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KR-20260065313-A - Edge-based intelligence support method for performing complex tasks of autonomous robots

KR20260065313AKR 20260065313 AKR20260065313 AKR 20260065313AKR-20260065313-A

Abstract

An edge-based intelligence support method for performing complex tasks by an autonomous robot is provided. The method for performing tasks by an autonomous robot according to an embodiment of the present invention involves the autonomous robot performing a task using an ultra-lightweight artificial intelligence model, an edge server supporting the task performance of the autonomous robot using the lightweight artificial intelligence model, and a cloud server supporting the task performance of the robot using a massive artificial intelligence model. Accordingly, by going beyond merely distributing and updating the artificial intelligence models required when the autonomous robot performs various tasks via edge computing, and by supporting the task performance itself through the edge or cloud, it becomes possible to enhance the mission performance of the autonomous robot and improve service quality.

Inventors

  • 김현우

Assignees

  • 한국전자기술연구원

Dates

Publication Date
20260508
Application Date
20241101

Claims (12)

  1. A step in which an autonomous robot performs a task using a first artificial intelligence model; A first support step in which an edge server supports the task execution of an autonomous robot using a second artificial intelligence model; A method for performing a task of an autonomous robot, characterized by including a second support step in which a cloud server supports the robot's task performance using a third artificial intelligence model.
  2. In claim 1, The work is, It includes at least one of path navigation, object recognition, map updating, given tasks, natural language understanding and generation, and content understanding and generation, and The mission is, A method for performing a task of an autonomous robot characterized by including at least one of delivery, patrolling, cleaning, and sensing.
  3. In claim 1, Support is, A method for performing a task by an autonomous robot, characterized by performing a task that the autonomous robot cannot directly perform or a task where the accuracy of the performance is expected to be below a standard even if it is directly performed, and providing the result of the performance.
  4. In claim 3, The tasks supported in the first support stage are, It is a task with higher complexity, difficulty, or a larger-scale artificial intelligence model than the task performed during the execution phase, and The tasks supported in the second support phase are, A method for performing a task by an autonomous robot, characterized by the task being more complex, difficult, or requiring a larger-scale artificial intelligence model than the task supported in the first support stage.
  5. In claim 3, The tasks supported in the first support stage are, It is a task in which the similarity between the input data to be processed and the previous data is less than the first similarity, and The tasks supported in the second support phase are, A method for performing a task by an autonomous robot, characterized by the similarity between input data to be processed and previous data being less than a second similarity, which is lower than a first similarity.
  6. In claim 3, The tasks supported in the first support stage are, It is a task whose execution result during the execution phase was determined to be a failure, and The tasks supported in the second support phase are, A method for performing a task by an autonomous robot, characterized in that the result of performing the task in the first support stage is also found to be a failure.
  7. In claim 3, The tasks supported in the first support stage are, It is a task that must be processed during the first time period, and The tasks supported in the second support phase are, A method for performing a task of an autonomous robot characterized by the task being to be processed in a second time period.
  8. In claim 3, The tasks supported in the first support stage are, The weather condition is a task that must be processed in the first state, and The tasks supported in the second support phase are, A method for performing a task of an autonomous robot characterized by the fact that the weather condition is a task that must be processed in a second state.
  9. In claim 3, The tasks supported in the first support stage are, It is a task that must be processed in a situation where the spatial density is at least the first density, and The tasks supported in the second support phase are, A method for performing a task of an autonomous robot, characterized by the fact that the task must be processed in a situation where the spatial density is higher than the first density, or higher than the second density.
  10. Autonomous robot performing tasks with a first artificial intelligence model; Edge server supporting task execution of autonomous robots with a second artificial intelligence model; A task execution system for an autonomous robot, characterized by including a cloud server that supports the robot's task execution with a third artificial intelligence model.
  11. A first support step in which an edge server supports the task execution of an autonomous robot that performs a task using a first artificial intelligence model by using a second artificial intelligence model; A method for supporting task execution of an autonomous robot, characterized by including a second support step in which a cloud server supports the task execution of the robot using a third artificial intelligence model.
  12. An edge server that supports the task execution of an autonomous robot performing a task with a first artificial intelligence model using a second artificial intelligence model; A task performance support system for an autonomous robot, characterized by including a cloud server that supports the robot's task performance using a third artificial intelligence model.

Description

Edge-based intelligence support method for performing complex tasks of autonomous robots The present invention relates to artificial intelligence-based robot control, and more specifically, to an intelligent support method for performing complex tasks of an autonomous robot operating based on artificial intelligence. Existing intelligent robot systems are structured such that dedicated intelligence models are mounted on the robot in the form of on-device AI to perform defined tasks in limited locations or environments. While they can demonstrate operational performance optimized for specific tasks, they are limited in performing other tasks. Furthermore, since the available computing resources for on-device AI-based intelligent robots are limited, the majority are equipped with lightweight AI models optimized for specific tasks. As a result, executing high-performance models such as LLM is difficult, making it challenging to perform new or complex tasks that deviate from pre-learned patterns. FIG. 1 is a complex task performance/support system for an autonomous action robot according to one embodiment of the present invention, FIG. 2 is a method for performing task substitution of an autonomous action robot based on task characteristics, according to another embodiment of the present invention. FIG. 3 is a method for performing task substitution of a data change-based autonomous action robot according to another embodiment of the present invention. FIG. 4 is a method for performing task substitution of an autonomous action robot based on task success or failure according to another embodiment of the present invention. FIG. 5 is a method for performing task substitution of a time-based autonomous action robot according to another embodiment of the present invention. FIG. 6 is a method for performing task substitution of a weather condition-based autonomous action robot according to another embodiment of the present invention. FIG. 7 is a method for performing task substitution of an illuminance-based autonomous action robot according to another embodiment of the present invention. FIG. 8 is a method for performing task substitution of a spatial density-based autonomous action robot according to another embodiment of the present invention. The present invention will be described in more detail below with reference to the drawings. An embodiment of the present invention presents an edge/cloud-based intelligence support method for performing complex tasks by an autonomous robot. This technology involves deploying and updating artificial intelligence models required when an autonomous robot performs various tasks via edge computing, or supporting the task execution itself through the edge or cloud. FIG. 1 is a diagram illustrating the configuration of a complex task execution/support system for an autonomous robot according to an embodiment of the present invention. In an embodiment of the present invention, the autonomous robot receives support from the edge and the cloud when performing complex tasks. A complex task performance/support system for an autonomous robot according to an embodiment of the present invention is configured to include, as illustrated, a cloud server (100), an edge server (200), and an autonomous robot (Device, 300). The autonomous robot (300) is a robot system that performs complex tasks through autonomous judgment and action to provide specific services in a designated area. Complex tasks for providing services include path navigation, object recognition, map updating, and given detailed tasks. Route navigation, object recognition, and map updates are the fundamental tasks involved in performing specific missions. These specific missions are determined by the type of service and may include item delivery, area patrolling, area cleaning, and area sensing; of course, depending on the service, other tasks may also be included. To perform complex tasks through autonomous judgment and action, the autonomous robot (300) utilizes an artificial intelligence model. That is, it performs path navigation, object recognition, map updates, and detailed tasks based on artificial intelligence. Meanwhile, since the resources of the autonomous robot (300) are limited in that it is a mobile platform requiring movement, the artificial intelligence model must be an ultra-lightweight model, and the range of tasks that can be performed is also limited. Accordingly, to support the performance of complex tasks by the autonomous robot (300), a cloud server (100) and an edge server (200) are operated. In FIG. 1, only one cloud server (100) and one edge server (200) are shown, but this is for convenience of illustration; in reality, multiple servers are operated. In particular, in the case of the edge server (200), multiple edge servers exist within the service area of the autonomous robot (300), so the autonomous robot (300) can receive support for task performance from the nearest edge server (200). Support for