Autonomy Operatng System for UAVs: Pilot-in-a-Box

Lowry, Michael; Bajwa, Anupa; Dalal, Michael; Quach, Patrick; Castle, Patrick; Renema, Fritz; Johnson, Jonas T.; Markowsian, Lawrence; Fry, Chuck; Spinovich, Lilly; Karsai, Gábor; Schumann, Johann; Rozier, Kristen; Rozier, Eric W. D.; Rajan, Sanjay

doi:10.2514/6.2017-4272

Cited by 5 publications

(7 citation statements)

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“…(Windhover Labs is developing an autopilot that interfaces directly through the software bus.) AOS has focused on the mission computer and integration of a critical mass of Artificial Intelligence capabilities in order to enable autonomy [4]. The artificial intelligence (AI) elements-in yellow-consist of reasoning components that themselves serve as integration points.…”

Section: Aos and Artificial Intelligencementioning

confidence: 99%

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

Lowry

Bajwa

Pressburger

et al. 2018

2018 AIAA Information Systems-Aiaa Infotech @ Aerospace

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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. https://ntrs.nasa.gov/search.jsp?R=20180004247 2019-07-07T08:54:28+00:00Z I. Nomenclature DF = a leg type for waypoint to waypoint navigation, part of ARINC 424 HIL = Hardware Integration Laboratory IVHM = Integrated Vehicle Health Management MTL = Metric Temporal Logic NAS = National Air Space SIL = Software Integration Laboratory UAS = Unmanned Aircraft System UTM = UAS Traffic Management VI = a leg type for intercept to course, part of ARINC 424

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Section: Aos and Artificial Intelligencementioning

confidence: 99%

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

Lowry

Bajwa

Pressburger

et al. 2018

2018 AIAA Information Systems-Aiaa Infotech @ Aerospace

Self Cite

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“…λ ir extends the simply-type lambda calculus in a style similar to [10]. This combination is arguably closer to the adoption of message-passing concurrency in practice [13,5,11,27,22], while remaining small enough to highlight the foundation nature of intensional receive.…”

Section: Figure 24 An Example Of the Receive Expression Supporting Multiplexingmentioning

confidence: 97%

“…Over the last decade, message passing concurrency has re-emerged as one of the dominant programming models for concurrency, as evidenced by the success of Scala actors [13], Akka [5], Panini [3] and Go [11] among others. The future of embedded systems depends on developments in message-passing architectures, including the Robot Operating System (ROS) [27] and NASA's new Autonomy Operating System (AOS) [22]. There is significant interest in understanding the theoretical properties of the message passing model further for enabling reasoning about behaviors of critical concurrent programs, e.g.…”

Section: Chapter 1 Introductionmentioning

confidence: 99%

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λir : A language with intensional receive

Priya¹

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“…• A message-passing version of R2U2 is integrated into the AOS (Autonomy Operating System) [11], which is built on top of NASA's cFE/cFS (core Flight Executive/core Flight System) software 4 . During flight, the R2U2 application monitors messages on the software bus that contain sensor and software data and publishes outputs to the message bus to update other apps on the current system health.…”

Section: R2u2 Realizationsmentioning

confidence: 99%

R2U2: Tool Overview

Rozier

Schumann

Kalpa Publications in Computing

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R2U2 (Realizable, Responsive, Unobtrusive Unit) is an extensible framework for runtime System Health Management (SHM) of cyber-physical systems. R2U2 can be run in hardware (e.g., FPGAs), or software; can monitor hardware, software, or a combination of the two; and can analyze a range of different types of system requirements during runtime. An R2U2 requirement is specified utilizing a hierarchical combination of building blocks: temporal formula runtime observers (in LTL or MTL), Bayesian networks, sensor filters, and Boolean testers. Importantly, the framework is extensible; it is designed to enable definitions of new building blocks in combination with the core structure. Originally deployed on Unmanned Aerial Systems (UAS), R2U2 is designed to run on a wide range of embedded platforms, from autonomous systems like rovers, satellites, and robots, to human-assistive ground systems and cockpits.R2U2 is named after the requirements it satisfies; while the exact requirements vary by platform and mission, the ability to formally reason about Realizability, Responsiveness, and Unobtrusiveness is necessary for flight certifiability, safety-critical system assurance, and achievement of technology readiness levels for target systems. Realizability ensures that R2U2 is sufficiently expressive to encapsulate meaningful runtime requirements while maintaining adaptability to run on different platforms, transition between different mission stages, and update quickly between missions. Responsiveness entails continuously monitoring the system under test, real-time reasoning, reporting intermediate status, and as-early-as-possible requirements evaluations. Unobtrusiveness ensures compliance with the crucial properties of the target architecture:

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Autonomy Operatng System for UAVs: Pilot-in-a-Box

Cited by 5 publications

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

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

λir : A language with intensional receive

R2U2: Tool Overview

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