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148 records · Page 9

NASA Pilot-Engaged Expert Response Using IBM Watson Technology: Prototype Evaluation of Knowledge Retrieval System

NASA Langley Research Center and IBM have been investigating the use of IBM Watson technology in aerospace research and development. One application of Watson technology is the Pilot-Engaged Expert Response (PEER) use case. The PEER system is envisioned as an in-cockpit advisor that will act as a source of situationally-relevant information for pilots and other flight crew members to assist in decision making about real-time events and situations that arise in the course of aircraft operations. PEER will make available vast stores of knowledge and information quickly and directly, putting important informational resources where they are needed most. IBM has worked with NASA to develop an architecture and articulate a roadmap for the development of the PEER system. That vision is built around Watson Discovery Advisor (WDA) software solution, derived from IBM's Jeopardy!-winning automatic question answering system. PEER makes use of WDA's sophisticated question-answering capabilities as its core, adding important User Interface components and other customizations for the cockpit environment, including communication with flight systems and other external data sources. The development plan for PEER includes four development stages, with the current project constituting the first phase. In this project, a prototype instance of PEER was successfully adapted to the aviation domain, enabling users to ask questions about aviation topics and receive useful and accurate answers to these questions. Major tasks accomplished include the development of procedures for domain adaptation through automatic lexicon extraction from domain glossaries; generation of question-answer training data which was used to train the system; and assessment of the effectiveness of domain adaptation, which showed a dramatic improvement in the ability of the PEER system to answer domain-relevant questions. In addition, the vision for the PEER system was pushed forward by the articulation of a plan for the automatic enhancement of question-answering with contextual information. This initial phase focused on two main goals: 1) the targeted domain adaptation of the underlying WDA system to the aviation domain; and, 2) the design of the software systems needed to leverage flight-contextual data. Domain adaptation of the WDA system proceeds via three main activities: Domain data ingestion, lexical customization and model training. A textual corpus consisting of 1,147 individual documents with more than 7.5 million words of text was ingested into the system and this served as the basis of all further development. A domain lexicon of over 3,500 aviation-domain terms was semi-automatically generated from domain documents and used to train the system. In addition, a set of over 500 question-answer (QA) pairs relevant to the PEER use case was developed; these were used to train and assess the system. These important first steps established the basis for the PEER system. In addition, steps were taken towards the integration of the PEER system into the cockpit environment with the development of a functional design for the Contextual Data Augmentation (CDA) subsystem. This subsystem brings to bear contextual data to improve system responses. It has three main submodules: the Contextual Data Collection module, the Contextual Data Selection module, and the Contextual QA Augmentation module. These modules form a processing pipeline that addresses the problems associated with automatically integrating information from external resources into the knowledge-retrieval mechanism.

Machine learning↗

Maneuver Design and Calibration for the Genesis Spacecraft

Genesis is the fifth mission selected as part of NASA's Discovery Program. The objective of Genesis is to collect solar wind samples for a period of approximately two years while in a halo orbit about the Earth-Sun L I point. At the end of this period, the samples are to be returned to a specific recovery point on the Earth for subsequent analysis. This goal has never been attempted before and presents a formidable challenge in terms of mission design and operations, particularly planning and execution of propulsive maneuvers. To achieve a level of cost-effectiveness consistent with a Discovery-class mission, the Genesis spacecraft design was adapted to the maximum extent possible from designs used on earlier missions, such as Mars Global Surveyor (MGS) and Stardust, another sample collection mission. The spacecraft design for Genesis is shown. Spin stabilization was chosen for attitude control, in lieu of three-axis stabilization, with neither reaction wheels nor accelerometers included. This precludes closed-loop control of propulsive maneuvers and implies that any attitude changes, including spin changes and precessions, will behave like translational propulsive maneuvers and affect the spacecraft trajectory. Moreover, to minimize contamination risk to the samples collected, all thrusters were placed on the side opposite the sample collection canister. The orientation and characteristics of thrusters are indicated. For large maneuvers (>2.5 m/s), two 5 lbf thrusters will be used for delta v, with precession to the burn attitude, followed by spin-up from 1.6 to 10 rpm before the burn and spin down to 1.6 rpm afterwards, then precession back to the original spin attitude. For small maneuvers (<2.5 m/s), no spin change is needed and four 0.2 lbf thrusters are used for Av. Single or double 360 deg. precession changes are required whenever the desired delta v falls inside the two-way turn circle (about 0.4 m/s) based on the mass properties, spin rate and lever arm lengths based on thruster locations. In such instances, delta v resulting from spacecraft precession cannot be used effectively as a component of the desired delta v, and must therefore be removed by precessing at least one complete revolution around the turn circle. To eliminate cross-track execution errors, a second revolution in the opposite direction would also be performed. This paper will address the design of propulsive maneuvers in light of the aforementioned challenges and other constraints. Maneuver design will be performed jointly by the Navigation Team at JPL and the Spacecraft Team at LMA, based on the process indicated . Typical maneuver timelines will be presented which address considerations introduced by attitude changes. These include nutation, which is introduced by precessing or spinning down and must be given sufficient time to damp out prior to execution of subsequent events, as well as sun and earth pointing constraints, which must be considered to ensure sufficient spacecraft power and to minimize telecommunications interruptions, respectively. The paper will include a description of how individual propulsive maneuvers are resolved into components to account for delta v from translational burns and spacecraft attitude changes required to carry out such maneuvers. Contributions to maneuver delta v arising from attitude changes, based on mass properties for the period just after launch, are indicated. Similar curves will be presented spanning all mission phases from launch through return. A set of closed-form equations for resolving maneuver components, base on a specific delta v required for correction or deterministic changes to the spacecraft trajectory will be presented, as well. In addition to nominal maneuvers, special calibration maneuvers are planned to improve open-loop modeling of maneuvers and to reduce execution errors. Uncalibrated execution errors are indicated. Such errors could be reduced by 50% or more over the course of the mission. Special calibrations are of particular importance for the return leg of the mission, since the sample canister must be returned to a specific location within the Utah Test and Training Range (UTTR) for mid-air retrieval. An entry angle tolerance of no less than +/- 0.08 deg. is required to achieve this objective. Biasing of the final return maneuvers coupled with a specific maneuver mode to use a series of well-characterized spin changes to effect these maneuvers is part of the current Genesis baseline mission plan. Another important objective of calibrations is to better characterize precession maneuvers. Such maneuvers are part of most propulsive maneuvers, but are also required periodically to maintain sun-pointing for power or daily during solar-wind pointing during collection periods. Although relatively small, such maneuvers will have a significant cumulative impact on orbit determination, particularly in the halo portion of the mission. The current mission design also calls for three stationkeeping maneuvers during each halo orbit of approximately six months duration. These stationkeeping maneuvers may be sufficiently small that single or double 360 deg. precession changes may be required. Because there are no accelerometers on board the spacecraft, calibration can only be performed with the aid of ground-based radiometric tracking. To establish a high degree of accuracy in characterizing the magnitude of burns, the spacecraft spin axis should be along the line of sight to the Earth, providing Doppler measurements with <1 mm/sec accuracy in S-Band. Emission constraints allow such alignment only during certain portions of the mission when the Earth-spacecraft-sun geometry is favorable. The impact of precessions, or burns at times when geometry is not favorable, can be assessed by reconstruction of the spacecraft trajectory using tracking arcs of several days before and after the event.

Williams, Kenneth E.↗

Distributed Spacecraft Autonomy - Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC) measurements. DSA will be demonstrated onboard the NASA Ames Starling mission – a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets. The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasmasphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input dataset for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software, aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements, which define the range of observability for the satellites, as well as exploitative measurements, which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth’s magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions. As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown. Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middleware provides reliable delivery, routing, and topic subscription features over User Datagram Protocol (UDP). Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarm scalability from 2 satellites to 100 satellites is shown.

Distributed Autonomy↗

Distributed Spacecraft Autonomy (DSA): Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC)measurements. DSA will be demonstrated on board the NASA Ames Starling mission a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets.The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasma sphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input data set for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software,aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements,which define the range of observability for the satellites, as well as exploitative measurements,which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth's magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions.As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown.Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middle ware provides reliable delivery, routing, and topic subscription features over User Data gram Protocol (UDP).Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarms calability from 2 satellites to 100 satellites is shown.

Fugate, Jason↗