3D Weld Torch Angle Correction for Robotic Seam Teaching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Programming and setting torch angles for robotic welding or cutting systems is complicated, requiring manual adjustment by users, which can be inaccurate and time-consuming.
Innovation Solution
A robotic welding system equipped with a depth camera and computer device that acquires stereoscopic image data to determine and correct torch angles based on pre-stored ideal angles, eliminating the need for precise manual positioning by users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual positioning of torch angles is used by users, then the system allows flexible operation, but the accuracy and precision of angle settings deteriorate
Solution Approach 1:
The patent replaces manual mechanical positioning of the torch with an automated vision-based system. A depth camera captures 3D point cloud data of the weld joint, and computer algorithms automatically calculate the optimal torch angles (work angle and push angle) relative to the joint geometry, eliminating the need for manual angle setting by users.
Solution Approach 2:
The system creates a digital 3D copy of the physical weld joint using depth camera imaging and point cloud processing. This digital model is then used to calculate precise torch angles without physically adjusting the torch multiple times, allowing virtual simulation and optimization of welding parameters before actual welding.
2Ease of operation
If manual positioning of torch angles is used, then user control is maintained, but the time required for programming and setup increases
Solution Approach 1:
The system enables self-service automation where the depth camera and computer algorithms automatically perform angle calculation and torch positioning without requiring user intervention. The system independently processes the 3D joint geometry data, computes optimal angles, and guides the torch placement, significantly reducing programming and setup time while maintaining welding quality.
Solution Approach 2:
The system performs preliminary action by pre-calculating the optimal torch angles before the actual welding process begins. The depth camera captures the joint geometry, and the computer algorithms compute the work angle and push angle in advance, allowing the robot to execute the welding path without real-time manual adjustments.
3Measurement precision
If automated depth camera-based angle correction is implemented, then angle setting accuracy improves, but device complexity increases
Solution Approach 1:
The depth camera system serves multiple functions: it captures 3D geometry of the weld joint, calculates work angles, determines push angles, and provides spatial reference for robot positioning. This multi-functional approach consolidates what would otherwise require separate devices for each measurement and calculation task, reducing overall system complexity despite the advanced capabilities.
Solution Approach 2:
The computer acts as an intermediary that processes the raw 3D point cloud data from the depth camera and translates it into meaningful torch angle parameters. The computer algorithms bridge the gap between the complex raw sensor data and the simple control commands needed by the robot, managing system complexity through intelligent data processing.
4Productivity
If automated angle correction is used, then welding process efficiency improves, but the initial setup and calibration requirements increase
Solution Approach 1:
The system uses feedback from the depth camera to continuously monitor and verify torch positioning accuracy during setup and operation. The camera captures real-time 3D data, compares it with the planned welding path, and provides feedback for minor adjustments, ensuring accurate angle correction while minimizing the need for extensive manual calibration.
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
Automates the correction of torch angles, ensuring accurate and efficient welding or cutting processes without requiring detailed user knowledge of angle settings.
Implementation Method 1
A depth camera is used to determine the actual angles of the welding or cutting torch, as positioned by the user, with respect to a corresponding joint/seam of the weldment. In one embodiment, the depth camera may include two imaging apertures for acquiring stereoscopic image data
Data Source
AI summary
A method of correcting angles of a welding torch positioned by a user while training a robot of a robotic welding system is provided. Weldment depth data of a weldment and a corresponding weld seam is acquired and 3D point cloud data is generated. 3D plane and intersection data is generated from the 3D point cloud data, representing the weldment and weld seam. User-placed 3D torch position and orientation data for a recorded weld point along the weld seam is imported. A torch push angle and a torch work angle are calculated for the recorded weld point, with respect to the weldment and weld seam, based on the user-placed torch position and orientation data and the 3D plane and intersection data. The torch push angle and the torch work angle are corrected for the recorded weld point based on pre-stored ideal angles for the weld seam.