Telepresence Robot Interface With Context-Based Visual Annotations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current graphical user interfaces for remotely controlling telepresence robots lack the ability to selectively render visual annotations for entities in the robot's environment based on user interactions and context, limiting the user's understanding of their surroundings and task efficiency.
Innovation Solution
A method and system that identify entities within the robot's environment using facial recognition, communication mechanisms, and user interaction records, calculate the user's potential interest in these entities, and selectively render visual annotations on a multi-dimensional representation of the environment, such as live video feeds or map views, with attributes based on this interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If visual annotations are rendered for all entities in the environment, then the user gains complete information about the surroundings, but the graphical user interface becomes cluttered and harder to interpret
Solution Approach 1:
The patent applies local quality by selectively rendering visual annotations based on user context and potential interest calculations. Different entities receive different treatment: high-interest entities get prominent annotations while low-interest entities remain unannotated. This resolves the contradiction by providing information selectively rather than uniformly, maintaining interface clarity while reducing information loss for relevant entities.
Solution Approach 2:
The system performs partial action by rendering annotations for only a subset of entities rather than all entities in the environment. The annotation rendering is governed by a calculated measure of potential user interest, which determines whether annotation resources are allocated to a particular entity. This partial application of annotation rendering maintains interface simplicity while providing sufficient information about important entities.
2Loss of information
If the system calculates potential interest for all entities, then the user receives highly relevant information, but the computational complexity and processing time increase
Solution Approach 1:
The system changes parameters by calculating a derived metric (potential interest score) that combines multiple user context factors into a single evaluative parameter. This parameter change transforms complex multi-dimensional user context data into a simplified scoring mechanism that guides annotation rendering decisions, reducing processing complexity while maintaining information relevance.
Solution Approach 2:
The system performs preliminary action by pre-calculating user context characteristics and potential interest measures before the actual annotation rendering process. User interaction records and context data are analyzed in advance to establish baseline interest levels, which then guide real-time annotation decisions. This preliminary processing reduces the computational burden during live operation.
3Adaptability or versatility
If visual annotations are rendered based on user context, then the interface becomes more personalized and useful, but the system requires access to and processing of user interaction data
Solution Approach 1:
The system applies universality by using a multi-functional user context analysis mechanism that serves both personalization and computational efficiency purposes. The same user interaction record processing infrastructure that enables personalized annotations also provides the data foundation for potential interest calculations. This multi-functionality reduces overall system complexity by consolidating data processing requirements rather than adding separate systems.
Data Source
AI summary
Methods, apparatus, systems, and computer-readable media are provided for visually annotating rendered multi-dimensional representations of robot environments. In various implementations, an entity may be identified that is present with a telepresence robot in an environment. A measure of potential interest of a user in the entity may be calculated based on a record of one or more interactions between the user and one or more computing devices. In some implementations, the one or more interactions may be for purposes other than directly operating the telepresence robot. In various implementations, a multi-dimensional representation of the environment may be rendered as part of a graphical user interface operable by the user to control the telepresence robot. In various implementations, a visual annotation may be selectively rendered within the multi-dimensional representation of the environment in association with the entity based on the measure of potential interest.