This research paper describes an autonomous system developed by a team of undergraduate engineering students at Embry-Riddle Aeronautical University - Prescott with support from Wisk Aero. Autonomous systems enable an electric vertical takeoff and landing (eVTOL) aircraft to perform the fundamental duties of a pilot - aviate, navigate, and communicate - without human intervention. A prototype eVTOL system, implemented as a modular payload attached to the bottom of a commercially available drone, was developed and tested to operate from the final approach through the landing phase of flight. The prototype vision-based system identifies a landing zone, and calculates relative position and orientation position without reliance on Global Positioning System (GPS) capabilities, which is potentially vulnerable to interruption and disruption. In addition, the system utilizes a machine learning approach to identify if any obstructions impact the safety of landing the aircraft. Through the development of the prototype, the findings demonstrated the viability of a computer vision-based landing system to be used on an eVTOL aircraft for the purpose of autonomous advanced air mobility (AAM) solutions.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Vision-Based Approach to Autonomous Landing of an eVTOL Aircraft in GPS-Denied Environments




    Publication date :

    2023-10-01


    Size :

    1590135 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Landing Framework and Control for EVTOL Aircraft in Urban Environments

    Meyer-Oehme, Taizo / Ginnell, Kilian / Lampl, David E. et al. | AIAA | 2023


    EVTOL AIRCRAFT

    ROSEN CHEN | European Patent Office | 2021

    Free access

    Autonomous Landing of eVTOL Vehicles Via Deep Q-Networks

    Deniz, Sabrullah / Wu, Yufei / Shi, Yang et al. | TIBKAT | 2023


    EVTOL AIRCRAFT

    NEWMAN GLEN | European Patent Office | 2023

    Free access

    Visual and Inertial Datasets for an eVTOL Aircraft Approach and Landing Scenario

    Nelson Brown / Evan Kawamura / Luke Bard et al. | NTRS