Backup navigation system for unmanned aerial vehicles

    公开(公告)号:US11656638B1

    公开(公告)日:2023-05-23

    申请号:US17133610

    申请日:2020-12-23

    Abstract: Described is a method that involves operating an unmanned aerial vehicle (UAV) to begin a flight, where the UAV relies on a navigation system to navigate to a destination. During the flight, the method involves operating a camera to capture images of the UAV's environment, and analyzing the images to detect features in the environment. The method also involves establishing a correlation between features detected in different images, and using location information from the navigation system to localize a feature detected in different images. Further, the method involves generating a flight log that includes the localized feature. Also, the method involves detecting a failure involving the navigation system, and responsively operating the camera to capture a post-failure image. The method also involves identifying one or more features in the post-failure image, and determining a location of the UAV based on a relationship between an identified feature and a localized feature.

    Systems and methods for generating annotations of structured, static objects in aerial imagery using geometric transfer learning and probabilistic localization

    公开(公告)号:US11100667B2

    公开(公告)日:2021-08-24

    申请号:US16669309

    申请日:2019-10-30

    Abstract: In some embodiments, aerial images of a geographic area are captured by an autonomous vehicle. In some embodiments, the locations of structures within a subset of the aerial images are manually annotated, and geographical locations of the manual annotations are determined based on pose information of the camera. In some embodiments, a machine learning model is trained using the manually annotated aerial images. The machine learning model is used to automatically generate annotations of other images of the geographic area, and the geographical locations determined from the manual annotations are used to determine an accuracy probability of the automatic annotations. The automatic annotations determined to be accurate may be used to re-train the machine learning model to increase its precision and recall.

    Detection of environmental changes to delivery zone

    公开(公告)号:US11587241B2

    公开(公告)日:2023-02-21

    申请号:US16887404

    申请日:2020-05-29

    Abstract: A technique for detecting an environmental change to a delivery zone via an unmanned aerial vehicle includes obtaining an anchor image and an evaluation image, each representative of the delivery zone, providing the anchor image and the evaluation image to a machine learning model to determine an embedding score associated with a distance between representations of the anchor image and the evaluation image within an embedding space, and determining an occurrence of the environmental change to the delivery zone when the embedding score is greater than a threshold value.

    DETECTION OF ENVIRONMENTAL CHANGES TO DELIVERY ZONE

    公开(公告)号:US20210374975A1

    公开(公告)日:2021-12-02

    申请号:US16887404

    申请日:2020-05-29

    Abstract: A technique for detecting an environmental change to a delivery zone via an unmanned aerial vehicle includes obtaining an anchor image and an evaluation image, each representative of the delivery zone, providing the anchor image and the evaluation image to a machine learning model to determine an embedding score associated with a distance between representations of the anchor image and the evaluation image within an embedding space, and determining an occurrence of the environmental change to the delivery zone when the embedding score is greater than a threshold value.

    MAP INCLUDING DATA FOR ROUTING AERIAL VEHICLES DURING GNSS FAILURE

    公开(公告)号:US20210150917A1

    公开(公告)日:2021-05-20

    申请号:US16689872

    申请日:2019-11-20

    Abstract: An unmanned aerial vehicle (UAV) includes a propulsion system, a global navigation satellite system (GNSS) sensor, a camera and a controller. The controller includes logic that, in response to execution by the controller, causes the UAV to in response to detecting a loss of tracking by the GNSS sensor determine an estimated location of the UAV on a map based on a location image captured by the camera, determine a route to a destination using tracking parameters embedded in the map, wherein the map is divided into a plurality of sections and the tracking parameters indicate an ease of determining a location of the UAV using images captured by the camera with respect to each section, and control the propulsion system to cause the UAV to follow the route to the destination.

    Backup Navigation System for Unmanned Aerial Vehicles

    公开(公告)号:US20200026902A1

    公开(公告)日:2020-01-23

    申请号:US16411576

    申请日:2019-05-14

    Abstract: Described is a method that involves operating an unmanned aerial vehicle (UAV) to begin a flight, where the UAV relies on a navigation system to navigate to a destination. During the flight, the method involves operating a camera to capture images of the UAV's environment, and analyzing the images to detect features in the environment. The method also involves establishing a correlation between features detected in different images, and using location information from the navigation system to localize a feature detected in different images. Further, the method involves generating a flight log that includes the localized feature. Also, the method involves detecting a failure involving the navigation system, and responsively operating the camera to capture a post-failure image. The method also involves identifying one or more features in the post-failure image, and determining a location of the UAV based on a relationship between an identified feature and a localized feature.

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