Robot system basic container mirror image construction method and system based on RT-OS

Abstract

The invention provides a robot system basic container mirror image construction method and system based on RT-OS, and relates to the technical field of intelligent technology. The method comprises the steps that firstly, a basic container mirror image integrating a real-time kernel and a hardware interface is constructed, and modular basic container mirror images are constructed in a layered mode according to different robot function requirements; then, a centralized mirror image warehouse is built, base container mirror images are stored in a centralized mode, and unified management and remote distribution of the mirror images are achieved; and finally, deploying a container runtime environment in a robot body, pulling and operating the basic container mirror image, and configuring real-time parameters to guarantee the system performance of the robot. According to the method and system, flexible deployment and management of the robot operating system are achieved through the containerization technology, an extensible and efficient platform is provided, and the requirements of different application scenes can be rapidly met.

Description

Technical Field

[0001] This invention relates to the field of embodied intelligence technology, and in particular to a method and system for constructing a basic container image for a robot system based on RT-OS. Background Technology

[0002] Modern robotic systems extensively utilize Linux or other real-time operating systems (RT-OS), such as RT-Linux, FreeRTOS, and VxWorks. While these systems offer advantages in real-time performance, installation and configuration typically require manual intervention, and each deployment necessitates building the environment from scratch. With the development of artificial intelligence and automation technologies, robots are widely used in automated manufacturing, intelligent services, medical assistance, warehousing and logistics, and other fields, all of which demand extremely high real-time performance and stability. Container technologies such as Docker and Podman are widely used in the IT field, enabling cross-platform operation by encapsulating operating systems and application software. However, in the robotics field, the application of containerization solutions still faces certain challenges due to the specific requirements for real-time hardware interaction. For example, real-time operating systems often need direct access to the underlying hardware, and the abstraction layer of container technology may impact its performance.

[0003] In practical applications of robots, installing the operating system and related software requires a significant amount of manual work, and the installation process needs to be repeated for each robot. This can easily lead to inconsistent environments and increase maintenance costs. Specifically, the main problems currently include: Long deployment times and low efficiency: Manually installing RT-OS and related software typically takes several hours or even longer, especially in large-scale deployments. This time-consuming installation process significantly impacts work efficiency. With the increasing prevalence of robotic applications and the growing demand for rapid deployment, traditional deployment methods can no longer meet industry needs.

[0004] Inconsistent environments and compatibility issues: Different robots, due to variations in software versions and configuration parameters, may experience system incompatibility, affecting normal operation. This not only increases the debugging workload for developers but may also lead to stability issues during robot operation, or even system crashes. Environmental differences between each robot make large-scale system updates and management in a production environment complex and prone to errors.

[0005] High maintenance costs: With each system update or configuration adjustment, the software needs to be manually reinstalled, and sometimes the hardware even needs to be reconfigured, increasing the complexity and cost of maintenance. Especially with a large number of robots, upgrading and maintaining each one individually is not only time-consuming and labor-intensive, but also prone to operational errors.

[0006] Lack of modular management: Current deployment methods are usually singular and fixed, making it difficult to flexibly adjust the robot system's software environment according to different application scenarios. For example, a robot may require different functional modules and configurations in different application scenarios, but traditional operating system installation methods are difficult to quickly adjust and customize, failing to achieve modular management, resulting in wasted resources and unnecessary redundant configurations.

[0007] Therefore, combining RT-OS with container image technology to enable robot systems to enjoy the advantages of rapid container deployment while maintaining real-time performance is an important direction for current technological research. Furthermore, different types of robot applications require different software components and driver support; traditional software installation methods require configuration one by one, which is time-consuming and error-prone. Therefore, finding a solution that can improve the deployment efficiency of robot operating systems while ensuring system consistency and real-time performance has become a key focus of the industry. Summary of the Invention

[0008] The technical problem to be solved by the present invention is to address the shortcomings of the prior art by providing a method and system for building a basic container image of a robot system based on RT-OS. By combining RT-OS with container technology, an efficient and modular robot operating system deployment can be achieved.

[0009] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: On the one hand, the present invention provides a method for building a basic container image of a robot system based on RT-OS, specifically including: First, select a real-time operating system suitable for the target robot scenario, and prepare the corresponding cross-compilation toolchain and header files according to the target robot hardware platform architecture to generate files that can be executed on another platform; Next, an RT-OS container image is built using a kernel build toolchain or container build script, serving as the base container image for the real-time operating system runtime environment; the base container image integrates the following: RT-OS real-time kernel and its patches; The real-time scheduling module is bound to the CPU interrupt to ensure that CPU interrupts are not preempted; System runtime library and POSIX interface support; The hardware driver module required for the robot supports real-time control of sensors and actuators in the robot system; User-space real-time toolchain and debugging tools; During container runtime, the base container image runs in privileged mode and maps the underlying device nodes to ensure that the container can access kernel interrupts, device drivers, and hardware bus resources, meeting the requirements of robot control systems for low latency and determinism.

[0010] Furthermore, the base container image supports pluggable drivers and mounting mechanisms, which facilitates the mounting of specific communication configurations, hardware parameters, and scheduling strategies onto the base container image, enabling the deployment system to have high scalability.

[0011] Furthermore, after the base container image is built, the method performs a real-time verification test on the base container image, including: Determine the maximum interrupt response delay; Perform jitter analysis; Determine the accuracy of task cycle scheduling; Generate benchmark performance reports to facilitate version control and compliance certification.

[0012] Furthermore, the method constructs a modular basic container image in layers according to different robot functional requirements, including: The business logic, algorithm modules, and middleware components of different types of robots are classified and managed, and basic container images are built to implement different functions. Each container image serves as a functional module and adopts a layered design approach.

[0013] Furthermore, the method enables consistent deployment and rapid replication of robot systems for mass production robots. All robots obtain the base container image for operation through a unified image repository. The configuration files of the container image are centrally managed, defining system-level parameters such as communication parameters, sensor configurations, and motion model parameters. The configuration files and system-level parameters are loaded into the base container image during deployment through mounting or injection. The robot system supports version switching and hot replacement of the base container image to meet the testing, deployment, and maintenance needs at different stages.

[0014] Furthermore, the method supports online upgrades of the base container image and expansion of task modules; when the robot system needs to add new functions or fix defects, online upgrades are achieved by updating the base container image; new functional modules are integrated into the robot system as independent container images.

[0015] On the other hand, the present invention also provides a robot system basic container image building system based on RT-OS, including: a basic container image building module: used to build a basic container image integrating a real-time kernel and hardware interface; Container image storage module: used to build a centralized image repository, centrally store basic container images, and realize unified management and remote distribution of images; Container image deployment module: Used to deploy a container runtime environment on the robot body, pull and run the base container image, and configure real-time parameters to ensure the performance of the robot system.

[0016] The beneficial effects of adopting the above technical solution are as follows: The present invention provides a method and system for constructing a basic container image for a robot system based on RT-OS. This method combines industrial real-time systems with containerized deployment to achieve rapid and efficient deployment of the robot operating system. It can build dedicated robot system images for different fields, and system replacement only requires replacing the new image, eliminating the need for environment configuration. An image repository is established, allowing different fields to pull the most suitable images. This method and system achieve flexible deployment and management of the robot operating system through containerization technology, providing a scalable and efficient platform that can quickly adapt to the needs of different application scenarios. It simplifies the deployment process, ensures environmental consistency, facilitates maintenance and updates, and improves resource utilization and system security. It is suitable for various robot applications in industry, medical, and service sectors, significantly improving the flexibility and reliability of the robot system. Attached Figure Description

[0017] Figure 1 A schematic diagram illustrating the process of constructing a basic container image for a robot system based on RT-OS, as provided by this invention; Figure 2 A schematic diagram of the structure of the basic container image provided by this invention; Figure 3 A comparison diagram of the RT-OS-based robot system basic container image construction method of the present invention and the traditional container image deployment method. Detailed Implementation

[0018] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0019] In this embodiment, a method for building a basic container image for a robot system based on RT-OS is described, such as... Figure 1 As shown, the process first involves building a basic container image integrating a real-time kernel and hardware interfaces, and then constructing modular basic container images in layers according to different robot functional requirements. A centralized image repository is established to achieve unified management and remote distribution of images. Next, a container runtime environment is deployed on the robot itself, the basic container image is pulled and run, and real-time parameters are configured to ensure performance. Simultaneously, consistent deployment and centralized management improve the reliability of the robot system. Furthermore, remote status monitoring, online upgrades, and modular expansion are supported, significantly improving the deployment efficiency, flexibility, and maintainability of the robot system. Specifically, the process includes the following steps: Step S1: Build the base container image of the real-time operating system (RT-OS) suitable for the target robot scenario. First, as follows... Figure 2As shown, select a real-time operating system (such as RT-Linux, Xenomai, or FreeRTOS) suitable for the target robot application scenario, and prepare the corresponding cross-compilation toolchain and header files according to the robot's hardware platform architecture (such as ARM or x86) to generate files executable on another platform. For example, compile code on the x86 host into an RT-OS program that can be directly run on the target robot hardware. Build an RT-OS container image using a kernel build toolchain (such as Yocto or Buildroot) or container build script (such as Dockerfile) as the base container image for the real-time operating system runtime environment. Unlike regular user-space application container images, the core of this step is to encapsulate a system kernel and driver stack with embedded RT capabilities to provide real-time scheduling guarantees for upper-layer business images.

[0020] This base container image integrates the RT-OS real-time kernel and its patches (e.g., enabling CONFIG_PREEMPT_RT), real-time scheduling modules and CPU interrupt binding settings (ensuring interrupts are not preempted), system runtime libraries and POSIX interface support, and hardware driver modules required by the robot (such as EtherCAT, CAN, SPI, I2C, serial port controllers, PWM drivers, etc.), supporting real-time control of sensors and actuators in the robot system; as well as user-space real-time toolchains and debugging tools (such as cyclictest, rtprio, irqbalance, taskset, etc.). During container runtime, the base container image must run in privileged mode and map underlying device nodes (such as / dev, / sys, / proc) to ensure that the container can access kernel interrupts, device drivers, and hardware bus resources, meeting the robot control system's requirements for low latency and determinism. Furthermore, the base image must support pluggable drivers and mounting mechanisms, facilitating the subsequent mounting of specific communication configurations, hardware parameters, and scheduling strategies to the base container image, improving system scalability. After the base container image is built, real-time verification tests are performed, including determining the maximum interrupt response latency (expected to be less than 50 microseconds), performing jitter analysis, determining the accuracy of task periodic scheduling, and generating a benchmark performance report to facilitate base container image version control and compliance certification.

[0021] Based on this, and according to the functional requirements of the robot, business logic, algorithm modules, and middleware components are categorized and managed to construct modular basic container images that realize functions such as motion control, path planning, environmental perception, and human-machine interaction. Each basic container image serves as a functional module, defining operating parameters, module loading order, interface mapping, hardware binding, network configuration, resource limits, security policies, and log mounting through configuration files. This modular approach allows for flexible combination of functions to adapt to different platform requirements, achieving system portability, scalability, and operational security. For example, the industrial robot basic container image comes pre-installed with the RT-Linux kernel and industrial bus drivers to meet high-precision task requirements; the medical robot basic container image includes FreeRTOS and medical image processing libraries, suitable for surgical assistance; the service robot basic container image integrates speech recognition and SLAM navigation systems to adapt to intelligent interaction scenarios; and the logistics robot basic container image is configured with path planning and warehousing system interfaces to achieve efficient handling and scheduling. This modular management approach supports flexible replacement of hardware drivers and applications, avoiding software redundancy and resource waste, and significantly improving the flexibility and operational efficiency of the real-time operating system.

[0022] Step S2: Build a centralized image repository management platform; use Harbor, Nexus, or a self-built image repository management system to build an image repository management platform, centrally store basic container images through the image repository, and provide version management, access control, container image signing and security verification mechanisms for basic container images; robot terminals or edge devices can remotely pull and update each container image in the image repository through the network, thereby supporting batch deployment, remote upgrade and rapid recovery and other operation and maintenance operations, improving the deployment efficiency and reliability of the robot system.

[0023] Step S3: Run a container runtime environment on the robot body and deploy a basic container image; the robot device is pre-installed with a lightweight Linux system (such as UbuntuCore, Yocto) and runs a container engine (such as Docker, containerd, etc.). Pull the required RT-OS basic container image from the image repository management platform and start it on the robot body; the container runtime needs to be configured with privileged mode and device mapping (such as mounting / dev, / sys, / proc) to ensure that the container image has access to the underlying hardware resources.

[0024] Step S4: Perform consistent deployment and rapid replication of the robot system for mass production robots; all robots obtain the base container image through a unified image repository to ensure the consistency of the robot system environment and avoid functional abnormalities caused by deployment differences. The configuration files of the base container image are centrally managed, defining system-level parameters such as communication parameters, sensor configurations, and motion model parameters. The configuration files and system-level parameters are loaded into the base container image during deployment through mounting or injection, achieving rapid parameter adaptation; the robot system supports version switching and hot replacement of the base container image to meet the testing, deployment, and maintenance needs at different stages.

[0025] Step S5: Perform online upgrades and task module expansions for the base container image; when the robot system needs to add new functions or fix defects, online upgrades are achieved by updating the base container image. No physical contact with equipment is required; functional modules can be remotely deployed via the network, significantly reducing maintenance costs and response time. New functional modules are integrated into the robot system as independent application container images, deployed on demand, improving the modularity and scalability of the robot system.

[0026] In this embodiment, the architecture of the RT-OS-based robot system basic container image construction method is as follows: Figure 2 As shown, this method enables flexible deployment and management of the robot operating system through containerization technology, providing a scalable and efficient platform that can quickly adapt to the needs of different application scenarios. It simplifies the deployment process, ensures environmental consistency, facilitates maintenance and updates, and improves resource utilization and system security. It is suitable for various robot applications in industry, healthcare, and service, significantly enhancing the flexibility and reliability of robot systems.

[0027] Compared with traditional deployment methods, the method of this invention has the following advantages: Figure 3 As shown, it has the following advantages: Combining RT-OS and container technology: Breaking through the traditional RT-OS deployment model, it provides a flexible containerization solution. By pre-integrating RT-OS and the necessary drivers into the container image, it simplifies the traditional operating system installation process while retaining RT-OS's direct access to the hardware layer.

[0028] Modular management: Customized images are designed for different robot application scenarios, supporting flexible adjustments to hardware drivers, applications, and system configurations, thus improving system adaptability. This innovative design enables the robot operating system to dynamically select the required software modules based on needs, achieving highly configurable deployment.

[0029] Optimizing performance and real-time performance: The RT-OS runtime mechanism is optimized for container environments to maintain high efficiency and stability. By adjusting the kernel scheduling algorithm, priority settings, and resource isolation strategies, RT-OS can still achieve high real-time performance and low latency when running in containers, meeting the stringent timeliness requirements of robot control systems.

[0030] Automated deployment and upgrades: No manual configuration is required; the entire process can be completed simply by pulling and running the image, significantly improving operational efficiency. System updates, software upgrades, and fault repairs can all be completed quickly through container image replacement and automatic deployment, reducing the workload of operations personnel and mitigating the risk of human error.

[0031] Reduced development and maintenance costs: Developers no longer need to manually install and configure robot systems, saving significant time and manpower costs, allowing them to focus on developing algorithms and application-level business logic. Robot manufacturers and service providers can also shorten product development cycles through rapid deployment of images.

[0032] Improved deployment efficiency: The time to go online for robotic systems can be reduced from hours to minutes, significantly improving production efficiency. The rapid deployment process significantly enhances the market responsiveness of robotic products, enabling companies to quickly adapt to market changes.

[0033] Enhanced system reliability: A unified software environment reduces system failures caused by software version differences between different devices, improving the stability of robot operation. The deployment of a standardized and consistent environment effectively reduces the risks of hardware compatibility issues and software conflicts.

[0034] Adaptable to various application scenarios: Supports robot applications in multiple fields such as industry, logistics, healthcare, and services, enhancing the system's adaptability and versatility. Flexible image management allows for customization of the robot system according to different scenarios, adapting to the varying performance and functional requirements of different fields.

[0035] Reduced resource consumption: Compared to traditional virtual machine solutions, containerized RT-OS consumes fewer resources and has higher energy efficiency, making it suitable for embedded systems and low-power devices. Containerization effectively reduces hardware resource consumption through resource sharing and a lightweight architecture, making it suitable for resource-constrained robotic hardware.

[0036] In this embodiment, a robot system based on RT-OS basic container image building system includes: a basic container image building module: used to build a basic container image integrating a real-time kernel and hardware interface; Container image storage module: used to build a centralized image repository, centrally store basic container images, and realize unified management and remote distribution of images; Container image deployment module: Used to deploy a container runtime environment on the robot body, pull and run the base container image, and configure real-time parameters to ensure the performance of the robot system.

[0037] The following describes the RT-OS-based robot system basic container image building device provided in the embodiments of the present invention. The RT-OS-based robot system basic container image building device described below can be referred to in correspondence with the RT-OS-based robot system basic container image building method and RT-OS-based robot system container image building system described above.

[0038] The robot system basic container image building device based on RT-OS provided in this embodiment of the invention may include a processor and a memory. The memory is used to store computer programs; the processor is used to execute the computer programs to implement the robot system basic container image building method based on RT-OS described in the above embodiment of the invention.

[0039] In this embodiment of the RT-OS-based robot system basic container image building device, the processor is used to install the RT-OS-based robot system basic container image building system described in the above-mentioned embodiments. Simultaneously, the processor, combined with the memory, can implement the RT-OS-based robot system basic container image building method described in any of the above-mentioned embodiments. Therefore, the specific implementation of the RT-OS-based robot system basic container image building device can be found in the preceding embodiment section of the RT-OS-based robot system basic container image building method. The specific implementation can be referred to the descriptions of the corresponding embodiments, and will not be repeated here.

[0040] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a method for constructing a basic container image of a robot system based on RT-OS as described in any of the above embodiments. Further details can be found in the prior art and will not be elaborated upon here.

[0041] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0042] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0043] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0044] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0045] The foregoing has provided a detailed description of a method for constructing a basic container image for a robot system based on RT-OS, a system for constructing a basic container image for a robot system based on RT-OS, an apparatus for constructing a basic container image for a robot system based on RT-OS, and a computer-readable storage medium. Specific examples have been used to illustrate the principles and implementation methods of the invention. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and core ideas of the invention. It should be noted that those skilled in the art can make various improvements and modifications to the invention without departing from its principles, and these improvements and modifications also fall within the protection scope of the invention.

[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the present invention.

Claims

1. A method for constructing a basic container image for a robot system based on RT-OS, characterized in that, include: Select a real-time operating system suitable for the target robot scenario, and prepare the corresponding cross-compilation toolchain and header files according to the target robot hardware platform architecture to generate files that can be executed on another platform; RT-OS container images are built using kernel build toolchains or container build scripts, serving as the base container images for the real-time operating system runtime environment; The base container image integrates the following: RT-OS real-time kernel and its patches; The real-time scheduling module is bound to the CPU interrupt to ensure that CPU interrupts are not preempted; System runtime library and POSIX interface support; The hardware driver module required for the robot supports real-time control of sensors and actuators in the robot system; User-space real-time toolchain and debugging tools; During container runtime, the base container image runs in privileged mode and maps the underlying device nodes to ensure that the container can access kernel interrupts, device drivers, and hardware bus resources, meeting the requirements of robot control systems for low latency and determinism.

2. The method for constructing a basic container image for a robot system based on RT-OS according to claim 1, characterized in that, The base container image supports pluggable drivers and mounting mechanisms, which facilitates the mounting of specific communication configurations, hardware parameters and scheduling strategies on the base container image, making the deployment system highly scalable.

3. The method for constructing a basic container image for a robot system based on RT-OS according to claim 2, characterized in that, After the base container image is built, the method performs real-time verification testing of the base container image, including: Determine the maximum interrupt response delay; Perform jitter analysis; Determine the accuracy of task cycle scheduling; Generate benchmark performance reports to facilitate version control and compliance certification.

4. The method for constructing a basic container image for a robot system based on RT-OS according to claim 1, characterized in that, The method constructs a modular base container image in layers according to different robot functional requirements, including: The business logic, algorithm modules, and middleware components of different types of robots are classified and managed, and basic container images are built to implement different functions. Each container image serves as a functional module and adopts a layered design approach.

5. The method for constructing a basic container image for a robot system based on RT-OS according to claim 1, characterized in that, The method described above enables consistent deployment and rapid replication of robot systems for mass production robots. All robots obtain the base container image for operation through a unified image repository. The configuration files of the container images are centrally managed, defining system-level parameters such as communication parameters, sensor configurations, and motion model parameters. The configuration files and system-level parameters are loaded into the base container image during deployment by mounting or injecting. The robot system supports version switching and hot replacement of the base container image to meet the testing, deployment, and maintenance needs at different stages.

6. The method for constructing a basic container image for a robot system based on RT-OS according to claim 5, characterized in that, The method supports online upgrades of the base container image and expansion of task modules. When the robot system needs to add new functions or fix defects, online upgrades are achieved by updating the base container image. New functional modules are integrated into the robot system as independent container images.

7. A system for building a basic container image for a robot system based on RT-OS, characterized in that: include: Basic container image build module: Used to build basic container images that integrate real-time kernel and hardware interfaces; Container image storage module: used to build a centralized image repository, centrally store basic container images, and realize unified management and remote distribution of images; Container image deployment module: Used to deploy a container runtime environment on the robot body, pull and run the base container image, and configure real-time parameters to ensure the performance of the robot system.

8. A robot system basic container image building device based on RT-OS, used to execute the robot system basic container image building method based on RT-OS according to any one of claims 1-6, characterized in that: It includes a processor and a memory; the memory is used to store computer programs; the processor is used to implement the RT-OS-based robot system basic container image construction method when executing the computer programs.

9. The RT-OS-based robot system basic container image building device according to claim 8, characterized in that: The processor is used to install the RT-OS-based robot system basic container image building system, and the combination of the processor and memory can realize the RT-OS-based robot system basic container image building method.

10. A computer-readable storage medium for executing the method for constructing a basic container image of a robot system based on RT-OS as described in any one of claims 1-6, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method for constructing a basic container image for a robot system based on RT-OS.

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