Mixed Reality Robotic Welding Simulator with Adaptive Rendering
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Solution Overview
Problem
Conventional systems for simulating robotic joining operations, such as welding, require substantial computational power, are cumbersome, and struggle with accurate modeling of material transfer, bead geometry, and melting processes, limiting their implementation on mobile devices and web browsers, and lack efficient simulation of robotic operations in augmented reality environments.
Innovation Solution
A mixed-reality system that uses augmented reality techniques to simulate robotic joining operations, accurately calculating material transfer, bead geometry, and melting processes, enabling simulation on less powerful platforms and allowing for customizable, efficient training environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional simulation systems use substantial GPU computational power to perform welding simulation, then the rendering accuracy of simulated weld bead is improved, but the device complexity and platform requirements increase, limiting implementation on mobile devices and web browsers
Solution Approach 1:
The simulation system is segmented into distinct functional modules: a simulation engine that performs calculations, a rendering module that generates visual output, and a platform adaptation layer. This segmentation allows the computationally intensive simulation engine to operate independently from the rendering requirements, enabling deployment on mobile devices and web browsers while maintaining weld bead rendering accuracy through optimized visualization techniques.
Solution Approach 2:
The patent replaces conventional GPU-intensive graphical rendering with an alternative rendering approach that uses simplified geometric models and optimized algorithms. Instead of relying heavily on graphical processing units, the system uses CPU-based calculation with optimized rendering pipelines, substituting the mechanical GPU rendering system with a more flexible computational approach that works across multiple platforms including mobile devices and web browsers.
2Manufacturing precision
If conventional simulation systems are designed for high computational power platforms, then the simulation accuracy is improved, but the ease of operation and accessibility deteriorate, making the systems cumbersome and difficult to implement
Solution Approach 1:
The simulation system is designed with universal compatibility across multiple platforms including mobile devices, tablets, desktop computers, and web browsers. The system uses standardized web technologies and adaptive rendering that automatically adjusts to different device capabilities, maintaining simulation accuracy while improving ease of operation and accessibility. This multi-functional design allows the same simulation to run on various platforms without requiring platform-specific versions.
Solution Approach 2:
The system implements adaptive simulation that adjusts the level of computational detail based on platform capabilities. On mobile devices and web browsers, the system uses optimized algorithms that provide sufficient accuracy for training purposes without requiring the full computational power of high-end systems. This partial action approach maintains essential simulation accuracy while improving accessibility on less powerful devices.
3Quantity of substance
If conventional weld simulation models material transfer and bead geometry, then the simulation completeness is improved, but the manufacturing precision deteriorates because the amount of material transferred cannot be accurately modeled
Solution Approach 1:
The simulation system incorporates feedback mechanisms that continuously adjust material transfer calculations based on simulated welding parameters and observed bead geometry outcomes. The system uses iterative algorithms that compare predicted material deposition with actual welding process data, refining the material transfer model to improve weld bead geometry accuracy. This feedback loop ensures that material transfer modeling accurately reflects real-world welding behavior.
Solution Approach 2:
The system dynamically adjusts material transfer parameters based on welding process conditions such as current, voltage, travel speed, and electrode configuration. By changing material transfer parameters in response to varying welding conditions, the system maintains accurate weld bead geometry predictions across different welding scenarios. This parameter adaptation allows the simulation to accurately model both material transfer and resulting bead geometry.
4Quantity of substance
If conventional simulation systems use complex algorithms to model welding processes, then the simulation completeness is improved, but the productivity and development efficiency deteriorate, presenting difficulties for development of new features and functionality
Solution Approach 1:
The simulation system uses pre-calculated material properties, welding parameters, and geometric models that are prepared in advance and stored in databases. When performing simulations, the system retrieves and applies these pre-computed values rather than calculating everything from scratch. This preliminary action approach maintains simulation completeness while significantly improving productivity and reducing the time required to develop new features and functionality.
Solution Approach 2:
The complex simulation algorithms are segmented into modular, independently testable components. Each module handles a specific aspect of the welding process (heat transfer, material deposition, bead formation), allowing developers to work on individual features without affecting the entire system. This modular segmentation improves development efficiency while maintaining overall simulation completeness through the coordinated operation of all modules.
Data Source
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AI summary
Systems and methods to simulate robotic joining operations are disclosed. An example system to simulate a robotic application includes: an image sensor configured to capture images of a physical simulation workpiece and a physical simulation welding torch manipulated by a robotic arm during welder during a simulated operation; and a simulator configured to: calculate a simulated result based on the captured images and based on communications output by the robotic arm; and output a visual representation of the simulated result.