A machine learning engine may correlate characteristics of obstacles identified during remotely piloted UAV flights with manual course deviations performed for obstacle avoidance. An obstacle detection application may access computer vision footage to determine notable characteristics (e.g. a direction of travel and/or velocity) of obstacles identified during the piloted UAV flights. A deviation characteristics application may access flight path information identify course deviations performed by a pilot in response to the obstacles. A machine learning engine may use the obstacle characteristic data and the deviation characteristics data as training data to generate an optimal course deviation model to use by an autopilot module to autonomously avoid obstacles during autonomous UAV flights. In creating the optimal deviation model, the training data may be processed by the machine learning engine to identify correlations between certain types of manual course deviations performed to avoid certain types of obstacles.


    Access

    Download


    Export, share and cite



    Title :

    Autonomous UAV obstacle avoidance using machine learning from piloted UAV flights


    Contributors:

    Publication date :

    2020-06-09


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / H04L TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION , Übertragung digitaler Information, z.B. Telegrafieverkehr



    Autonomous UAV obstacle avoidance using machine learning from piloted UAV flights

    YARLAGADDA PRADEEP KRISHNA | European Patent Office | 2021

    Free access


    Autonomous vision-based helicopter flights through obstacle gates

    Andert, Franz / Adolf, Florian-M. / Goormann, Lukas et al. | Tema Archive | 2010


    Q-learning for autonomous mobile robot obstacle avoidance

    Ribeiro, Tiago / Gonçalves, Fernando / Garcia, Inês et al. | BASE | 2019

    Free access

    OBSTACLE AVOIDANCE IN AUTONOMOUS VEHICLES

    COHEN OFIR / APPELMAN DINA | European Patent Office | 2021

    Free access