3D Weld Torch Angle Correction for Easier Robot Training
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Solution Overview
Problem
Programming motion trajectories and setting angles for robotic welding or cutting systems is complex, particularly in ensuring accurate torch orientations along weld joints, which can be challenging for human users without detailed knowledge.
Innovation Solution
A weld angle correction tool utilizing a depth camera to acquire stereoscopic depth image data, generating 3D point cloud and plane data, and calculating torch push and work angles based on user-placed positions, allowing for correction to ideal angles stored in the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a human user manually positions the torch at various points along the joint to train the robot, then the robot can learn the weld trajectory, but the user must be particularly careful about positioning the torch angles (push angle and work angle) precisely, which increases the difficulty and time required for training
Solution Approach 1:
The patent replaces manual mechanical positioning and angle measurement with an optical system (depth camera) that automatically captures and processes torch position and angle data. The depth camera acquires stereoscopic image data to determine actual torch angles, eliminating the need for users to manually measure and input angle values, thus resolving the contradiction between measurement precision and ease of operation
Solution Approach 2:
The system enables self-correction by automatically comparing the actual torch angles (measured by the depth camera) with ideal angles (stored in the system) and generating corrected trajectory data without requiring user expertise in angle measurement or manual adjustment, allowing the robot training process to self-correct angle deviations
2Reliability
If the user manually positions the torch with precise angle control, then weld quality can be maintained, but the training process becomes time-consuming and complex
Solution Approach 1:
The system implements automatic feedback by continuously monitoring actual torch angles during training using the depth camera, comparing them against pre-stored ideal angles, and automatically generating corrected trajectory data. This closed-loop feedback mechanism ensures weld quality is maintained while eliminating manual angle adjustment time, thereby resolving the contradiction between reliability and productivity
Solution Approach 2:
The system performs preliminary action by pre-storing ideal torch angles for different welding scenarios in the system memory. During training, these pre-stored ideal angles are automatically retrieved and used for comparison and correction, eliminating the need for users to manually determine optimal angles during the training process, thus improving productivity while maintaining weld quality
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
Enables accurate and efficient correction of torch angles during robot training, reducing the need for precise user input and improving the quality of welds by aligning the torch with pre-stored ideal orientations, thus simplifying the training process for robotic welding systems.
Implementation Method 1
a depth camera that acquires stereoscopic depth image data which is used to determine the actual torch angles of the torch, as positioned by the user, with respect to the joint/seam
Data Source
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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.