UAV Collision Avoidance Using UV Imaging and ML
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Solution Overview
Problem
Conventional automated collision detection and avoidance systems for unmanned aerial vehicles (UAVs) are impractical due to their weight, power consumption, and high cost, and are unable to interact with non-cooperating or stationary objects without corresponding equipment.
Innovation Solution
A detection and avoidance system using an imaging unit that captures images in the ultraviolet range, with a processing unit that detects objects and communicates collision hazard information to a pilot control system, employing machine learning for classification and exclusion of non-hazardous objects, and utilizing a second camera channel for color imaging to enhance object recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional automated detection and avoidance systems (TCAS, ADS-B) are used on UAVs, then collision detection capability is improved, but weight and power consumption increase significantly
Solution Approach 1:
The patent replaces conventional radio-based detection systems (TCAS, ADS-B) with an optical imaging system that uses cameras and image processing algorithms. This substitution eliminates the need for heavy transponders and radar equipment, significantly reducing weight while maintaining collision detection capability through visual object recognition and classification
Solution Approach 2:
The system uses imaging cameras to create visual copies (images) of potential collision hazards instead of using direct radio communication or radar signals. By capturing and analyzing images of objects in the flight path, the system achieves detection capability without requiring the target objects to have any special equipment, while keeping the UAV's own equipment lightweight
2Reliability
If conventional TCAS equipment is used, then automated collision avoidance is achieved, but cost increases significantly
Solution Approach 1:
The patent replaces expensive, specialized aviation equipment (TCAS, transponders) with inexpensive consumer-grade imaging cameras and standard image processing hardware. These affordable components perform collision detection through software-based object recognition, making the system economically viable for small UAVs while maintaining automated avoidance functionality
Solution Approach 2:
The imaging system serves multiple functions: it captures visual data for collision detection, provides situational awareness, and can potentially be used for navigation and monitoring. This multi-functionality eliminates the need for separate specialized equipment, reducing overall system cost while maintaining comprehensive safety capabilities
3Reliability
If standard TCAS equipment is used, then collision avoidance with equipped objects is possible, but inability to detect non-cooperating or stationary objects remains
Solution Approach 1:
The patent replaces radio-based active transponder systems with passive optical imaging. This substitution allows the system to detect objects that do not emit or reflect radio signals, including non-cooperating aircraft without transponders and stationary objects like towers or buildings, by capturing their visual images and identifying them through image processing algorithms
Solution Approach 2:
The imaging system provides universal detection capability across multiple object types and states. Unlike TCAS that only detects equipped moving objects, the visual system can identify and classify various objects including non-cooperating aircraft, stationary structures, birds, and other hazards, making the system adaptable to diverse detection scenarios without requiring target objects to have specific equipment
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides a compact, lightweight, and economical solution for UAVs to detect and avoid collisions with hazardous objects, including those that do not emit radiation in the ultraviolet range, effectively guiding the vehicle to avoid potential collisions.
Implementation Method 1
The first camera channel filters radiation at a wavelength, where one or more objects in the field of view do not emit radiation at the wavelength
Implementation Method 2
The wavelength at which the first camera channel of the detection and avoidance system filters radiation is within the ultraviolet (UV) range
Data Source
AI summary
In general, certain embodiments of the present disclosure provide a detection and avoidance system for a vehicle. According to various embodiments, the detection and avoidance system comprises an imaging unit configured to obtain a first image of a field of view at a first camera channel. The first camera channel filters radiation at a wavelength, where one or more objects in the field of view do not emit radiation at the wavelength. The detection and avoidance system further comprises a processing unit configured to receive the first image from the imaging unit and to detect one or more objects therein, as well as a notifying unit configured to communicate collision hazard information determined based upon the detected one or more objects to a pilot control system of the vehicle. Accordingly, the pilot control maneuvers the vehicle to avoid the detected objects.