Event-driven and asset graph-based robot no-code programming method, system and medium

By importing physical asset models into a 3D simulation environment and generating event-driven asset maps, logical control events are automatically analyzed and generated, solving the problems of messy wiring and difficult signal management in complex production lines caused by traditional robot programming methods, and realizing efficient and intuitive no-code programming.

CN122363685APending Publication Date: 2026-07-10HANGZHOU CORE CONTROL INTELLIGENT TECH CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
HANGZHOU CORE CONTROL INTELLIGENT TECH CO LTD
Filing Date
2026-06-10
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Traditional robot programming methods suffer from problems such as messy wiring, difficult signal management, poor reusability, and difficulty for non-programmers to learn in complex multi-device collaborative scenarios, especially in achieving efficient no-code programming on complex production lines.

Method used

The method adopts an event-driven and asset graph approach. By importing physical asset models into the 3D simulation environment, assigning predefined functional labels to each model, basic action events and compound events are automatically generated. Based on the functional labels and spatial relationships of the assets, an asset graph is constructed. The execution relationships between events are automatically analyzed and logical control events are generated. Finally, the underlying control code is compiled.

Benefits of technology

It enables efficient and intuitive no-code programming, reduces cognitive load, improves automation, supports flexible adaptation to new devices, and the programming process is close to the thinking habits of engineers, avoiding tedious and error-prone manual wiring.

✦ Generated by Eureka AI based on patent content.

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Abstract

This application provides a no-code programming method, system, and medium for robots based on event-driven and asset graphs. The method includes: importing physical asset models into a 3D simulation environment; assigning predefined functional labels to each physical asset model; generating basic motion events for non-robot assets based on functional labels and configuration parameters; generating composite events for robot assets based on process types and key work points defined in an interactive interface; constructing an asset graph based on asset functional labels, assembly relationships in 3D space, and defined work space points; traversing the asset graph and automatically generating logical control events in an event tree; compiling the final constructed event tree and logical relationships to generate underlying control code; and automatically deriving and establishing logical dependencies between events by analyzing the graph relationships composed of asset types, spatial position relationships, and work point identifiers, thereby achieving efficient and intuitive no-code programming.
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