Virtual Expert Avatars for Real-Time AR/VR Task Guidance
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Solution Overview
Problem
Conventional user assistance methods, such as training videos and AI-based chatbots, lack real-time guidance and spatial adaptability for complex tasks in AR and VR environments, and AI-based virtual assistants require extensive training data to provide effective assistance.
Innovation Solution
The implementation of expert-based guidance technology using virtual avatars that capture and replicate the knowledge and actions of experienced individuals, allowing for precise semantic classification and comparison of user movements with expert actions, and provide tailored guidance through virtual 3D avatars in AR and VR settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If training videos and AI-based chatbots are used for user assistance, then basic information can be provided, but real-time guidance and spatial adaptability are lacking
Solution Approach 1:
The patent creates virtual avatar copies of human experts that replicate their appearance, mannerisms, and knowledge. These digital twins provide guidance in virtual environments, combining the reliability of expert knowledge with the adaptability to spatial contexts that traditional videos and chatbots cannot achieve.
Solution Approach 2:
The virtual avatar serves as an intermediary between the human expert and the user. It translates expert knowledge into context-aware guidance within the virtual environment, bridging the gap between static training materials and dynamic real-time assistance needs.
2Extent of automation
If AI-based virtual assistants are deployed, then automated assistance can be provided, but extensive training data is required
Solution Approach 1:
The system performs preliminary actions by capturing expert knowledge through observation and interaction before deployment. The virtual avatar learns from recorded expert behaviors and demonstrations, eliminating the need for extensive structured training data while maintaining automated assistance capabilities.
Solution Approach 2:
The virtual avatar system is self-learning through observation of expert behaviors. Rather than requiring externally provided training datasets, the system autonomously acquires knowledge by watching and analyzing expert actions, reducing the burden of data collection and preparation.
3Ease of operation
If human experts provide direct guidance, then personalized assistance can be given, but spatial and temporal limitations apply
Solution Approach 1:
By creating virtual copies of human experts, the system preserves the personalized guidance quality while eliminating temporal constraints. The digital twin can provide assistance at any time, removing the bottleneck of expert availability while maintaining the benefits of human-like interaction.
4Ease of manufacture
If conventional assistance methods are used, then implementation is simple, but real-time interaction and context-awareness are insufficient
Solution Approach 1:
The patent transitions from 2D screens and text-based chatbots to 3D virtual avatars immersed in the user's virtual environment. This dimensional shift enables natural spatial interaction and contextual awareness while maintaining relative ease of implementation through standardized virtual reality technologies.
Data Source
AI summary
A system may include a semantic actions database configured to reference a working context knowledge graph to specify target actions to perform a task and environment conditions of an environment in which an individual performs the task. The system may also include an expert avatar engine configured to access a posture set from a digital data stream of a target individual performing the task in an environment, classify the postures of the posture set into discrete actions, retrieve target actions from the semantic actions database for performing the task in the environment, generate guidance for the target individual based on a comparison between the discrete actions classified for the target individual and the target actions retrieved from the semantic actions database, and provide the guidance to the target individual to assist the target individual in performing the task.