Smart Vision Cobot Welding Trajectory Correction for Part Misalignment
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Solution Overview
Problem
Current cobot welding systems lack vision guidance, leading to misalignment and inefficiency in repeated welding tasks due to the need for manual programming and adjustment of welding trajectories, especially when parts are repositioned, and existing vision systems are costly and not widely available.
Innovation Solution
A vision-guided cobot welding system utilizing a compact, high-resolution camera with multi-color light source and dust protection, equipped with computer vision algorithms to automatically correct displacement errors and calculate new welding trajectories for accurate repeatable tasks, significantly reducing programming time and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a laser-based guided vision system is used for welding seam finding and tracking, then welding precision is improved, but system cost increases significantly (more than 20K per unit)
Solution Approach 1:
The patent replaces expensive laser-based vision systems with a low-cost 2D camera system. The 2D camera captures images that are then processed through algorithms to extract welding trajectory information, achieving comparable precision at a fraction of the cost. This substitution of expensive equipment with cheaper alternatives while maintaining functionality directly addresses the cost issue.
Solution Approach 2:
The patent substitutes the optical-mechanical laser guidance system with a 2D vision system combined with computer algorithms. Instead of using laser lines and mechanical scanning, the system uses 2D image capture and digital processing to achieve welding trajectory guidance, reducing hardware complexity and cost while maintaining welding precision.
2Device complexity
If manual teaching of welding trajectory is used, then system cost is reduced, but programming time and operator intervention increase significantly
Solution Approach 1:
The vision system enables the welding system to automatically determine its own trajectory by capturing images of the workpiece and processing them through algorithms. The system self-corrects for part positioning errors and automatically generates welding paths without requiring manual teaching, thereby reducing programming time while maintaining cost-effectiveness.
Solution Approach 2:
The 2D camera captures real-time images of the workpiece position, and the control system processes these images to detect part placement variations. This feedback loop allows the system to automatically adjust the welding trajectory based on actual part position, eliminating the need for manual re-programming when parts are repositioned.
3Ease of operation
If cobot works with human operators manually adjusting pose, then ease of operation is improved, but welding precision decreases due to inability to automatically correct part position errors
Solution Approach 1:
The vision system continuously monitors the workpiece position and provides feedback to the control system. When part positioning errors are detected, the system automatically calculates correction values and adjusts the welding trajectory accordingly, maintaining welding precision while keeping the cobot easy to operate through manual pose adjustment.
Solution Approach 2:
The patent replaces manual visual inspection and adjustment with an automated 2D vision system that automatically detects part position and calculates trajectory corrections. This substitution maintains the ease of manual cobot operation while eliminating the precision losses associated with manual error detection and correction.
Data Source
AI summary
A compact vision-sensing device for a robotic welding arm, having a high-resolution camera, a multi-color light source configured to have multi-color selectivity, and a means of dust and welding fume protection configured to automatically close and protect the high-resolution camera and multi-color light source during a welding operation.