Connector Segmentation for Accurate Robotic Wire Insertion
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Solution Overview
Problem
Existing methods for inserting wires into connectors lack accuracy and speed due to sensitivity to ambient lighting conditions and require manual tuning of vision parameters, making them inefficient and adaptable to various connector types.
Innovation Solution
A robotic system with a camera system and controller that generates images of connectors, creates segmentation masks, and applies thresholding to accurately insert wires into connectors, reducing the need for manual tuning and improving adaptability to different lighting conditions and connector types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional vision systems are used for wire insertion, then the system can operate with simple hardware, but the accuracy and reliability of wire insertion deteriorates due to sensitivity to ambient lighting conditions
Solution Approach 1:
The vision system processes the connector image by segmenting it into multiple masks: initial mask identifying connector region, segmentation mask with edges, and final mask with recovered pixels. This multi-stage segmentation approach improves measurement precision by systematically isolating the connector from background and handling lighting variations at each stage.
Solution Approach 2:
The patent replaces traditional mechanical vision parameter tuning with an automated image processing system that uses algorithmic mask generation and thresholding. This substitution eliminates the need for manual calibration and reduces sensitivity to ambient lighting by using computational methods instead of mechanical adjustment.
2Adaptability or versatility
If manual tuning of vision parameters is performed, then the system can be adapted to specific connector types, but the productivity and speed of wire insertion deteriorates due to time-consuming calibration
Solution Approach 1:
The vision system performs self-calibration by automatically generating segmentation masks and applying thresholding to recover connector pixels. The system adapts to different connector types through automated image processing rather than manual tuning, maintaining versatility while eliminating calibration time and improving productivity.
3Manufacturing precision
If image processing is performed for each wire insertion, then the system can maintain high precision, but the computational redundancy increases and slows down the insertion speed
Solution Approach 1:
The system performs preliminary image processing by generating the final mask before wire insertion begins. This mask, which contains the segmented connector region with recovered pixels, can be reused for multiple wire insertions, eliminating the need to repeat computationally intensive processing for each wire and reducing time loss while maintaining precision.
Data Source
AI summary
A method for inserting a wire. An image of a connector is generated using a camera system connected to an end effector. The end effector is at a connector pose facing the connector. A region in the image encompassing the connector is selected. An initial mask is created using the image and the region. The initial mask comprises a background region and a connector region. A segmentation mask is created using the initial mask and the image, wherein the segmentation mask includes edges for the connector. Thresholding is applied to the segmentation mask to recover pixels for the connector and generate a final mask. The final mask is used to insert the wire into the connector.