Extended Reality System Learning Object-Centered Routines
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Solution Overview
Problem
Extended reality systems lack the ability to recognize and respond to user-performed object-centered routines, limiting their functionality in providing relevant content and automations within virtual and mixed reality environments.
Innovation Solution
An extended reality system that includes a head-mounted device with sensors and processors to learn and recognize object-centered routines by collecting data on user interactions with objects in real and virtual environments, presenting a visual graph for user input, defining nodes and relationships, and triggering automations based on recognized routines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If extended reality systems use hand controllers for interaction, then users can control applications, but it betrays the point of freeing the user's hands and limits headset use
Solution Approach 1:
The patent replaces mechanical hand controllers with voice-based virtual assistant interaction. The system uses speech recognition and natural language processing to enable hands-free control of applications, replacing the mechanical controller interface with acoustic field-based voice commands.
Solution Approach 2:
The patent introduces a virtual assistant as an intermediary between the user and the extended reality system. This virtual assistant processes voice commands and translates them into application control actions, serving as a mediator that enables natural hands-free interaction without requiring direct manual control.
2Ease of operation
If extended reality systems use hand gestures for interaction, then users can interact with components, but users must keep arms extended within sensor range causing fatigue
Solution Approach 1:
The patent replaces physical hand gesture mechanics with acoustic field-based voice recognition. Instead of requiring arm movement within sensor range, the system captures voice commands through microphones and processes them via speech recognition algorithms, eliminating the physical strain of extended arm positioning.
Solution Approach 2:
The virtual assistant acts as an intermediary that translates voice commands into system actions, replacing the need for continuous physical gesturing. This mediator enables sustained interaction without the fatigue associated with maintaining arm extensions within sensor fields.
3Adaptability or versatility
If virtual assistants are added to extended reality devices, then users can accomplish tasks with voice commands, but the system complexity increases
Solution Approach 1:
The patent implements a universal virtual assistant platform that handles multiple interaction modalities (voice commands, natural language queries, application control) through a single integrated system. This multi-functional approach consolidates what would otherwise require separate specialized components, managing complexity through consolidation rather than proliferation.
Solution Approach 2:
The virtual assistant serves as a central intermediary layer that manages complexity by providing a unified interface between various extended reality functions and user commands. This mediator abstracts the underlying system complexity, presenting a simplified voice-based interaction model to users while handling diverse backend operations.
Data Source
AI summary
Features described herein generally relate to learning and recognizing object-centered routines. Particularly, object-centered routines can be learned and recognized by collecting data corresponding to a user. The data can include information representing interactions by the user with respect to objects in an environment. The routine can be learned by presenting a visual graph to the user. The user can define nodes associating an interaction with an object, specify a relationship between nodes, and arrange the nodes into segments. The visual graph can be stored, and a routine can be recognized based on the visual graph.