Self-Programming Robotic Visual Inspection for Unknown Fixtures
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Solution Overview
Problem
In manufacturing, early detection of defects in parts is challenging, especially in complex geometries like metal bond layup, where visual inspection is difficult before bonding, leading to costly failures later in the process.
Innovation Solution
A robotic self-learning visual inspection system that generates its own path and inspection routine, using a controller with non-volatile memory and multiple instruments like cameras, distance sensors, and a touch probe to create 3D models of parts and identify features autonomously, allowing for automated inspection and learning of new parts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional preprogrammed inspection paths are used, then inspection reliability is improved, but robot collisions occur and adaptability to new parts deteriorates
Solution Approach 1:
The robotic system performs self-learning by autonomously capturing images of new parts, identifying features through image processing, and generating inspection paths without human intervention. The system serves itself by automatically adapting to new part geometries and configurations, eliminating the need for manual reprogramming while maintaining inspection reliability through consistent automated execution.
Solution Approach 2:
The system performs preliminary learning actions by capturing images and identifying features before actual inspection begins. This preliminary phase allows the robot to build a knowledge base of part features and generate inspection paths in advance, ensuring reliable inspection execution while adapting to new parts without collisions.
2Adaptability or versatility
If manual visual inspection is used, then adaptability to complex geometries is improved, but inspection reliability and consistency deteriorate
Solution Approach 1:
The system replaces manual mechanical inspection with automated robotic inspection equipped with sensors and image processing capabilities. The robotic system can adapt to complex geometries through automated image capture and analysis, eliminating human limitations while maintaining consistent, reliable inspection results through programmed execution and automated decision-making.
Solution Approach 2:
The system transitions from two-dimensional visual inspection to three-dimensional spatial understanding by capturing multiple images from different angles and positions. This dimensional enhancement allows the robotic system to comprehend complex part geometries fully, achieving both adaptability to intricate shapes and reliable, consistent inspection through automated analysis.
3Measurement precision
If extensive preprogramming is performed, then inspection precision is improved, but productivity and setup time deteriorate
Solution Approach 1:
The robotic system performs self-learning by autonomously capturing images, identifying features, and generating inspection paths without human intervention. This self-service capability eliminates time-consuming manual preprogramming while maintaining high inspection precision through automated image processing and feature recognition algorithms.
Solution Approach 2:
The system performs preliminary learning actions rapidly by capturing images and generating inspection paths automatically before production begins. This automated preliminary phase maintains measurement precision through sophisticated image processing while dramatically reducing setup time and improving overall productivity compared to manual preprogramming.
Data Source
AI summary
A robotic self-learning visual inspection method includes determining if a fixture on a component is known by searching a database of known fixtures. If the fixture is unknown, a robotic self-programming visually learning process is performed that includes determining one or more features of the fixture and providing information via a controller about the one or more features in the database such that the fixture becomes known. When the fixture is known, a robotic self-programming visual inspection process is performed that includes determining if the one or more features each pass an inspection based on predetermined criteria. A robotic self-programming visual inspection system includes a robot having one or more arms each adapted for attaching one or more instruments and tools. The instruments and tools are adapted for performing visual inspection processes.