Robotic Weldhead TCP Calibration Using Multi-Camera Protrusion Sensing
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Solution Overview
Problem
Conventional robotic welding systems require manual calibration of the tool center point (TCP) in 3D space, which is time-consuming and prone to operator error due to the need for manual movement and alignment of the tool against a fixed point.
Innovation Solution
An automated method using image sensors and a controller to identify a protrusion from the weldhead, define its longitudinal axis, and calculate the TCP's location in 3D space, eliminating the need for manual intervention by guiding the robot to brush against a fixed object.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration method is used, then operator can directly adjust TCP position, but calibration process is time-consuming and prone to operator error
Solution Approach 1:
The patent replaces manual mechanical calibration operations with an automated vision-based system. Image sensors capture images of the tool, and a controller automatically processes these images to determine TCP coordinates, eliminating the need for manual mechanical adjustment and reducing both time and human error.
Solution Approach 2:
The system enables self-calibration by using the robot's own image sensors to capture and process images of its tool. The controller automatically identifies the protrusion, defines the longitudinal axis, and calculates TCP position without requiring external operators or additional calibration equipment.
2Reliability
If manual calibration method is used, then operator can adjust TCP position, but the process is prone to operator error
Solution Approach 1:
The patent replaces manual mechanical calibration operations with an automated vision-based system. Image sensors capture images of the tool, and a controller automatically processes these images to determine TCP coordinates, eliminating the need for manual mechanical adjustment and reducing both time and human error.
Solution Approach 2:
The patent introduces an intermediary automated processing system between the physical tool and the TCP calibration result. The controller acts as an intermediary that objectively processes image data and calculates coordinates, removing human judgment and error from the calibration process.
3Measurement precision
If automated image-based method is used, then calibration time is reduced and precision is improved, but device complexity increases
Solution Approach 1:
The patent makes the robot's existing image sensors multi-functional by using them both for welding process monitoring and for TCP calibration. This eliminates the need for separate dedicated calibration sensors, reducing overall system complexity while maintaining high precision.
Solution Approach 2:
The system enables self-calibration by using the robot's own image sensors to capture and process images of its tool. The controller automatically identifies the protrusion, defines the longitudinal axis, and calculates TCP position without requiring external operators or additional calibration equipment.
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
This approach allows for accurate and precise calibration of the TCP in 3D space, reducing calibration time and minimizing operator error, enabling faster and more reliable robotic welding operations.
Implementation Method 1
receiving a plurality of images captured from a plurality of image sensors of the robotic welding system, the plurality of images containing at least a portion of a protrusion extending from a tip of a weldhead
Data Source
AI summary
A method for calibrating a tool center point (TCP) of a robotic welding system. The method includes receiving a plurality of images captured from a plurality of image sensors of the robotic welding system, the plurality of images containing at least a portion of a protrusion extending from a tip of a weldhead of the robotic welding system, and identifying by a controller of the robotic welding system the protrusion extending from the weldhead in the plurality of images. The method additionally includes defining by the controller a longitudinal axis of the protrusion based on the protrusion identified in the plurality of images, and identifying by the controller a location in three-dimensional (3D) space of the weldhead based on the protrusion identified in the plurality of images and the defined longitudinal axis of the protrusion.