Drone Formation Control Using Camera-Based Distance Estimation
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Solution Overview
Problem
Unmanned moving vehicles face challenges in monitoring environments and maintaining formation when communication with a master device is disconnected, leading to potential collisions and inefficiencies in monitoring tasks.
Innovation Solution
A system where unmanned moving vehicles use machine learning to calculate distances to other vehicles via camera images, allowing them to adjust altitude and maintain formation without additional sensors, and switch to centralized control for safe return and collision avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If unmanned moving vehicles use camera images and machine learning to calculate distances, then additional collision avoidance sensors are eliminated, but the complexity of processing camera data and maintaining formation increases
Solution Approach 1:
The camera system performs multiple functions: it captures images for monitoring tasks and simultaneously serves as a distance measurement tool for collision avoidance. The machine learning model processes camera images to calculate distances between vehicles, eliminating the need for dedicated sensors while using existing hardware for dual purposes.
Solution Approach 2:
The system uses visual information from camera images to create a virtual representation of the physical environment, including distance measurements. Instead of directly measuring physical distances with sensors, the system creates a digital model through image processing and machine learning that replicates the spatial relationships needed for collision avoidance.
2Reliability
If unmanned moving vehicles switch to centralized control when communication is disconnected, then collision avoidance and safe return are improved, but the response time and autonomy during communication loss may be reduced
Solution Approach 1:
The system pre-establishes control protocols and algorithms that automatically activate when communication is lost. The unmanned vehicles are pre-programmed with formation maintenance algorithms and collision avoidance logic that execute without real-time master device input, enabling immediate response to communication failures.
Solution Approach 2:
The system continuously monitors communication status and automatically switches between centralized and autonomous control modes. When communication is restored, the system provides feedback to the master device about the situation that occurred during disconnection, allowing for adaptive response and learning.
Data Source
AI summary
Provided is an unmanned moving vehicle for monitoring and a system including the same and, more particularly, to a method of controlling an unmanned moving vehicle whose communication with a master unmanned device is disconnected. To this end, the unmanned moving vehicle system for monitoring includes a master unmanned device performing communication with a ground control system located on the ground; and an unmanned moving vehicle performing communication with the master unmanned device, flying in formation around the master unmanned device, and calculating a distance to other unmanned moving vehicle flying in formation when communication with the master unmanned device is disconnected.