AR Hand Mapping for Low-Latency Remote Expert Guidance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing augmented reality systems struggle to effectively connect remote experts with frontline workers for tasks like surgery or complex manual operations due to challenges in transmitting precise hand movements and spatial coordination, especially over distances, leading to difficulties in providing intuitive guidance.
Innovation Solution
A system using a remote expert's 2D camera to capture hand movements, determine 3D coordinates, and render corresponding AR models in real-time on the frontline worker's AR headset, allowing intuitive guidance through hand gestures, while reducing latency and data transmission requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional video conferencing or 2D screen sharing is used to guide remote workers, then the system is simple to implement, but the spatial coordination and hand movement precision are insufficient for complex tasks
Solution Approach 1:
The patent transitions from 2D video/screen sharing to 3D spatial mapping by determining three-dimensional coordinates of hand movements and mapping them to AR models. This dimensional transformation enables precise spatial coordination and intuitive gesture control, resolving the limitation of traditional 2D guidance methods for complex manual tasks
Solution Approach 2:
The system introduces AR models as intermediaries between the remote expert and frontline worker. These virtual models act as a mediator that translates hand movements into actionable guidance, enabling precise communication of spatial relationships and procedures without requiring direct visual contact or complex verbal descriptions
2Reliability
If high-resolution 3D video streams are transmitted in real-time, then the guidance quality is improved, but the data transmission requirements and latency increase
Solution Approach 1:
The system extracts only the essential information needed for guidance by determining specific 3D coordinates of hand movements rather than transmitting complete high-resolution video streams. This selective extraction of critical spatial data maintains guidance quality while dramatically reducing data transmission requirements and latency
Solution Approach 2:
Instead of transmitting actual video streams, the system creates simplified 3D coordinate representations and AR model copies that replicate the essential guidance information. These virtual models serve as lightweight copies that convey the same guidance intent without the data burden of full video transmission
3Loss of information
If the remote expert uses complex gestures or verbal instructions, then the guidance detail is improved, but the ease of operation decreases
Solution Approach 1:
The system enables the remote expert's natural hand movements to automatically generate the guidance information. By tracking and mapping the expert's own hand gestures to AR models, the system eliminates the need to learn complex control schemes or provide detailed verbal instructions, making the interface as simple as natural gesture
Solution Approach 2:
The system replaces complex mechanical interaction schemes with intuitive gesture-based control. Natural hand movements are captured and translated into AR model manipulations, substituting complicated control mechanisms with simple, intuitive gesture recognition that maintains full guidance capability
Data Source
AI summary
One example of the present application discloses an augmented reality (AR) method and system which may connect a remote expert with a front line worker. A first video stream from a 2D camera at a first location where the remote expert is located is processed in real time to determine 3D coordinates of a hand of the remote expert. An AR model is mapped to the 3D coordinates of the hand of the remote expert and rendering in real time as a first AR image in a AR headset at a second location at which the front line worker is located. Further examples relate to an augmented lighting system and an augmented optics system.