and flexibility of the system.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method for building a cross-platform industrial robot operating system image integration. Background Art

[0002] With the continuous expansion of the application of industrial robots in industrial production and daily life, especially driven by the demand for networking and intelligence, the development potential and market value of industrial robots are becoming increasingly prominent. In addition to its core role in the industrial field, robots have shown significant advantages and broad prospects in many industries such as education, finance, medical care, transportation, security and electricity. Therefore, quickly building an industrial robot operating system that is both practical and scalable, and promoting the deep integration of artificial intelligence and robotics technology, has become the key to promoting the large-scale development of the intelligent robot industry.

[0003] However, existing robot operating systems and development platforms have many deficiencies in terms of hardware platform uniformity, modularity, real-time response capability, scalability, and intelligence level. These problems not only increase the difficulty and cost of robot development, but also limit its wide application in different industries. To solve these problems, the industry urgently needs a unified and open robot real-time operating system integrated construction platform to simplify the development process and improve the intelligence level, so as to better meet the diverse market needs. Summary of the invention

[0004] The purpose of the present invention is to provide a method for building a cross-platform industrial robot operating system image integration to solve the problems of large hardware platform differences, low modularity and weak real-time response capability in the industrial robot control system proposed in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for building a cross-platform industrial robot operating system image integration, comprising the following steps:

[0006] S1: Determine the application scenarios of industrial robots and quickly confirm the specific scenarios of robot applications according to needs;

[0007] S2: Hardware platform selection: select the appropriate hardware architecture and operating system based on the determined application scenario requirements, and determine the operating system architecture;

[0008] S3: Rapid description and configuration of robot functions. According to the application scenario requirements, a rapid configuration description file of functions is formulated for industrial robots.

[0009] S4: Pre-install applications and environment customization. According to the description file of the robot function configuration, the necessary applications and library files are pre-installed for the robot to establish an operating environment suitable for specific scenarios.

[0010] S5: Yocto file system customization and lightweight, using Yocto tools to customize the file system, by eliminating unnecessary libraries and services, reducing the file system size, and improving the system startup speed and operating efficiency;

[0011] S6: Image building and integration. After completing the file system customization, the image of the robot operating system is generated in combination with the hardware platform information determined in S2, and the pre-installed applications and environment are integrated into the image.

[0012] S7: Industrial robot operating system deployment, deploying the built image to the actual robot hardware, and performing on-site testing and optimization.

[0013] Furthermore, in S1, the application scenarios include handling, assembly, welding, and spraying. At this stage, the main tasks and core functional requirements of the robot in each application scenario are clarified.

[0014] Furthermore, in S2, the selected hardware architecture includes: evaluation computing platform, sensor type and execution component.

[0015] Furthermore, in S3, the goal of developing a quick configuration description file for the functions of an industrial robot is to clarify the robot's core functional modules, required software functions, supported algorithm libraries, and generate a configuration list to prepare for the pre-installation of the next environment.

[0016] Furthermore, in S3, the algorithm library includes motion control algorithm library, perception-planning-control algorithm library, process model library, python, CUDA, MLP, and OpenGL.

[0017] Furthermore, in S4, applications and library files are preinstalled according to the functions selected in S3. The environment customization includes configuring the dependency packages, tool chains, and specific network communication protocol stacks required for development to ensure that the robot can run stably and efficiently in actual applications. The purpose of this step is to accelerate subsequent development and debugging and improve development efficiency.

[0018] Furthermore, in S5, the kernel configuration is optimized during the file system customization process, retaining only the drivers and functional modules required for the application scenario to achieve a lightweight operating system. This process helps to improve the system's response speed and reliability.

[0019] Furthermore, in S6, compatibility testing was performed to ensure that the robot could start and run smoothly.

[0020] Furthermore, in S6, integration testing is performed during compatibility testing, and module test cases are provided through an integrated development environment to verify whether each functional module can run stably on specific hardware and meet the needs of the industrial site.

[0021] Furthermore, in S7, system settings are adjusted based on the test results to optimize performance and ensure compliance with all technical specifications and safety standards, ultimately outputting a fully functional industrial robot ready for production use.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] The present invention adapts to different hardware platforms, improves the modularity of the system, optimizes the real-time response performance, realizes the efficient construction of the controller environment, simplifies the development process and reduces the development difficulty and cost by abstracting the robot functions, using structured text to describe the robot, and using an integrated development environment to quickly build a controller image. The design of the hardware abstraction layer enables the robot system to easily adapt to a variety of computing platforms and sensor combinations, improving the applicability and flexibility of the system. The use of automated construction tools and an integrated development environment greatly shortens the development and deployment time, ensures that the system image generated each time is consistent, and reduces the errors and differences caused by manual configuration. Through rapid prototyping and standardized interfaces, the development team can iterate and test faster, shortening the time to market. In addition, this method also lowers the entry threshold for developers, reduces the learning curve, and further reduces development costs.

[0024] The parts not involved in the device are the same as those in the prior art or can be implemented by using the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A framework diagram of a method for integrating and building a cross-platform industrial robot operating system image according to the present invention;

[0026] Figure 2 A flowchart of a method for integrating and building a cross-platform industrial robot operating system image according to the present invention; Figure 3 The present invention provides a structured file for integrating hardware platform information into a cross-platform industrial robot operating system mirror. DETAILED DESCRIPTION

[0027] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0028] See also Figure 1-Figure 2 The present invention provides a technical solution: a method for building a cross-platform industrial robot operating system image integration, comprising the following steps:

[0029] S1: Determine the application scenarios of industrial robots and quickly confirm the specific scenarios of robot applications according to needs;

[0030] S2: Hardware platform selection: select the appropriate hardware architecture and operating system based on the determined application scenario requirements, and determine the operating system architecture;

[0031] S3: Rapid description and configuration of robot functions. According to the application scenario requirements, a rapid configuration description file of functions is formulated for industrial robots.

[0032] S4: Pre-install applications and environment customization. According to the description file of the robot function configuration, the necessary applications and library files are pre-installed for the robot to establish an operating environment suitable for specific scenarios.

[0033] S5: Yocto file system customization and lightweight, using Yocto tools to customize the file system, by eliminating unnecessary libraries and services, reducing the file system size, and improving the system startup speed and operating efficiency;

[0034] S6: Image building and integration. After completing the file system customization, the image of the robot operating system is generated in combination with the hardware platform information determined in S2, and the pre-installed applications and environment are integrated into the image.

[0035] S7: Industrial robot operating system deployment, deploying the built image to the actual robot hardware, and performing on-site testing and optimization.

[0036] In S1, the application scenarios include handling, assembly, welding, and spraying. At this stage, the main tasks and core functional requirements of the robot in each application scenario are clarified. For example, in welding applications, the robot should have functions such as precise positioning, trajectory control, and temperature management; while in assembly applications, it needs to have high-precision assembly and material management capabilities.

[0037] In S2, the selected hardware architecture includes: evaluating computing platforms, such as x86, ARM, RISC-V, LoongArch, etc., sensor types, such as force sensors, visual sensors, and actuators, such as robotic arms, grippers, etc. Determine the operating system architecture, such as the real-time operating system RTOS for tasks with high real-time requirements, or the Linux architecture for versatility and multi-tasking scenarios.

[0038] In S3, the goal of developing a quick configuration description file for the functions of an industrial robot is to clarify the robot's core functional modules, required software functions, supported algorithm libraries, and generate a configuration list to prepare for the pre-installation of the next environment.

[0039] In S3, the algorithm library includes motion control algorithm library, perception-planning-control algorithm library, process model library, python, CUDA, MLP, and OpenGL.

[0040] In S4, pre-installed applications and library files are pre-installed according to the functions selected in S3. The environment customization includes configuring the dependency packages, tool chains and specific network communication protocol stacks required for development to ensure that the robot can run stably and efficiently in actual applications. The purpose of this step is to accelerate subsequent development and debugging and improve development efficiency.

[0041] In S5, the kernel configuration is optimized during the file system customization process, retaining only the drivers and functional modules required for the application scenario to achieve a lightweight operating system. This process helps improve the system's response speed and reliability.

[0042] In S6, compatibility testing is performed to ensure that the robot can start and run smoothly.

[0043] In S6, integration testing is performed during compatibility testing, and module test cases are provided through the integrated development environment to verify whether each functional module can run stably on specific hardware and meet the needs of the industrial site.

[0044] In S7, system settings are adjusted based on the test results to optimize performance and ensure compliance with all technical specifications and safety standards, ultimately outputting a fully functional industrial robot ready for production use.

[0045] The present invention adapts to different hardware platforms, improves the modularity of the system, optimizes the real-time response performance, realizes the efficient construction of the controller environment, simplifies the development process and reduces the development difficulty and cost by abstracting the robot functions, using structured text to describe the robot, and using an integrated development environment to quickly build a controller image. The design of the hardware abstraction layer enables the robot system to easily adapt to a variety of computing platforms and sensor combinations, improving the applicability and flexibility of the system. The use of automated construction tools and an integrated development environment greatly shortens the development and deployment time, ensures that the system image generated each time is consistent, and reduces the errors and differences caused by manual configuration. Through rapid prototyping and standardized interfaces, the development team can iterate and test faster, shortening the time to market. In addition, this method also lowers the entry threshold for developers, reduces the learning curve, and further reduces development costs.

[0046] Example 2: Please refer to Figure 1-Figure 2 The present invention provides a technical solution: a method for building an integrated image of a cross-platform industrial robot operating system. In this embodiment, the technical solution of the present invention is further described by taking the robot spraying process as a scenario:

[0047] Step 1: The spraying robot uses a high-precision visual scanning camera to calibrate and test the accuracy of the information and contour features of the sprayed workpiece; the image processing system is used to identify, segment and reduce noise on the collected image information, and the processing effect is tested by comparing it with the actual object. It is clear that the spraying robot needs precise control of the visual processing function.

[0048] Step 2: Through the analysis of step 1, we can clearly understand the visual processing functions required by the spraying process robot, including high-precision image recognition, target segmentation, contour feature extraction, and noise suppression processing. Based on these functional requirements, open the integrated development environment (IDE), create a new project and select "Robot Spraying Configuration". According to the prompts, select the required sensor type, such as high-precision industrial cameras and image processors. In addition, it is necessary to select a suitable computing architecture and consider using a high-performance ARM (RK3588) platform to meet the needs of visual computing. At the same time, select RTOS to achieve real-time control of the spraying process to ensure the accuracy and stability of the operation. Finally, the integrated development environment will recommend the existing technical solution, the chip model is RK3568, the memory is 2GB, and the final configuration file is generated, such as Figure 3 shown.

[0049] Step 3: Use the integrated development environment (IDE) and select the robot configuration as spraying according to the prompts of the IDE. The integrated environment will provide configuration prompts such as visual recognition, trajectory processing, and spray path planning. According to these prompts, select the driver modules including visual recognition, trajectory planning, spray path control, spray gun management, image segmentation algorithm library, contour extraction algorithm library, path planning algorithm library, Python, OpenCV, EtherCAT, and related peripherals. After the selection is completed, the IDE will generate a structured description file for the industrial robot.

[0050] Step 4: Based on the structured description file in step 3, use the integrated development environment (IDE) to compile and generate applications and library files related to visual processing, path planning, and spray control. Install OpenCV and MoveIt according to the IDE prompts, and ensure that the library file path is set correctly.

[0051] Step 5: Use Yocto tools to build a customized file system. Execute make menuconfig to configure the necessary environment except for the one in step 4. Execute chroot to load the Yocto file system, uninstall unnecessary system libraries and services, and only keep the core libraries and services. Reduce the size of the file system, improve the system startup speed and operating efficiency, and thus improve the real-time response capability of the spraying process robot. Run bitbake core-image-minimal to build a customized file system.

[0052] Step 6: After completing the customization of the Yocto file system, combined with the hardware platform information configured in step 2, click the "Build" button of the integrated development environment (IDE) to package the kernel and the Yocto file system to generate an operating system image suitable for the spray process robot. The pre-installed image processing and spray control applications, as well as the customized environment, will be integrated into the image, and the generated image file will appear in the workspaces directory to ensure its correct integration.

[0053] Step 7: Use the burning cable to deploy the built operating system image to the controller of the spray process robot and start the controller. After starting, observe the startup log to confirm that each module is loaded normally. Then, compile and verify the functions of each component through the integrated development environment (IDE). Through these specific operation steps, developers can implement the development process of the spray process robot more smoothly. If you need to add or modify some functions, you can start from step 3 again for adjustment and optimization.

[0054] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of the present invention.

Claims

1. A method for building a cross-platform industrial robot operating system image integration, characterized in that: The following steps are involved: S1: Determine the application scenarios of industrial robots and quickly confirm the specific scenarios of robot applications according to needs; S2: Hardware platform selection: select the appropriate hardware architecture and operating system based on the determined application scenario requirements, and determine the operating system architecture; S3: Rapid description and configuration of robot functions. According to the application scenario requirements, a rapid configuration description file of functions is formulated for industrial robots. S4: Pre-install applications and environment customization. According to the description file of the robot function configuration, the necessary applications and library files are pre-installed for the robot to establish an operating environment suitable for specific scenarios. S5: Yocto file system customization and lightweight, using Yocto tools to customize the file system, by eliminating unnecessary libraries and services, reducing the file system size, and improving the system startup speed and operating efficiency; S6: Image building and integration. After completing the file system customization, the image of the robot operating system is generated in combination with the hardware platform information determined in S2, and the pre-installed applications and environment are integrated into the image. S7: Industrial robot operating system deployment, deploying the built image to the actual robot hardware, and performing on-site testing and optimization.

2. A method for building a cross-platform industrial robot operating system image integration according to claim 1, characterized in that: In S1, application scenarios include handling, assembly, welding, and spraying. At this stage, the main tasks and core functional requirements of the robot in each application scenario are clarified.

3. A method for building a cross-platform industrial robot operating system image integration according to claim 1, characterized in that: In S2, the selected hardware architecture includes: evaluation computing platform, sensor types and execution components.

4. A method for building a cross-platform industrial robot operating system image integration according to claim 1, characterized in that: In S3, the goal of developing a quick configuration description file for the functions of an industrial robot is to clarify the robot's core functional modules, required software functions, supported algorithm libraries, and generate a configuration list to prepare for the pre-installation of the next environment.

5. The method for building a cross-platform industrial robot operating system image integration according to claim 1, characterized in that: In S3, the algorithm library includes motion control algorithm library, perception-planning-control algorithm library, process model library, python, CUDA, MLP, and OpenGL.

6. A method for building a cross-platform industrial robot operating system image integration according to claim 1, characterized in that: In S4, pre-installed applications and library files are pre-installed according to the functions selected in S3. The environment customization includes configuring the dependency packages, tool chains and specific network communication protocol stacks required for development to ensure that the robot can run stably and efficiently in actual applications. The purpose of this step is to accelerate subsequent development and debugging and improve development efficiency.

7. A method for building a cross-platform industrial robot operating system image integration according to claim 1, characterized in that: In S5, the kernel configuration is optimized during the file system customization process, retaining only the drivers and functional modules required for the application scenario to achieve a lightweight operating system. This process helps improve the system's response speed and reliability.

8. The method for building a cross-platform industrial robot operating system image integration according to claim 1, characterized in that: In S6, compatibility testing is performed to ensure that the robot can start and run smoothly.

9. A method for building a cross-platform industrial robot operating system image integration according to claim 8, characterized in that: In S6, integration testing is performed during compatibility testing, and module test cases are provided through the integrated development environment to verify whether each functional module can run stably on specific hardware and meet the needs of the industrial site.

10. The method for building a cross-platform industrial robot operating system image integration according to claim 1, characterized in that: In S7, system settings are adjusted based on the test results to optimize performance and ensure compliance with all technical specifications and safety standards, ultimately outputting a fully functional industrial robot ready for production use.

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