Robotic Assembly Task Sequencing With GUI-Generated Directed Graphs
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Solution Overview
Problem
Configuring robotic systems to perform varying sequences of assembly tasks is time-consuming and often requires skilled labor, as existing methods lack user-friendly interfaces for defining task orders.
Innovation Solution
A system and method utilizing a graphical user interface that allows users to define task sequences by selecting components and operations on a displayed work scene, generating a directed graph to control robotic systems, and enabling reconstruction of the graph during operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional programming methods are used to configure robotic systems for different assembly tasks, then the robotic system can perform precise tasks, but the configuration process becomes time-consuming and requires highly skilled labor
Solution Approach 1:
The patent uses visual copying of task sequences through graphical representation. Users can see task sequences displayed as graphs or diagrams and replicate or modify them for different devices, eliminating the need to program each sequence from scratch. The system captures images of work scenes and reconstructs directed graphs to create reusable task templates.
Solution Approach 2:
The patent introduces an intermediary visual interface (graphical user interface displaying directed graphs) between the user and the robotic system's task configuration. This intermediary layer allows users to define task sequences by selecting and arranging visual elements rather than writing complex code, bridging the gap between user intent and robotic execution.
2Ease of operation
If traditional programming methods are used to configure robotic systems, then tasks can be performed accurately, but highly skilled labor is required which increases operational complexity
Solution Approach 1:
The patent enables self-service configuration where the system automatically generates directed graphs and task sequences from visual inputs. The robotic system can capture images of work scenes, automatically reconstruct the task sequence as a directed graph, and configure itself without requiring skilled programmers. This transfers the intelligence from the operator to the system.
Solution Approach 2:
The patent replaces the mechanical process of manual programming with an automated visual recognition and graph construction system. Instead of manually coding task sequences, the system uses image processing and automated graph algorithms to generate task configurations, substituting human cognitive labor with automated computational processes.
3Adaptability or versatility
If the same robot is used to assemble different electronic devices, then resource utilization is improved, but the ability to adapt to different task sequences decreases
Solution Approach 1:
The patent implements dynamic task sequence representation using directed graphs that can be easily modified and reconstructed. The system can capture the current work scene, dynamically generate or update the directed graph representation, and immediately apply it to the robotic system. This dynamic approach allows rapid adaptation to different devices without fixed, rigid programming.
Solution Approach 2:
The patent performs preliminary action by pre-defining task sequences as reusable directed graphs that can be stored and quickly loaded. The system can prepare task sequences in advance for different device types, so when a new device needs assembly, the appropriate pre-configured graph can be rapidly reconstructed and applied, minimizing reconfiguration time.
Data Source
AI summary
One embodiment can provide a method and system for configuring a robotic system. During operation, the system can present to a user on a graphical user interface an image of a work scene comprising a plurality of components and receive, from the user, a sequence of operation commands. A respective operation command can correspond to a pixel location in the image. For each operation command, the system can determine, based on the image, a task to be performed at a corresponding location in the work scene and generate a directed graph based on the received sequence of operation commands. Each node in the directed graph can correspond to a task, and each directed edge in the directed graph can correspond to a task-performing order, thereby facilitating the robotic system to perform a sequence of tasks based on the sequence of operation commands.