Wing Aviation LLC

Domitille Commun

Ali Shoeb

Dinuka Abeywardena

Kyle Krafka

Konstantin Bozhkov

Xinzhi Fan

Linhao Jin

A technique performed by UAV delivery system includes: arriving by a UAV of over a destination area; capturing a plurality of aerial images of a scene at the destination area with an onboard camera system of the UAV while flying above the destination area, wherein the aerial images capture the scene from a plurality of UAV vantage points offset from each other; optimizing weights of a generative neural network (GNN) using at least some of the aerial images as a training dataset to encode a volumetric representation of the scene into the GNN, wherein the weights are optimized by an onboard processing system of the UAV; and communicating the GNN with the weights optimized to a backend datacenter in communication with the UAV to transmit the volumetric representation of the scene over which the UAV flew without transmitting the aerial images themselves to the backend datacenter.

Compressing a scene into a generative neural network for UAV scene analysis applications

A method of operation of an unmanned aerial vehicle (UAV) service includes acquiring aerial images of a scene at an area of interest (AOI), wherein the aerial images are acquired with a UAV of the UAV service during a flight mission of the UAV that passes over the AOI; uploading a mission log of the flight mission to a backend data system of the UAV service, the mission log including image data that includes, or is derived from, at least a portion of the aerial images; and training a neural radiance field (NeRF) model with one or more of the aerial images, wherein the NeRF model comprises a neural network, which after the training, encodes a volumetric representation of the scene capable of generating novel views of the scene different than any of the aerial images used to train the NeRF model.

Using NeRF models to facilitate operations of a UAV delivery service

Techniques for identifying a close encounter between an aircraft and an obstacle are disclosed. The technique includes acquiring a video stream of a ground area below the aircraft with a stereovision camera system disposed onboard the aircraft. A depth perception map is generated with a stereovision processing pipeline indicating stereovision depth estimates of first image pixels from the video stream. An optical flow map is generated with an optical flow processing pipeline indicating optical flow depth estimates of second image pixels from the video stream. The depth perception and optical flow maps are compared. An encounter flag indicating that the close encounter between the aircraft and the obstacle occurred is asserted based at least on the comparing.

Growing community of inventors

Mountain View, CA, United States of America

Domitille Commun