Robotic Weld Torch Orientation Teaching With Stored Pose Recall
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The complexity and time required for programming robotic welding tasks pose a significant obstacle for small to medium enterprises lacking resources and expertise, particularly in defining and stabilizing the torch orientation along the weld seam, which affects the accuracy and efficiency of the welding process.
Innovation Solution
The method involves storing and recalling the robot pose as a combination of current torch tip position and orientation, allowing the operator to define and store torch orientation once and reuse it along the weld path, reducing the effort needed to teach the weld path by focusing on translational movements and using stored orientations for rotational adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional lead-through teaching method is used to program robot positions and orientations, then the robot can perform welding tasks, but the programming time and complexity increase significantly
Solution Approach 1:
The patent segments the torch pose definition into two independent components: torch position (taught by operator) and torch orientation (automatically calculated). This segmentation allows the system to handle position and orientation separately, reducing the programming burden on the operator while maintaining welding precision.
Solution Approach 2:
The system performs self-service by automatically calculating the torch orientation based on the taught position and stored reference points. Instead of requiring the operator to manually teach both position and orientation, the system autonomously computes the orientation information, significantly reducing programming time while maintaining accuracy.
2Manufacturing precision
If operator manually defines torch orientation at each position, then welding accuracy is maintained, but the effort and time required for programming increases
Solution Approach 1:
The patent applies preliminary action by storing reference points (such as weld seam start point, end point, and intermediate points) before the actual welding path teaching. These pre-stored reference points enable the system to automatically calculate torch orientation during path teaching, reducing the effort required while maintaining weld quality.
Solution Approach 2:
The system introduces an intermediary computational process that automatically calculates torch orientation based on the relationship between the current torch position and pre-stored reference points. This intermediary mechanism bridges the gap between simple position teaching and accurate orientation control, reducing programming effort while maintaining precision.
3Reliability
If complete pose (position and orientation) is taught at each point, then welding accuracy is ensured, but programming complexity increases for small to medium enterprises
Solution Approach 1:
The patent extracts the orientation calculation from the manual teaching process and performs it automatically by the system. By taking out the orientation definition from the operator's tasks and converting it into an automatic computational process, the system reduces programming complexity while maintaining welding accuracy, making robotic welding more accessible to small to medium enterprises.
Data Source
AI summary
Robots are commonly used for automated MIG (Metal Inert Gas) or TIG (Tungsten Inert Gas) welding in many industries such as automotive manufacturing. A weld procedure is defined and the robot performs motion control of the weld torch along the weld seam, while starting and stopping the arc as desired along the weld seams. The robot controls the motion of the torch along the weld path. The motion is defined by a combination of the position and orientation of the torch which is attached to the robot end-effector. The weld specification will generally prescribe a portion or all of the desired orientation of the torch. This information can be used to reduce the complexity of programming a weld path for a robot.