UAV Object Avoidance via Passive Optical and Acoustic Detection
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Solution Overview
Problem
Current aircraft collision avoidance systems are often heavy, expensive, and rely on active transponder interrogation, making them ineffective for detecting objects without transponders, particularly in busy and unpredictable low-altitude airspace where UAVs operate.
Innovation Solution
The implementation of a UAV system equipped with sensors such as cameras, acoustic sensors, and multispectral sensors that detect and analyze electromagnetic and acoustic signals to identify objects and update flight plans dynamically, using a peer-to-peer communication network to extend detection limits and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If active transponder interrogation systems are used for collision avoidance, then detection capability is improved, but system weight and cost increase
Solution Approach 1:
The patent replaces active transponder interrogation systems with passive optical detection systems using cameras and image processing. This substitution eliminates the need for heavy radar and transponder equipment while maintaining detection capability through visual recognition of aircraft lights, shapes, and movement patterns.
Solution Approach 2:
The system creates visual copies or representations of aircraft through captured images and video feeds. By analyzing these optical copies rather than using physical radar systems, the patent achieves detection functionality with significantly reduced weight and cost.
2Measurement precision
If active transponder interrogation systems are used for collision avoidance, then detection capability is improved, but system cost increases
Solution Approach 1:
The patent replaces expensive radar and transponder interrogation equipment with relatively inexpensive optical cameras and image processing algorithms. This substitution dramatically reduces system cost while maintaining effective detection capability through computer vision techniques.
Solution Approach 2:
The system uses standard commercial cameras and processing equipment rather than specialized expensive aviation-grade systems. By utilizing off-the-shelf components, the patent achieves cost-effective collision avoidance functionality.
3Weight of moving object
If passive transponder detection is used, then system weight is reduced, but detection of objects without transponders is lost
Solution Approach 1:
The patent introduces optical cameras and image processing as an intermediary detection method. Instead of relying solely on transponders, the system uses visual intermediaries to detect aircraft characteristics, enabling identification of objects without transponders while maintaining lightweight system architecture.
Solution Approach 2:
The system changes the detection parameter from electronic transponder signals to optical visual characteristics. By detecting aircraft lights, shapes, sizes, and movement patterns optically, the patent achieves universal detection capability that works with all aircraft regardless of transponder presence.
4Device complexity
If manual pilot control is used for separation, then system complexity is reduced, but safety and separation assurance deteriorate
Solution Approach 1:
The patent implements self-service collision avoidance where the UAV autonomously detects objects, calculates separation requirements, and executes avoidance maneuvers without continuous pilot intervention. This self-service approach maintains simple system architecture while significantly improving safety assurance through automated monitoring and response.
Solution Approach 2:
The system continuously monitors the environment, compares detected object positions with safe separation parameters, and automatically adjusts flight path in response. This closed-loop feedback mechanism provides reliable safety assurance while keeping the control system relatively simple through rule-based decision logic.
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
This solution enables effective object detection and avoidance in complex airspace, ensuring safe UAV operation by identifying various objects and updating flight plans to minimize interactions, even with objects lacking transponders, thereby enhancing safety and efficiency in busy environments.
Implementation Method 1
The optical sensor may capture one or more wavelengths of electromagnetic energy including infrared and visual
Implementation Method 2
an acoustic sensor (e.g., a microphone, etc.), and/or multispectral sensor for the detection and autonomous avoidance of objects
Data Source
AI summary
This disclosure is directed to a detection and avoidance apparatus for an unmanned aerial vehicle (“UAV”) and systems, devices, and techniques pertaining to automated object detection and avoidance during UAV flight. The system may detect objects within the UAV's airspace through acoustic, visual, infrared, multispectral, hyperspectral, or object detectable signal emitted or reflected from an object. The system may identify the source of the object detectable signal by comparing features of the received signal with known sources signals in a database. The features may include, for example, an acoustic signature emitted or reflected by the object. Furthermore, a trajectory envelope for the object may be determined based on characteristic performance parameters for the object such as cursing speed, maneuverability, etc. The UAV may determine an optimized flight plan based on the trajectory envelopes of detected objects within the UAV's airspace.