AUTOMATED AND ADAPTIVE THREE-DIMENSIONAL ROBOTIC SITE SURVEYING

    公开(公告)号:US20190228573A1

    公开(公告)日:2019-07-25

    申请号:US15879743

    申请日:2018-01-25

    摘要: A method for generating a three-dimensional model of an asset includes receiving input parameters corresponding to constraints of a mission plan for operating an unmanned vehicle around an asset, generating the mission plan based on the input parameters including information of a representative asset type, wherein the mission plan includes waypoints identifying locations and orientations of one or more image sensors of the unmanned vehicle, generating a flight path for the unmanned vehicle connecting the waypoints that satisfy one or more predefined criteria, monitoring a vehicle state of the unmanned vehicle during execution of the flight path from one waypoint to the next waypoint, determining, at each waypoint, a local geometry of the asset sensed by the one or more image sensors, changing the mission plan on-the-fly based on the local geometry, and capturing images of the asset along waypoints of the changed mission plan.

    SYSTEMS AND METHODS ASSOCIATED WITH UNMANNED AERIAL VEHICLE TARGETING ACCURACY

    公开(公告)号:US20190204123A1

    公开(公告)日:2019-07-04

    申请号:US15861054

    申请日:2018-01-03

    摘要: System and methods may evaluate and/or improve target aiming accuracy for a sensor of an Unmanned Aerial Vehicle (“UAV”). According to some embodiments, a position and orientation measuring unit may measure a position and orientation associated with the sensor. A pose estimation platform may execute a first order calculation using the measured position and orientation as the actual position and orientation to create a first order model. A geometry evaluation platform may receive planned sensor position and orientation from a targeting goal data store and calculate a standard deviation for a target aiming error utilizing: (i) location and geometry information associated with the industrial asset, (ii) a known relationship between the sensor and a center-of-gravity of the UAV, (iii) the first order model as a transfer function, and (iv) an assumption that the position and orientation of the sensor have Gaussian-distributed noises with zero mean and a pre-determined standard deviation.

    SELF-LOCALIZED MOBILE SENSOR NETWORK FOR AUTONOMOUS ROBOTIC INSPECTION

    公开(公告)号:US20180329433A1

    公开(公告)日:2018-11-15

    申请号:US15591400

    申请日:2017-05-10

    IPC分类号: G05D1/10

    摘要: Provided are systems and methods for autonomous robotic localization. In one example, the method includes receiving ranging measurements from a plurality of fixed anchor nodes that each have a fixed position and height with respect to the asset, receiving another ranging measurement from an aerial anchor node attached to an unmanned robot having a dynamically adjustable position and height different than the fixed position and height of each of the plurality of anchor nodes, and determining a location of the autonomous robot with respect to the asset based on the ranging measurements received from the fixed anchor nodes and the aerial anchor node, and autonomously moving the autonomous robot about the asset based on the determined location.