Safe autonomous operations of an Unmanned Aerial System (UAS) requires that the UAS can react to unforeseen circumstances, for example, after a failure has occurred. In this paper we describe a model-based run-time architecture for autonomous on-board diagnosis, system health management, and contingency management. This architecture is being instantiated on top of NASA's Core Flight System (cFS/cFE) as amajor component of the on-board AutonomousOperating System (AOS). We will describe our diagnosis and monitoring components, which continuously provide system health status. Automated reasoning with constraint satisfaction form the core of our decision-making component, which assesses the current situation, aids in failure disambiguation, and constructs a contingency plan to mitigate the failure(s) and allow for a safe end of the mission. We will illustrate our contingency management system with two case studies, one for a fixed-wing aircraft in simulation, and one for an autonomous DJI S1000+ octo-copter.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Model-based System Health Management and Contingency Planning for Autonomous UAS



    Conference:

    AIAA SciTech Forum 2019 ; 2019 ; San Diego, CA, United States


    Publication date :

    2019-01-07


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English




    Model-based System Health Management and Contingency Planning for Autonomous UAS

    Schumann, Johann / Mahadevan, Nagabhushan / Sweet, Adam et al. | TIBKAT | 2019


    Model-based System Health Management and Contingency Planning for Autonomous UAS

    Schumann, Johann / Mahadevan, Nagabhushan / Sweet, Adam et al. | AIAA | 2019


    STOP CONTINGENCY PLANNING DURING AUTONOMOUS VEHICLE OPERATION

    CHU KEVIN / GHOSE SHIVA / HAGHIGHAT SOHRAB et al. | European Patent Office | 2018

    Free access

    Simulation-based health and contingency management

    Roemer, M.J. / Liang Tang, / Kacprzynski, G. et al. | IEEE | 2006


    Contingency Planning

    Olsen, Alexander | Springer Verlag | 2024