3D Robot Station Localization for Fast Handling Setup
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Solution Overview
Problem
Current handling device programming methods require expertise and are time-consuming, especially for multi-axis robots, as they often need manual initialization and precise station recognition, which can be labor-intensive and prone to errors.
Innovation Solution
A handling arrangement with a multi-axis robot equipped with a 3D monitoring sensor and localization module that automatically recognizes stations using machine learning-based training data, allowing for rapid initialization and precise positioning without the need for expert intervention, utilizing a user-friendly interface for task definition and path planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual programming and initialization methods are used for handling devices, then programming can be performed with simple equipment, but the process becomes time-consuming and requires expert knowledge
Solution Approach 1:
The patent replaces manual mechanical programming methods with an automated optical system. A monitoring sensor captures images of the work area, and a localization module automatically processes these images to identify stations and generate coordinate data, eliminating the need for manual teaching and expert programming knowledge.
Solution Approach 2:
The handling device performs self-initialization through automated station recognition. The system independently captures images, processes them to identify station positions, and generates the necessary coordinate information without requiring external expert intervention or manual programming.
2Productivity
If automated station recognition is implemented, then initialization time is reduced, but system complexity increases due to additional sensors and processing modules
Solution Approach 1:
The monitoring sensor serves multiple functions: it captures images for station recognition, provides visual feedback for verification, and supports the localization module in generating coordinate data. This multi-functionality reduces the need for separate dedicated components, thereby limiting the increase in system complexity.
Solution Approach 2:
The localization module acts as an intermediary that processes images from the monitoring sensor and generates coordinate information for the control module. This intermediary layer simplifies the overall system architecture by centralizing the complex image processing and coordinate transformation tasks in a dedicated module.
3Measurement precision
If expert programming is required for handling devices, then precise control can be achieved, but the operation becomes labor-intensive and prone to human error
Solution Approach 1:
The patent replaces manual expert programming with automated image-based station recognition. The monitoring sensor captures precise spatial information, and the localization module processes this data to generate accurate coordinate information, eliminating human error while maintaining positioning precision.
Solution Approach 2:
The system uses visual feedback from the monitoring sensor to verify station recognition and coordinate generation. This feedback mechanism ensures positioning accuracy by allowing the system to confirm that stations have been correctly identified and positioned before executing handling operations.
Data Source
Figure 1
Figure 2a~2b
Figure 3
AI summary
The invention relates to a handling assembly (1) comprising a handling device (2) for carrying out at least one work step with and/or on a workpiece (6) in a working region (3) of the handling device (2), wherein stations (5, 5a-5f) are provided in the working region (3). The handling assembly comprises at least one monitoring sensor (7) for optically monitoring the working region (3) and for providing monitoring data and a localizing module (9), said localizing module (9) being designed to detect the stations (5, 5a-5f) and determine a respective station position (11) for each station (5, 5a-5f).