Weld Angle Correction for Faster Multi-Pass Cobot Programming
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Solution Overview
Problem
Programming and setting the precise angles and orientations of a welding or cutting torch for robots can be complex and time-consuming, especially when transferring welding or cutting trajectories between similar weld seams, requiring manual input of numerical offsets which is labor-intensive and prone to errors.
Innovation Solution
A collaborative robot welding system that automatically calculates positional and angle offsets for secondary passes based on recorded root pass data, allowing users to input only physical start and stop positions, and utilizes a weld angle correction tool with a depth camera to adjust torch angles to ideal positions using stereoscopic image data and 3D point cloud processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual positioning and numerical offset input is used for programming robot welding passes, then programming precision can be achieved, but programming complexity and time consumption increase significantly
Solution Approach 1:
The patent replaces manual mechanical positioning and numerical offset input with an automated vision-based system. A camera captures images of the weld seam, and image processing algorithms automatically determine the weld geometry and calculate optimal torch angles, eliminating the need for manual measurement and calculation while maintaining high precision.
Solution Approach 2:
The system enables the robot to automatically program itself by capturing images of the weld seam during teaching mode, processing the images to extract geometric features, and generating welding parameters without human intervention. This self-programming capability reduces programming complexity while maintaining accuracy.
2Ease of operation
If manual positioning of torch angles is performed by users, then flexibility in positioning is maintained, but angle accuracy deviates from ideal positions
Solution Approach 1:
The system uses a camera to capture real-time images of the weld seam and torch position, processes these images to calculate actual torch angles, and provides feedback to automatically adjust the torch to ideal positions. This closed-loop feedback mechanism ensures high angle accuracy while maintaining operational simplicity.
Solution Approach 2:
The patent introduces an image processing intermediary between the user's manual positioning action and the final torch angle. The system captures images, extracts geometric information, calculates optimal angles, and adjusts the torch position, serving as an intelligent mediator that transforms simple user input into precise torch positioning.
3Manufacturing precision
If numerical offset data is manually input for secondary passes, then precise control of weld passes is achieved, but programming time and user effort increase
Solution Approach 1:
The system performs preliminary image capture and processing during the teaching phase to pre-calculate all necessary offset data for secondary passes. By preparing this information in advance through automated image analysis, the system eliminates the need for manual offset input during actual welding operations, significantly improving programming speed while maintaining precision.
Solution Approach 2:
The patent uses image copying and pattern recognition to transfer weld geometry information from the teaching phase to the execution phase. The system captures images of the weld seam, creates a digital model, and automatically generates offset data for multiple passes by copying and adapting the root pass parameters, eliminating repetitive manual programming.
4Manufacturing precision
If complete path planning is performed for each secondary pass, then welding accuracy is maintained, but computational time and system complexity increase
Solution Approach 1:
The patent segments the welding path planning into two parts: root pass planning with complete path calculation, and secondary passes with simplified offset-based positioning. By dividing the problem this way, the system performs detailed path planning only once for the root pass, then uses the calculated offsets to quickly generate secondary pass trajectories, reducing computational time while maintaining accuracy.
Solution Approach 2:
The system performs complete path planning for the root pass but uses simplified offset calculations for secondary passes, applying partial planning action. This approach is sufficient because the offset calculations inherit the precision of the root pass planning while requiring minimal additional computation, achieving the necessary accuracy without excessive computational effort.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Simplifies the programming of multi-pass welds by automating offset calculations and angle corrections, reducing user effort and error, while enabling efficient transfer of weld templates between similar seams, thus improving the speed and accuracy of robotic welding processes.
Implementation Method 1
acquire stereoscopic image data which is used to determine the actual torch angles
Implementation Method 2
3D point cloud data is generated from the stereoscopic image data
Data Source
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AI summary
A method of programming multiple weld passes in a collaborative robot welding system to perform multi-pass welding is provided. A root pass is programmed for a first weld seam by manually positioning a welding torch and automatically recording root pass position and angle data. Secondary passes for the first weld seam are also programmed. The tip of the welding torch is positioned at a start point and a stop point for each secondary pass. The start and stop position data of the start point and the stop point are automatically recorded for each secondary pass. Numerical position and angle offset data are automatically calculated. The root pass position and angle data and the offset data are stored as a multi-pass template. The template is translated and applied to a weld reference frame of a second weld seam to aid in programming secondary passes for the second weld seam.