Telemetry-Linked 3D Model Augmentation for Aerial Vehicle Awareness
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Solution Overview
Problem
Current autonomous flight systems for aerial vehicles lack effective methods to provide real-time situational awareness and efficient decision-making during emergency operations, leading to inefficiencies and potential damage due to limited human understanding of complex situations.
Innovation Solution
A computer-implemented method that utilizes real-time telemetry data and manifest data to generate a visually augmented 3D model of the aerial vehicle, highlighting critical components and providing dynamic visual indicators for improved situational awareness and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If real-time telemetry data is processed and correlated with 3D model data to generate visually augmented representations, then situational awareness and operational efficiency are improved, but computational resources and processing complexity increase
Solution Approach 1:
The system segments the 3D model into discrete components corresponding to vehicle subsystems (propulsion, avionics, payload, etc.). Each component can be independently augmented with telemetry data, allowing selective processing of only relevant portions rather than the entire model, thus reducing computational complexity while maintaining situational awareness.
Solution Approach 2:
The patent applies different levels of visual augmentation to different portions of the 3D model based on operational relevance. Critical components experiencing anomalies receive enhanced visual indicators (color changes, highlights, annotations), while normal components maintain standard representation. This local differentiation optimizes computational resources by focusing processing power only where needed.
2Productivity
If dynamic visual indicators are applied to highlight critical components based on real-time data, then operational decision-making is improved, but data processing time and system complexity increase
Solution Approach 1:
The system pre-establishes the manifest data structure that maps telemetry parameters to specific 3D model portions before flight operations begin. This preliminary configuration enables direct, real-time correlation of incoming telemetry data with model components without requiring complex runtime analysis, significantly reducing data processing time while maintaining operational efficiency.
Solution Approach 2:
The patent implements real-time feedback loops where telemetry data continuously updates the visual representation of vehicle components. The system monitors critical parameters and immediately reflects their status through visual indicators (color changes, warnings, alerts), enabling operators to make rapid decisions based on current vehicle state without delay.
3Measurement precision
If a parameterized manifest data structure is used to link telemetry parameters to 3D model portions, then data correlation accuracy is improved, but data structure complexity and implementation difficulty increase
Solution Approach 1:
The manifest data structure is designed as a universal, standardized format that can be applied across different vehicle types and configurations. The same data structure framework accommodates various telemetry parameters and 3D model formats, reducing implementation difficulty through reusability while maintaining precise correlation capabilities through configurable parameter mappings.
Data Source
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AI summary
Embodiments of the present disclosure are directed to providing three-dimensional (3D) model augmentation for a vehicle. In an example embodiment, a manifest data structure and 3D model for a vehicle communicatively coupled to a control station (CS) system is received. The manifest data structure includes a parameterized format for respective sub-components of the vehicle that links telemetry parameters to respective portions of the 3D model for the vehicle. Based on the manifest data structure for the vehicle, real-time telemetry data is correlated with the respective portions of the 3D model to generate a visually augmented version of the 3D model for the vehicle.