Robotic Sewing Path Adjustment Using Vision Feedback
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Solution Overview
Problem
The process of making sewn products still relies heavily on human labor, leading to high labor costs, inaccuracies, and safety issues, and previous attempts at automation in developed countries have been unsuccessful.
Innovation Solution
An automated sewing robot system comprising a manufacturer premise with a motion profiling module, product construction module, and path generation module, along with a sewing device, fabric mover, and vision device, which uses computer-aided design files to generate product construction files and sewing paths, minimizing human intervention and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If human labor is used to cut and sew fabrics, then flexibility and adaptability are maintained, but labor costs increase and accuracy decreases
Solution Approach 1:
The patent replaces manual mechanical sewing operations with an automated robotic system that uses computer vision and automated cutting/sewing mechanisms. The robot system eliminates human hands from direct contact with sharp tools while maintaining precise control over cutting and sewing operations through programmed motion paths and force control.
Solution Approach 2:
The system enables the fabric and product to guide the sewing process through computer vision tracking. The vision system continuously detects fabric edges, seams, and alignment features, allowing the robot to automatically adjust its path without human intervention. The fabric itself provides the reference information needed for precise positioning.
2Productivity
If automation is implemented to reduce labor costs, then productivity increases, but device complexity increases
Solution Approach 1:
The robotic system is designed to perform multiple functions: vision detection, path planning, automated cutting, automated sewing, and quality inspection. A single integrated robot platform handles various sewing operations (straight seams, curves, topstitching, binding) and can adapt to different fabric types and product designs through software reconfiguration rather than requiring separate specialized machines.
Solution Approach 2:
The patent introduces a computer vision system as an intermediary between the fabric and the robot controller. The vision system captures images, processes them to extract geometric features, and translates them into robot motion commands. This intermediary layer simplifies the control architecture by handling the complex task of interpreting fabric geometry and converting it into executable sewing paths.
3Reliability
If human operators perform sewing tasks, then adaptability to design changes is maintained, but safety issues arise
Solution Approach 1:
The patent replaces human operators with an automated robotic system that eliminates safety risks associated with human contact with sharp cutting tools and moving sewing mechanisms. The robot system maintains reliability through programmed safety protocols, emergency stop functions, and controlled force application during fabric manipulation and sewing operations.
4Manufacturing precision
If manual sewing processes are used, then equipment simplicity is maintained, but labor costs and human error increase
Solution Approach 1:
The system implements continuous feedback through the computer vision system that monitors fabric position, edge alignment, and seam quality in real-time. The vision data feeds back to the robot controller, which adjusts motion paths and sewing parameters dynamically to maintain precision. This closed-loop control compensates for fabric variability and positioning errors automatically.
Solution Approach 2:
The robot system performs preliminary actions including fabric inspection, path planning, and positioning before the actual sewing operation begins. The vision system pre-processes fabric images to identify features and calculate optimal sewing paths, allowing the robot to approach and execute sewing tasks with predetermined precision rather than reacting during the operation.
Data Source
AI summary
A sewn product making apparatus such as a sewing robot can be used to produce a variety of products over a broad range of sizes, shapes or materials. Various examples are provided related to the automation of sewing robots, and the making of sewn products. In one example, among others, a system can generate a product making path using a product construction file, and instruct a sewing device and fabric mover(s) to automatically sew the product based upon the product making path. The product making path can be modified when a deviation is detected, and the sewing adjusted based upon the modified product making path. The product construction file can be generated using information from a computer aided design associated with the product.