Camera-Guided Seat Track Loading for Distortion Alignment
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Solution Overview
Problem
The existing methods for loading and unloading seat tracks using robots often result in misalignment due to slight distortion of the seat tracks during gripping, leading to potential collisions and reduced production efficiency.
Innovation Solution
A seat track loading/unloading system and method that utilize an unmanned transport vehicle and a seat track loading/unloading robot, equipped with cameras and processors, to accurately correct the position of the seat track by comparing captured images with reference images and calculating correction values based on mounting holes and pins.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a robot grips the seat track for automated loading/unloading, then automation level increases, but the seat track may be slightly distorted leading to misalignment
Solution Approach 1:
The system performs preliminary actions by capturing images of the seat track's mounting holes and pins before loading, calculating correction values in advance, and pre-positioning the seat track on the pallet with corrected coordinates. This preliminary measurement and correction process prevents distortion-related misalignment issues during the actual loading operation.
Solution Approach 2:
The system implements feedback by capturing images of the seat track's mounting features, comparing actual positions with reference positions, calculating correction values based on the deviations detected, and using these correction values to adjust the loading position. This closed-loop feedback mechanism compensates for distortion effects and ensures precise loading settlement position.
2Manufacturing precision
If manual loading method is used, then positioning accuracy is maintained, but labor intensity increases and automation is reduced
Solution Approach 1:
The system enables self-service by equipping the robot with imaging and calculation capabilities to automatically detect seat track positions, calculate correction values, and adjust loading coordinates without human intervention. The robot independently performs measurement, computation, and correction operations, achieving both high automation and precision simultaneously.
Solution Approach 2:
The system replaces manual mechanical positioning with an automated optical-mechanical system. Instead of relying on human operators to visually position the seat track, the system uses cameras to capture mounting hole and pin positions, processes images to calculate correction values, and automatically adjusts the robot's loading position based on these computational results.
3Manufacturing precision
If correction system is added to detect and correct position, then loading precision is improved, but device complexity increases
Solution Approach 1:
The system achieves multi-functionality by integrating imaging, measurement, calculation, and correction capabilities into a single comprehensive loading system. The same robot and imaging system used for basic loading operations are also employed for precision measurement and correction, eliminating the need for separate dedicated correction equipment and reducing overall system complexity.
Solution Approach 2:
The system introduces an intermediary computational layer that processes image data and generates correction values. This intermediary processing step acts as a bridge between the simple imaging function and the precise positioning requirement, translating visual information into actionable correction coordinates without requiring complex mechanical adjustment mechanisms.
Data Source
AI summary
Disclosed is a seat track loading/unloading system including a cart where a seat track is loaded and unloaded. an unmanned transport vehicle configured to carry the cart. a seat track loading/unloading robot on which a gripper is mounted to unload the seat track from the cart, and a conveyor on which the seat track is loaded.