Augmented Reality Remote Control for Unmanned Vehicles in Low Visibility
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Solution Overview
Problem
Existing systems for controlling unmanned vehicles with built-in cameras lack reliability, especially in conditions of poor visibility, which hinders safe management and effective interaction with remote users.
Innovation Solution
The method involves generating an augmented reality environment by transmitting camera images from unmanned vehicles to remote users, overlaying user spatial models onto the images, and integrating additional sensors like IR, radar, or echo sounders to enhance data intensity and visibility, allowing real-time voice and text communication for improved control and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If only camera images are transmitted for remote control, then device complexity is reduced, but reliability deteriorates in poor visibility conditions
Solution Approach 1:
The system segments information into multiple channels: visible light camera images and infrared sensor data. Each sensor type captures different aspects of the environment, and their combined transmission to the remote user provides comprehensive situational awareness that overcomes the limitations of any single sensor modality.
Solution Approach 2:
The unmanned vehicle is equipped with multi-functional sensors including both visible light cameras and infrared sensors. These sensors serve multiple purposes: navigation, obstacle detection, and environmental monitoring. The infrared sensor specifically enables operation in low-visibility conditions where visible light cameras fail.
2Loss of information
If camera images alone are used for visualization, then ease of operation is maintained, but information completeness deteriorates
Solution Approach 1:
The system adds the infrared spectrum dimension to the traditional visible light imaging. By overlaying infrared sensor data on camera images, the system provides thermal information that reveals hidden objects and conditions not visible to the human eye, thereby reducing information loss without significantly complicating the user interface.
3Measurement precision
If multiple sensors are integrated to enhance visibility, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system merges data from multiple sensor types (camera and infrared sensor) into a unified visualization. The infrared sensor data is overlaid on the camera image feed, creating a composite view that enhances obstacle detection precision. This merging approach allows the remote user to perceive environmental details that would be invisible to either sensor alone.
Data Source
AI summary
The invention relates to computerized data processing, more particularly to methods of generating an augmented reality environment, and comprises the following steps: controlling the position of an unmanned transport vehicle having a built-in camera, determining the position coordinates of the unmanned transport vehicle, transmitting a captured camera image to a user display means for visualization, exchanging messages in real time between the user and at least one second user located within visual range of the unmanned transport vehicle and equipped with augmented reality visualization means, visualizing an image captured by a camera of the second user using augmented reality generating means of the second user, visualizing a spatial model of the user, wherein the position of the spatial model in the visualized image corresponds to the position of the unmanned transport vehicle in the captured image from the camera of the second user.