Operator Characteristic-Based Visual Overlays for AR Task Guidance
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Solution Overview
Problem
Augmented Reality (AR) devices lack the ability to provide custom-tailored instructions to operators based on their characteristics and the specific tasks they need to perform in a physical environment, often providing inappropriate or repetitive information due to their inability to register operator characteristics and understand the environment beyond basic object identification.
Innovation Solution
The system extracts data from digital images of the physical environment using computer vision and deep learning, identifies operator characteristics, and selects relevant information to create a visual overlay that is tailored to the operator's skills and preferences, adapting the information in real-time based on feedback during task performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AR devices provide comprehensive task instructions to operators, then task performance improves, but operators experience information overload and distraction
Solution Approach 1:
The system customizes the information display for each operator based on their skill level, role, and performance needs. Different operators receive different subsets of task information tailored to their specific requirements, rather than providing uniform comprehensive instructions to all users.
Solution Approach 2:
The information display dynamically adapts during task execution based on real-time operator performance data, environmental conditions, and task progress. The system adjusts the amount and type of information provided on-the-fly rather than using static pre-defined instruction sets.
2Object-affected harmful factors
If AR devices provide simplified task instructions to operators, then information overload is reduced, but task performance and safety may be compromised
Solution Approach 1:
The system continuously monitors operator performance, environmental conditions, and task progress, then uses this feedback to dynamically adjust the information provided. When performance metrics indicate potential issues or when environmental conditions change, the system automatically provides additional relevant information to maintain safety and performance.
Solution Approach 2:
The system pre-loads and prepares multiple levels of task information and instructions before the operator begins the task. Based on preliminary assessment of operator characteristics and task requirements, the system has relevant information ready to be displayed at appropriate moments during task execution.
3Adaptability or versatility
If AR devices provide custom-tailored instructions based on operator characteristics, then information relevance improves, but system complexity increases
Solution Approach 1:
The system automatically collects operator characteristics, performance data, and environmental information, then autonomously processes this data to generate customized instruction sets without requiring manual configuration or complex user setup procedures.
Solution Approach 2:
The system uses a unified framework that handles multiple functions: operator profiling, environmental sensing, task management, and dynamic information delivery. This multi-functional approach consolidates complexity into a single integrated system rather than requiring separate specialized systems for each function.
4Measurement precision
If AR devices collect and process operator characteristics and environmental data, then information accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system collects and processes operator characteristic data, environmental information, and task parameters before the operator begins the actual task. This preliminary data processing creates ready-to-use profiles and pre-calculates relevant information, reducing the computational burden during time-critical task execution.
Solution Approach 2:
The system focuses computational resources on processing and analyzing only the specific data subsets that are most relevant to the current operator, task, and environmental conditions. Rather than uniformly processing all available data, the system identifies and prioritizes the most critical information for real-time decision-making.
Data Source
AI summary
A system may include a processing resource, and a computing device comprising instructions executable to: extract data from objects in a digital image of a physical environment; utilize the extracted data to identify information about a task to be performed by an operator at the physical environment; and select, based on a characteristic of the operator, a portion of the identified information about the task to include in a visual overlay to be displayed to the operator at the physical environment.