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Mahadevan, Nagabhushan

Publications and source records attributed to Mahadevan, Nagabhushan.

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

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.

Schumann, Johann M.↗

Design Considerations for a Variable Autonomy Executive for UAS in the NAS

This paper describes research targeted towards an autonomy executive (AOS) for UAS in the National Air Space (NAS). The project goal is to incrementally provide the knowledge and intelligence onboard a UAS to safely fly in the National Air Space, eventually autonomous from remote human ground crews and communicating directly with air traffic control. Longer-term, the goal is to provide the capability for pilotless air vehicles such as air taxis that will be key for new transportation concepts such as air mobility-on-demand. For both of these targeted applications, AOS is incorporating artificial intelligence capabilities that operationally meet human pilot competencies. Even when autonomy is achieved from a remote human ground crew, AOS will have variable degrees of autonomy with respect to air traffic control (ATC), just as human pilots do now. AOS has the capability of interacting in natural language with ATC, as well as through data link protocols. AOS can adapt to varying levels of autonomy and control directed by ATC in standard and relaxed FAA phraseology- from being vectored moment by moment, to accepting broad directives such as following a specified aircraft or sighting and avoiding traffic. AOS can autonomously manage contingencies such as vehicle systems degradations and failures. It incorporates a decision maker that takes information from multiple diagnostic reasoners, disambiguates (if needed) sensor results to specific failures using active mode changes, then projects forward the impact of the degradation on the nominal plan. If the nominal plan is no longer viable, then alternative plans are formulated, and subsequently selected and executed, including abort options.

Lowry, Michael↗

A Framework for Reliability and Safety Analysis of Complex Space Missions

Long duration and complex mission scenarios are characteristics of NASA's human exploration of Mars, and will provide unprecedented challenges. Systems reliability and safety will become increasingly demanding and management of uncertainty will be increasingly important. NASA's current pioneering strategy recognizes and relies upon assurance of crew and asset safety. In this regard, flexibility to develop and innovate in the emergence of new design environments and methodologies, encompassing modeling of complex systems, is essential to meet the challenges.

Safety Analysis↗