Robotic Gripper Vision System for Unstructured Object Handling
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Solution Overview
Problem
Designing a gripper that can reliably grip objects of varying shapes and sizes from an unstructured environment, especially when they are among other objects or obstructions, is challenging due to the need for prior knowledge of object shapes and orientations.
Innovation Solution
A method involving image processing to calculate masks for background, object, gripper, and gripping areas, determining overlapping areas, and selecting a gripping location based on quality factors to ensure effective gripping, even for objects larger than the gripper opening with protruding handles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a generic gripper design is used to handle objects of varying shapes and sizes, then the gripper can be applied to unstructured environments, but the gripping reliability decreases
Solution Approach 1:
The system performs preliminary actions by calculating background masks, object masks, gripper masks, and gripping area masks before selecting a gripping location. These preliminary calculations enable the generic gripper to adapt to various objects while maintaining reliability through systematic pre-analysis of the gripping scenario.
Solution Approach 2:
The invention changes parameters by calculating quality factors based on different mask overlaps and selecting gripping locations that optimize these parameters. This allows the generic gripper to adapt to varying object shapes and sizes while maintaining reliable gripping through quantitative parameter optimization.
2Measurement precision
If the robot system uses complex image processing and mask calculations to determine gripping locations, then gripping accuracy improves, but processing time increases
Solution Approach 1:
The image processing is segmented into distinct mask calculations (background mask, object mask, gripper mask, gripping area mask), allowing parallel processing and reducing overall computation time while maintaining high precision in gripping location determination.
Solution Approach 2:
The system performs partial actions by calculating only the necessary mask overlaps relevant to gripping locations rather than analyzing entire images in detail, reducing processing time while maintaining sufficient precision for gripping decisions.
Data Source
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AI summary
According to one aspect of the invention, there is provided a method com- prising: obtaining at least one image comprising at least one object; analysing the at least one image to determine at least one gripping location to grip an object; selecting a gripping location from the at least one gripping lo- cation based on a predetermined criterion; and issuing at least one instruction to a gripper to grip the object at the selected gripping location.