Limp Flat Workpiece Positioning Using Vision-Guided Gripping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Limp flat workpieces, with low elasticity and dimensional instability, are difficult to transfer from a random, irregularly folded state to a defined position for machining or processing, often requiring manual handling or multiple regripping, which is inefficient and unreliable.
Innovation Solution
A method using a positioning device with a camera and machine learning modules to identify grippable edges and determine gripping points for automated handling, allowing the workpiece to be transferred to a defined position efficiently and reliably.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual handling is used to transfer limp flat workpieces from random folded state to defined position, then the workpiece can be positioned reliably, but the process is inefficient and requires significant time
Solution Approach 1:
The patent replaces manual mechanical handling with an automated robotic system that uses vision guidance (camera) and machine learning algorithms to identify workpiece edges and determine gripping points, enabling automated transfer while maintaining reliability through intelligent control
Solution Approach 2:
The system enables the workpiece to essentially position itself by identifying its own edges and features through the camera and machine learning module, which automatically determine optimal gripping points without human intervention, allowing the robotic gripper to adapt to any random initial state
2Manufacturing precision
If multiple regripping operations are performed to transfer the workpiece, then the workpiece can be positioned accurately, but the process becomes complex and time-consuming
Solution Approach 1:
The system performs preliminary identification of the workpiece edge and gripping points using the camera and machine learning module before the actual gripping action, allowing the robotic gripper to achieve accurate positioning in a single operation without multiple regripping steps
Solution Approach 2:
The patent introduces an intermediary intelligent control system comprising a camera and machine learning module that bridges the gap between the random initial state of the workpiece and the desired final position, enabling direct accurate transfer without complex multiple gripping operations
3Extent of automation
If automated solutions based on multiple regripping are used, then the transfer process can be automated, but the system becomes complex and less reliable
Solution Approach 1:
The patent replaces complex mechanical multiple-regripping mechanisms with a simpler robotic system guided by vision and machine learning, achieving high automation through intelligent software rather than complex mechanical sequences
Solution Approach 2:
The system achieves automation by allowing the machine learning module to autonomously identify workpiece features and determine gripping points without human intervention, simplifying the automated process through intelligent self-determination rather than pre-programmed complex sequences
4Ease of operation
If traditional mechanical processes are used to handle limp flat workpieces, then the handling can be performed, but the process is slow and requires multiple gripping operations
Solution Approach 1:
The patent replaces traditional slow mechanical handling processes with a faster robotic system enhanced by vision guidance and machine learning, which can rapidly identify workpiece features and execute transfer in a single operation
Solution Approach 2:
The system performs rapid preliminary identification of gripping points through the camera and machine learning module before execution, enabling fast single-operation transfer without the time-consuming multiple gripping steps of traditional mechanical processes
Data Source
AI summary
Disclosed is a method of positioning a limp flat workpiece is described, wherein the flat workpiece is provided in a random state on a manipulation surface. Subsequently, a camera image showing the flat workpiece is generated, and a grippable edge of the flat workpiece is identified by extracting characteristic image features of the camera image. Thereafter, a first gripping point for a first gripper and a second gripping point for a second gripper are determined, the second gripping point being spaced apart from the first gripping point. Also disclosed is positioning device for positioning a limp flat workpiece is presented.