Systems and methods for creating an occupancy map based on an objective function

    公开(公告)号:US11495030B1

    公开(公告)日:2022-11-08

    申请号:US16712946

    申请日:2019-12-12

    Abstract: Described are systems and methods to utilize an objective function of an aerial vehicle in constructing and/or updating an occupancy map. The described systems and methods can determine whether to include, add, and/or remove an object from an occupancy map based on one or more confidence score(s) that can be determined for the presence (or absence) of an object at a given location. The confidence score for an object at a given location can be determined, for example, based on various sources of information, which can each be provided different weights, parameters, thresholds, etc. based on the objective function of the aerial vehicle.

    Automated air traffic control systems and methods

    公开(公告)号:US11107360B1

    公开(公告)日:2021-08-31

    申请号:US16553677

    申请日:2019-08-28

    Abstract: Automated air traffic control systems and methods may include one or more sensors, such as radar sensors, that are positioned and oriented at opposite ends of a runway. The sensors may detect aerial vehicles on the runway, as well as aerial vehicles within approach corridors at opposite ends of the runway, and other aerial vehicles proximate the runway. Based on data received by the sensors, various characteristics of aerial vehicles can be determined, and instructions for the aerial vehicles can be determined based on the detected characteristics. Then, the aerial vehicles may utilize the determined instructions to coordinate their operations proximate the runway, which may include takeoff, taxiing, and/or landing operations. Further, speech-to-data processing may be used to translate between data and speech or audio input/output in order to enable coordination between unmanned aerial vehicles, manned aerial vehicles, and combinations thereof.

    Determining integrity of acoustically excited objects

    公开(公告)号:US11097856B1

    公开(公告)日:2021-08-24

    申请号:US16838695

    申请日:2020-04-02

    Abstract: A vibrometric signature for a vehicle, or a set of one or more frequencies where vibration of the vehicle is naturally observed in the presence of excitation, may be generated and used to make one or more determinations regarding the integrity or suitability of the vehicle for one or more missions. When the vehicle is subjected to excitation over a range of frequencies, images of the vehicle are captured, and power levels of vibrations of the vehicle are calculated based on the images. A vibrometric signature is generated based on the power levels of the vibrations, and compared to vibrometric signatures previously generated for the aerial vehicle, or to vibrometric signatures associated with one or more other vehicles, or anomalies experienced by such other vehicles, to determine whether the vehicle may be cleared for the performance of one or more missions, or whether maintenance or inspections are required.

    MAINTAINING ATTITUDE CONTROL OF UNMANNED AERIAL VEHICLES BY VARYING CENTERS OF GRAVITY

    公开(公告)号:US20210107633A1

    公开(公告)日:2021-04-15

    申请号:US16992074

    申请日:2020-08-12

    Abstract: Aerial vehicles may be configured to control their attitudes by changing one or more physical attributes. For example, an aerial vehicle may be outfitted with propulsion motors having repositionable mounts by which the motors may be rotated about one or more axes, in order to redirect forces generated by the motors during operation. An aerial vehicle may also be outfitted with one or more other movable objects such as landing gear, antenna and/or engaged payloads, and one or more of such objects may be translated in one or more directions in order to adjust a center of gravity of the aerial vehicle. By varying angles by which forces are supplied to the aerial vehicle, or locations of the center of gravity of the aerial vehicle, a desired attitude of the aerial vehicle may be maintained irrespective of velocity, altitude and/or forces of thrust, lift, weight or drag acting upon the aerial vehicle.

    Determining relative positions and trusting data based on locally sensed events

    公开(公告)号:US10944573B1

    公开(公告)日:2021-03-09

    申请号:US15860589

    申请日:2018-01-02

    Abstract: Devices or systems such as aerial vehicles may determine that they are located within a common locality based on data captured during an event, such as the emission of light, sound or other matter or energy. Where sensors associated with such devices or systems are each determined to have captured data associated with the event, the devices or systems may be determined to have been located within a common locality during the event. The locality may be defined with respect to the data or the devices or systems, e.g., a range associated with the data or the event, on any basis. A relative distance between the devices or systems may be determined based on the data captured during the event. Additionally, where two or more devices or systems are determined to have been located within a common locality, data exchanged therebetween may be trusted by each of such devices or systems.

    Automated pre-flight and in-flight testing of aerial vehicles by machine learning

    公开(公告)号:US10810501B1

    公开(公告)日:2020-10-20

    申请号:US15789185

    申请日:2017-10-20

    Abstract: Data captured during evolutions performed by aerial vehicles prior to one or more missions, and data regarding outcomes of the missions, may be used to train a machine learning system to predict data regarding an outcome of a mission of an aerial vehicle based on the performance of the aerial vehicle during one or more evolutions. The data may be captured by sensors provided aboard an aerial vehicle, or in association with a testing facility, and may include data captured during both pre-flight and/or in-flight evolutions performed by the aerial vehicle. The evolutions may include any pre-flight operation of motors, propellers and/or control surfaces, or any other components, as well as the in-flight operation of such components. If a machine learning system determines that a mission is unlikely to succeed, the mission may be canceled, delayed until further inspections may be performed, or assigned to another aerial vehicle.

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