Human-Machine Collaboration State Feedback Using Ergonomic and Scene Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing human-machine collaboration systems lack effective methods for real-time feedback and adaptation based on virtual-real integration, leading to inefficiencies and safety risks in human-machine interactions.
Innovation Solution
A method and apparatus for feedbacking human-machine collaboration state through virtual-real integration, utilizing ergonomic data and operation scene images to recognize collaboration and personnel states, enabling real-time adjustments and decision-making for improved efficiency and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time feedback and adaptation mechanisms are implemented in human-machine collaboration systems, then efficiency and safety are improved, but system complexity and computational resource requirements increase
Solution Approach 1:
The patent implements real-time feedback mechanisms by acquiring ergonomic data (eye movement, physiological signals) and operation scene images, then analyzing them to generate collaboration state feedback. This closed-loop feedback system continuously monitors and adjusts the human-machine collaboration process, improving efficiency through adaptive adjustments while managing complexity through modular architecture
Solution Approach 2:
The system segments the complex feedback process into distinct functional modules: data acquisition module (ergonomic sensors, cameras), analysis module (gaze position recognition, physiological signal processing), and feedback generation module. This segmentation reduces overall system complexity by making each component independent and manageable while maintaining real-time operational capabilities
2Measurement precision
If multiple types of ergonomic data and operation scene images are collected and analyzed, then recognition accuracy and decision-making quality are improved, but data processing time and computational load increase
Solution Approach 1:
The system performs preliminary processing of ergonomic data and operation scene images by pre-defining analysis frameworks and recognition models. Gaze position recognition and physiological signal processing are prepared in advance with predetermined algorithms, enabling rapid real-time analysis without extensive computational delays during actual operation
Solution Approach 2:
The patent replaces complex mechanical data processing with intelligent algorithms and machine learning models. Neural networks and pattern recognition systems automatically analyze ergonomic data and images, substituting traditional computational methods with more efficient intelligent processing that maintains high accuracy while reducing processing time
Data Source
AI summary
Provided are a method and an apparatus for feedbacking a human-machine collaboration state based on virtual-real integration, and an electronic device. Ergonomic data of an operation subject in a human-machine collaboration process for a current operation task and an operation scene image that is obtained by shooting the human-machine collaboration process and at least includes an operation device and a setting parameter of an operation environment are acquired. A human-machine collaboration state recognition is performed based on the operation scene image to obtain target collaboration state data corresponding to the current operation task, and a personnel state recognition is performed based on the ergonomic data to obtain personnel state data of the operation subject. Based on the target collaboration state data and the personnel state data, a state of the human-machine collaboration process is feedbacked.