Refined searching based on detected object configurations is provided by training a machine learning model to identify non-naturally occurring object configurations, acquiring images of an initial search area based on scanning it using a camera-equipped autonomous aerial vehicle operating in accordance with an initial automated flight plan defining the initial search area, analyzing the acquired images using the trained machine learning model and identifying that an object configuration is a non-naturally occurring object configuration, then based on identifying the non-naturally occurring object configuration, refining the initial automated flight plan to obtain a modified automated flight plan defining a different search area as compared to the initial search area, and initiating autonomous aerial scanning of the different search area in accordance with the modified automated flight plan.


    Access

    Download


    Export, share and cite



    Title :

    REFINED SEARCHING BASED ON DETECTED OBJECT CONFIGURATIONS



    Publication date :

    2021-07-08


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06V / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



    Cellular automaton simulations of a T-shaped unsignalised intersection with refined configurations

    Jin, Cheng-Jie / Wang, Wei / Jiang, Rui | Taylor & Francis Verlag | 2014


    Real-time object subspace searching based on discrete searching paths and local energy

    Zhou, W. J. / Fei, Z. X. / Hu, H. S. et al. | British Library Online Contents | 2016


    Object searching method and system

    HUANG YAOMING | European Patent Office | 2020

    Free access


    TRANSMITTTING INFORMATION ABOUT A DETECTED OBJECT

    GRAZIOLI FILIPPO / MÖLLER SVEN / UNZUETA MARC et al. | European Patent Office | 2025

    Free access