GUIDING AN UNMANNED AERIAL VEHICLE USING MULTI-POINT GUIDANCE

    公开(公告)号:US20240046803A1

    公开(公告)日:2024-02-08

    申请号:US17626050

    申请日:2020-07-10

    CPC classification number: G08G5/0069 G08G5/0039 G08G5/0021 G05D1/101

    Abstract: The present disclosure relates to systems, methods, and computer readable media implemented in connection with an unmanned aerial vehicle (UAV) to navigate a UAV along a desired path. For example, systems disclosed herein identify an anticipatory flight path and identify a plurality of reference points on the flight path relative to a current position of the UAV. The systems described herein may further determine reference angles between a current trajectory of the UAV and the reference points to determine an updated trajectory that the UAV should take to stay close to the identified flight path. The systems described herein may further cause the UAV to accelerate in a lateral direction based on the updated trajectory. The features and functionality of systems disclosed herein enable the UAV to accurately follow a complex path having sharp turns with little or no advanced knowledge of the flight path prior to departure.

    Vision-based fatigue crack detection using feature tracking

    公开(公告)号:US11714024B2

    公开(公告)日:2023-08-01

    申请号:US16768165

    申请日:2018-11-30

    CPC classification number: G01M5/0033 G01M5/0008 G01M5/0091

    Abstract: A computer-vision-based fatigue crack detection approach using a short video is described. Feature tracking is applied to the video for tracking the surface motion of the monitored structure under repetitive load. Then, a crack detection and localization algorithm is established to search for differential features at different frames in the video. The effectiveness of the proposed approach is validated through testing two experimental specimens with in-plane and out-of-plane fatigue cracks. Results indicate that the proposed approach can robustly identify fatigue cracks, even when the cracks are under ambient lighting conditions, surrounded by other crack-like edges, covered by complex surface textures, or invisible to human eyes due to crack closure. The approach enables accurate quantification of crack openings under fatigue loading with good accuracy.

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