Robotic Arm Defect Inspection With Motion-Optimized Object Rotation
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Solution Overview
Problem
Existing defect detection methods in manufacturing are inefficient due to the need for manual inspection of unseen areas by operators and the processing of voluminous data from multiple cameras, which are computationally intensive and time-consuming.
Innovation Solution
A method involving a robot arm that computes a motion-optimized path to rotate an object, capturing images with a camera at each rotation, and performing defect detection on these images to notify operators of defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple cameras are used to capture images for defect detection, then the coverage of visible surfaces is improved, but the volume of data to be processed increases significantly
Solution Approach 1:
The patent extracts only the essential information needed for defect detection by processing images from a single camera systematically. Instead of capturing all surfaces with multiple cameras, the method processes images from one camera to identify defects, thereby reducing the volume of data while maintaining detection effectiveness.
Solution Approach 2:
The patent applies partial action by inspecting only the surfaces that are visible to the single camera at any given time, rather than attempting to capture all surfaces simultaneously with multiple cameras. This selective approach reduces data volume while still achieving comprehensive inspection through sequential imaging.
2Reliability
If manual visual inspection by operators is performed, then the detection of defects in hidden areas is improved, but the productivity and processing time are reduced
Solution Approach 1:
The system performs self-service by automatically capturing and processing images of the part surfaces using a single camera, eliminating the need for manual inspection. The automated image processing system independently completes the inspection task that would otherwise require operator intervention, thereby maintaining reliability while significantly improving productivity.
Solution Approach 2:
The patent replaces the mechanical action of manual visual inspection with an automated optical and computational system. Instead of operators physically examining parts, the system uses a camera and image processing algorithms to automatically detect defects, substituting human labor with an automated technological system that is both faster and equally reliable.
3Area of stationary object
If voluminous data from multiple cameras is processed, then the inspection coverage is improved, but the computational intensity and time consumption increase
Solution Approach 1:
The patent extracts only the necessary computational processing from the total available data by focusing on images from a single camera. Instead of processing voluminous data from multiple cameras, the system processes a manageable subset of images that are sufficient for defect detection, thereby reducing computational intensity while maintaining adequate inspection coverage.
Solution Approach 2:
The patent applies partial computational action by processing only the images that are actually needed for defect detection, rather than processing all captured data from multiple cameras. This selective processing approach reduces computational load while still achieving comprehensive inspection through strategic image selection and processing.
Data Source
AI summary
A method for object defect detection. The method may include receiving an object on a production line; computing, by a processor, a motion optimized path for a robot arm, wherein the motion optimized path comprises a path for performing a sequence of rotations by the robot arm on the object for image capturing; using the robot arm to grasp the object and moving the robot arm according to the motion optimized path to rotate the object based on the sequence of rotations; capturing, by a camera, a plurality of images of the object while the object is being rotated; performing, by the processor, defect detection on the plurality of images of the object to determine object defect; and for object defect being detected, issuing, by the processor, a defect notification to an operator of the production line.