Robotic Cable Connector Insertion Using Vision-Based Alignment
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Solution Overview
Problem
Existing methods for assembling modular cable connectors are inefficient and prone to human error, requiring manual insertion of cable insert modules into module retainers.
Innovation Solution
A robotic insertion system is used to automate the assembly of modular cable connectors, employing an end effector to hold a cable insert module and a camera system with laser alignment to capture images, process them to identify a segmented image region and virtual plane, and move the module to a precise alignment and insertion pose.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual insertion methods are used for assembling modular cable connectors, then operational flexibility is maintained, but assembly speed and accuracy deteriorate
Solution Approach 1:
The patent replaces manual mechanical insertion operations with an automated robotic system that uses computer vision guidance. The robotic arm with end effector automatically positions and inserts cable insert modules into module retainers, substituting human manual operations with automated mechanical systems guided by image processing and laser alignment technology.
2Manufacturing precision
If manual insertion methods are used, then system complexity remains low, but assembly precision and error rates worsen
Solution Approach 1:
The patent introduces an intermediary computer vision system consisting of cameras and laser alignment tools that mediate between the robotic system and the assembly task. This intermediary layer captures images, processes them to identify module retainer positions, and guides the robotic arm for precise insertion, thereby achieving high precision without directly increasing the complexity of the mechanical insertion mechanism itself.
3Productivity
If automated robotic insertion is implemented, then productivity improves, but initial system complexity increases
Solution Approach 1:
The patent segments the automated assembly system into distinct functional modules: image capture subsystem (cameras), image processing subsystem (computer vision algorithms), laser alignment subsystem, robotic control subsystem, and mechanical insertion subsystem. This segmentation allows each component to be optimized independently and simplifies the overall system architecture by breaking down the complex automated system into manageable, specialized modules.
Data Source
AI summary
In an example, a method for assembly of a modular cable connector includes, at an end effector of a robotic insertion system, holding a cable insert module for insertion into a module slot of a module retainer. Two or more images are captured of the module retainer. Image processing is performed to identify a segmented image region corresponding to the module retainer and a virtual plane parallel to a face of the module retainer. The end effector is moved to an alignment pose determined based, at least in part, on the segmented image region and the virtual plane. The end effector is moved from the alignment pose toward an insertion pose. Upon insertion of the cable insert module into the module slot of the module retainer, the cable insert module is released from the end effector.