Robot Workpiece Grasping With Fast Image Area Extraction
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Solution Overview
Problem
Conventional image processing for recognizing workpieces in a production line is time-consuming, hindering productivity in factory automation.
Innovation Solution
A robot system with an image processing apparatus and control portion that uses deep learning-based object detection and pattern matching to quickly identify and grasp workpieces, employing multiple cameras and a robot arm to optimize the image processing and grasping process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing methods are used for workpiece recognition, then measurement precision is achieved, but processing time increases significantly
Solution Approach 1:
The patent segments the image processing task into distinct stages: candidate workpiece area extraction followed by detailed pattern matching. This segmentation allows the system to first identify potential workpiece locations efficiently, then apply more computationally intensive recognition only to relevant regions, thereby reducing overall processing time while maintaining accuracy.
Solution Approach 2:
The patent performs preliminary extraction of candidate workpiece areas before conducting full pattern matching. By pre-identifying regions that contain workpieces based on basic image features, the system prepares the data in advance for more efficient detailed processing, avoiding the need to perform comprehensive pattern matching on the entire image.
2Productivity
If deep learning-based object detection is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary step between simple area extraction and final pattern matching recognition. The candidate workpiece area extraction acts as a mediator that filters and prepares data for the subsequent recognition stage, enabling the use of more sophisticated algorithms without directly overwhelming the system with full-image processing complexity.
Solution Approach 2:
The processing system is segmented into multiple functional modules: area extraction unit, pattern matching unit, and workpiece information extraction unit. This modular segmentation allows each component to be optimized independently and facilitates easier maintenance and adjustment of the overall system complexity.
3Measurement precision
If multiple cameras are used for comprehensive workpiece detection, then measurement precision is enhanced, but device complexity increases
Solution Approach 1:
The patent employs cameras that serve multiple functions: capturing workpiece images for position detection, determining posture information, and identifying candidate areas. This multi-functionality allows the system to achieve comprehensive measurement precision with a relatively small number of camera units, reducing overall device complexity.
Solution Approach 2:
The image capture and processing system is segmented into specialized units: image capture apparatus, area extraction unit, and pattern matching unit. Each unit handles specific aspects of the detection task, allowing the multiple cameras to be integrated systematically without creating overwhelming system complexity.
Data Source
AI summary
A robot system includes a robot, an image capture apparatus, an image processing portion, and a control portion. The image processing portion is configured to specify in an image of a plurality of objects captured by the image capture apparatus, at least one area in which a predetermined object having a predetermined posture exists, and obtain information on position and/or posture of the predetermined object in the area. The control portion is configured to control the robot, based on the information on position and/or posture of the predetermined object, for the robot to hold the predetermined object.