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US 11,783,715 B2Granted
Unmanned aerial vehicle with neural network for enhanced mission performance
AssigneeDrobotics, LLC
InventorEyal Stein
Life of this patent
Estimating the term…
Abstract
An unmanned aerial vehicle (UAV) or “drone” executes a neural network to assist with inspection, surveillance, reporting, and other missions. The drone inspection neural network may monitor, in real time, the data stream from a plurality of onboard sensors during navigation to an asset along a preprogrammed flight path and/or during its mission (e.g., as it scans and inspects an asset).
Claims21
An unmanned aerial vehicle (UAV) comprising:
- a flight package;
- a navigation system;
- an image-acquisition device;
- a communication facility;
- a computer memory;
- and
- a computer including a processor and electronically stored instructions, executable by the processor, for:
- causing the UAV to autonomously execute a preliminary flight plan around an asset to be inspected,
- using data received from the image-acquisition device as input to a neural-network-based predictor that has been computationally trained to identify and classify objects appearing in images acquired by the image-acquisition device during the preliminary flight plan,
- during analysis of the data received from the image-acquisition device, detecting a feature requiring an update to the predictor,
- requesting and receiving, in real time, an updated predictor computationally trained based on the detected feature, and
- based on (a) object classifications made by the predictor during the preliminary flight plan and (b) the updated predictor, computing and autonomously executing a revised flight plan around the asset
- wherein:
- the computer is configured to analyze the detected feature in real-time and classify the detected feature as normal or anomalous;
- and
- when the detected feature is classified as anomalous, the computer is configured to request airspace authorization and receive updated configuration files for additional inspection of the asset.
13 more elements
A method of inspecting an asset using an unmanned aerial vehicle (UAV), the method comprising the steps of:
- acquiring digital images in real time during an autonomous flight of the UAV in accordance with a preliminary flight plan around an asset to be inspected;
- computationally analyzing the acquired digital images with a neural-network-based predictor that has been computationally trained to identify and classify objects appearing in the images;
- during the analysis of the acquired digital images, computationally detecting a feature requiring an update to the predictor;
- while the UAV is in flight, requesting and receiving, in real time, an updated predictor computationally trained based on the detected feature;
- and
- while the UAV is in flight, and based on (a) object classifications made by the predictor during the preliminary flight plan and (b) the updated predictor, computing and autonomously executing a revised flight plan around the asset,
- the method further comprising:
- analyzing the detected feature in real-time and classifying the detected feature as normal or anomalous;
- and
- when the detected feature is classified as anomalous, requesting airspace authorization and receiving updated configuration files for additional inspection of the asset.
7 more elements
Dependencies are inferred from the claim text.