Parallel Content Authoring for Mixed Reality Procedural Guidance
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Solution Overview
Problem
Current technologies face challenges in creating accurate mixed reality experiences due to the lack of reliable 3D models for existing equipment, which can be costly or time-consuming to obtain, and the subjective nature of quality assurance processes in mixed reality environments.
Innovation Solution
A Parallel Content Authoring Method and System that generates content for mixed reality environments by creating a 3D representation of physical systems, allowing for the selection and annotation of parts, and associating augmented reality data with these annotations, enabling objective quality assurance through sensor data and machine learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 3D models are obtained through reverse engineering or 3D scanning, then mixed reality content can be created for existing equipment, but the process becomes laborious, costly, and time-consuming
Solution Approach 1:
The system performs preliminary actions by automatically generating 3D models from 2D drawings and specifications before mixed reality content creation begins. This advance preparation eliminates the need for time-consuming reverse engineering or scanning during the content development phase.
Solution Approach 2:
Instead of creating new 3D models through scanning or reverse engineering, the system creates accurate digital copies from existing 2D engineering drawings and specifications. This copying approach is faster and more cost-effective while maintaining model accuracy.
2Reliability
If quality assurance is performed through human inspection and subjective evaluation, then mixed reality content can be reviewed, but the process introduces subjectivity and risk
Solution Approach 1:
The system implements automated feedback mechanisms that objectively evaluate mixed reality content against defined criteria. Sensors and analytics continuously monitor content accuracy and provide immediate feedback, eliminating subjective human judgment and associated risks.
Solution Approach 2:
The quality assurance system performs self-service by automatically evaluating and validating mixed reality content without requiring human inspection. The system uses predefined rules and analytics to assess content accuracy, ensuring consistent and objective quality control.
3Measurement precision
If CAD models are used to replicate physical objects in mixed reality, then accuracy is improved, but access to CAD models is expensive and not always available
Solution Approach 1:
Instead of requiring access to expensive CAD models to create 3D representations, the system inverts the approach by generating accurate 3D models from readily available 2D drawings and specifications. This reversal makes the process accessible without compromising accuracy.
Solution Approach 2:
The system uses inexpensive 2D drawings and specifications as the basis for creating 3D models, replacing the need for expensive CAD model access. These 2D sources are typically already available and cost-effective, enabling widespread adoption.
4Ease of operation
If device connectivity is added to provide real-time feedback and dynamic adjustments, then user experience is enhanced, but device complexity increases
Solution Approach 1:
The system uses multi-functional sensors and connectivity components that serve multiple purposes. For example, sensors not only track user actions but also provide spatial context and environmental data, reducing the need for separate dedicated components and lowering overall complexity.
Data Source
AI summary
This disclosure and exemplary embodiments described herein provide a Parallel Content Authoring Method and Tool for Procedural Guidance, and a Remote Expert Method and System Utilizing Quantitative Quality Assurance in Mixed Reality. The implementation described herein is related to the generation of content/instruction set that can be viewed in different modalities, including but not limited to mixed reality, VR, audio text, however it is to be understood that the scope of this disclosure is not limited to such application.