Rotorcraft Object Detection for Rotor Blade Strike Avoidance
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Solution Overview
Problem
Piloting a rotorcraft is challenging due to the difficulty in detecting low-visibility objects, such as fences, power lines, and rotor blades of other aircraft, which increases the risk of rotor blade strikes.
Innovation Solution
The use of artificial intelligence (AI) models to process image information from sensors mounted on the rotorcraft, enabling the detection of objects and determination of their distance to facilitate avoiding collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If human eye and environmental detection systems are used to detect objects, then the system is simple, but the detection capability for low-visibility objects is insufficient
Solution Approach 1:
The patent replaces human visual detection and conventional environmental detection systems with an AI-based computer vision system. Image sensors capture visual data, which is then processed by trained AI models to detect low-visibility objects such as power lines, fences, and trees. This substitution transforms the detection mechanism from biological/conventional mechanical systems to an intelligent computational system, significantly improving detection precision while maintaining manageable complexity.
2Measurement precision
If AI models are used to process image information and detect objects, then object detection precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary AI processing layer between image sensors and the collision avoidance system. Trained AI models serve as mediators that process raw image data, extract meaningful object information, and provide structured output to the flight control system. This intermediary layer manages complexity by encapsulating sophisticated image processing within modular AI components, allowing high detection precision without overwhelming system complexity.
Solution Approach 2:
The patent applies preliminary action by pre-training AI models with extensive datasets before deployment. The AI models are trained in advance to recognize various objects including low-visibility items, power lines, and natural features. This preliminary training equips the system with pre-acquired knowledge, enabling it to perform complex detection tasks during operation without requiring real-time computational complexity to be excessively high.
3Reliability
If multiple image sensors and AI models are deployed for comprehensive object detection, then detection reliability is improved, but energy consumption increases
Solution Approach 1:
The patent implements multi-functionality by designing an integrated system where image sensors serve multiple purposes: detecting objects, determining their spatial location, and providing data for collision avoidance. The AI models perform multiple functions including object recognition, classification, and distance estimation. This universal approach improves detection reliability through comprehensive data collection while managing energy consumption by consolidating multiple functions into a unified processing architecture rather than requiring separate dedicated systems for each function.
Data Source
AI summary
In certain embodiments, a method includes accessing image information generated by one or more image sensors configured to generate the image information for a surrounding environment of a rotorcraft. The method includes causing one or more AI models to process the image information to generate proximity information for the image information. The proximity information includes depth measurements for one or more image objects from the image information that correspond to one or more physical objects in the surrounding environment of the rotorcraft. The method includes initiating, in response to generating the proximity information from the image information, further analysis of the proximity information for the one or more image objects to facilitate avoiding, based on the proximity information, a collision of a rotor blade of the rotorcraft with the one or more physical objects that correspond to the one or more image objects.