Robot Camera Lens Dirt Detection Using Hand Motion Cues
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Solution Overview
Problem
Current robot devices fail to distinguish between dirt and scratches on camera lenses and hands, leading to inefficient operation and potential contamination of objects during grasping tasks.
Innovation Solution
A robot device equipped with a controller that processes images to differentiate between dirt and scratches on camera lenses and hands by using reference images and correlation analysis, allowing for autonomous detection and cleaning of these issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a robot device compares multiple images in the same area to detect dirt on a camera lens, then dirt detection capability is improved, but the device cannot distinguish between dirt and scratches on the lens
Solution Approach 1:
The patent applies dynamics by moving the hand to different positions and capturing multiple images. By comparing images taken when the hand is at different positions, the system can distinguish between dirt on the lens (which remains stationary in the image) and scratches on the hand (which move with the hand). This dynamic approach transforms a static detection problem into a dynamic one that can be solved through motion-based differentiation.
Solution Approach 2:
The patent uses the hand as an intermediary object to detect lens dirt. Instead of directly analyzing the lens surface, the system photographs the hand multiple times at different positions. The hand serves as a mediator that allows indirect detection of lens contamination by observing how dirt on the lens appears consistently across multiple hand images while scratches on the hand move with the hand's motion.
2Productivity
If a robot device uses a camera to detect objects and perform grasping tasks, then operational capability is improved, but dirt or scratches on the lens significantly affect object detection and recognition ability
Solution Approach 1:
The patent implements self-service by enabling the robot to automatically detect and identify lens dirt and scratches without human intervention. The system uses its own camera to photograph the hand at multiple positions, automatically compares the images, and autonomously determines the presence and location of dirt or scratches on the lens. This self-diagnostic capability allows the robot to maintain operational reliability by identifying optical contaminants that would otherwise degrade detection and recognition performance.
3Measurement precision
If a robot device photographs the hand to detect dirt, then dirt detection is enabled, but the device cannot determine whether the dirt is on the lens or on the hand
Solution Approach 1:
The patent resolves the location identification problem through dynamic hand movement. When the hand is moved to different positions, scratches on the hand appear at different locations in the captured images, while dirt on the lens remains at the same position in all images. By analyzing the positional consistency of detected dirt across multiple images, the system can determine whether the contamination is on the stationary lens or on the moving hand.
Data Source
AI summary
Provided is an excellent robot device capable of preferably detecting difference between dirt and a scratch on a lens of a camera and difference between dirt and a scratch on a hand. A robot device detects a site in which there is the dirt or the scratch using an image of the hand taken by a camera as a reference image. Further, this determines whether the detected dirt or scratch is due to the lens of the camera or the hand by moving the hand. The robot device performs cleaning work assuming that the dirt is detected, and then this detects the difference between the dirt and the scratch depending on whether the dirt is removed.