SEARCH · Search NASA

Results for “autonomous flight dynamics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

NASA NTRS1988

An intelligent training system for space shuttle flight controllers

An autonomous intelligent training system which integrates expert system technology with training/teaching methodologies is described. The system was designed to train Mission Control Center (MCC) Flight Dynamics Officers (FDOs) to deploy a certain type of satellite from the Space Shuttle. The Payload-assist module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system consists of five components: a user interface, a domain expert, a training session manager, a trainee model, and a training scenario generator. The interface provides the trainee with information of the characteristics of the current training session and with on-line help. The domain expert (Dep1Ex for Deploy Expert) contains the rules and procedural knowledge needed by the FDO to carry out the satellite deploy. The Dep1Ex also contains mal-rules which permit the identification and diagnosis of common errors made by the trainee. The training session manager (TSM) examines the actions of the trainee and compares them with the actions of Dep1Ex in order to determine appropriate responses. A trainee model is developed for each individual using the system. The model includes a history of the trainee's interactions with the training system and provides evaluative data on the trainee's current skill level. A training scenario generator (TSG) designs appropriate training exercises for each trainee based on the trainee model and the training goals. All of the expert system components of PD/ICAT communicate via a common blackboard. The PD/ICAT is currently being tested. Ultimately, this project will serve as a vehicle for developing a general architecture for intelligent training systems together with a software environment for creating such systems.

Loftin, R. Bowen↗

NASA NTRS1996

South Atlantic Anomaly Entry and Exit as Measured by the X-Ray Timing Explorer

The Rossi X-ray Timing Explorer (RXTE) carries instruments that must switch off high voltages (HV) when passing through the South Atlantic Anomaly (SAA). The High Energy X-ray Timing Experiment (HEXTE) contains a particle monitor that detects the increased particle flux associated with the SAA and autonomously reduces its voltage. The Proportional Counter Array (PCA) relies on uplinked predictions of SAA entry/exit times based on ephemeris data provided by the Flight Dynamics Facility. A third instrument, the All-Sky Monitor (ASM) also uses a predicted SAA model to reduce voltage when passing through the SAA. Data collected from the HEXTE particle monitor, as well as other instrument readings near the times of SAA entry/exit offer the potential for refining models of the boundaries of the SAA. The SAA has an increased particle flux which causes high rates of detection in the RXTE instruments designed to observe x-rays. The high counting rates could degrade the PCA if HV is not reduced during SAA passages. On the other hand, PCA downtime can be minimized and the science return can be optimized by having the best possible model of the SAA boundary. Thus, the PCA team planned an extensive effort during in-orbit checkout to utilize both the HEXTE particle monitor data and instrument counting rates to refine the model of the SAA boundary. The times of SAA entry and exit are compared with the definitive epemeris to determine the precise location (latitude and longitude) of the SAA boundary. Over time, the SAA and its perimeter were mapped. The RXTE Science Operations Center is continuously working to feed back the results of this effort into the science scheduling process, improving the SAA model as it affects the RXTE instruments, thus obtaining more accurate estimates of the SAA entry/exit times.

Smith, Evan↗

NASA NTRS2012

NASA Dryden Status: Aerospace Control and Guidance Sub-Committee Meeting 109

NASA Dryden has been engaging in some exciting work that will enable lighter weight and more fuel efficient vehicles through advanced control and dynamics technologies. The main areas of emphasis are Enabling Light-weight Flexible Structures, real time control surface optimization for fuel efficiency and autonomous formation flight. This presentation provides a description of the current and upcoming work in these areas. Additionally, status is for the Dreamchaser pilot training activity and KQ-X autonomous aerial refueling.

Jacobson, Steven R.↗

NASA NTRS2012

NASA Dryden Status

NASA Dryden has been engaged in exciting work that will enable lighter weight and more fuel efficient vehicles through advanced control and dynamics technologies. The main areas of emphasis are Enabling Light-weight Flexible Structures, real time control surface optimization for fuel efficiency and autonomous formation flight. This presentation provides a description of the current and upcoming work in these areas. Additionally, status is provided Dryden's work on HTV-2.

Jacobson, Steve↗

NASA NTRS2021

Case Studies in Verifying Spacecraft Autonomy

Spacecraft, operating with a time-to-effect faster than human command response, or with absent or delayed communication, have depended on autonomy. It is likely that this reliance will continue, and increase further in future missions. Spacecraft autonomy is used when operator intervention is not available or feasible, or when dynamic aspects of a spacecraft situation cannot be predicted in advance. This paper provides case studies of several successfully verified autonomous software systems across multiple spacecraft, flight phases (launch, transit, entry and landing, science utilization), and software classifications, and can serve as examples to future missions in methods of successfully assuring spacecraft autonomy.

Johnson, Stephen B.↗

NASA NTRS2004

Science Goal Monitor: Science Goal Driven Automation for NASA Missions

Infusion of automation technologies into NASA s future missions will be essential because of the need to: (1) effectively handle an exponentially increasing volume of scientific data, (2) successfully meet dynamic, opportunistic scientific goals and objectives, and (3) substantially reduce mission operations staff and costs. While much effort has gone into automating routine spacecraft operations to reduce human workload and hence costs, applying intelligent automation to the science side, i.e., science data acquisition, data analysis and reactions to that data analysis in a timely and still scientifically valid manner, has been relatively under-emphasized. In order to introduce science driven automation in missions, we must be able to: capture and interpret the science goals of observing programs, represent those goals in machine interpretable language; and allow spacecrafts onboard systems to autonomously react to the scientist's goals. In short, we must teach our platforms to dynamically understand, recognize, and react to the scientists goals. The Science Goal Monitor (SGM) project at NASA Goddard Space Flight Center is a prototype software tool being developed to determine the best strategies for implementing science goal driven automation in missions. The tools being developed in SGM improve the ability to monitor and react to the changing status of scientific events. The SGM system enables scientists to specify what to look for and how to react in descriptive rather than technical terms. The system monitors streams of science data to identify occurrences of key events previously specified by the scientist. When an event occurs, the system autonomously coordinates the execution of the scientist s desired reactions. Through SGM, we will improve om understanding about the capabilities needed onboard for success, develop metrics to understand the potential increase in science returns, and develop an operational prototype so that the perceived risks associated with increased use of automation can be reduced.

Koratkar, Anuradha↗

NASA NTRS2001

Testing the Preliminary X-33 Navigation System

The X-33 Reusable Launch Vehicle (RLV) must meet the demanding requirements of landing autonomously on a narrow landing strip following a flight that reaches an altitude of up to 200,000 feet and a speed in excess of Mach 9 with significant in-flight energy bleed-off maneuvers. To execute this flight regimen a highly reliable avionics system has been designed that includes three LN-100G Inertial Navigation System/Global Positioning System (INS/GPS) units as the primary navigation system for the X-33. NASA's Marshall Space Flight Center (MSFC) tested an INS/GPS system in real-time simulations to determine the ability of this navigation suite to meet the in flight and autonomous landing requirements of the X-33 RLV. A total of sixty-one open loop tests were performed to characterize the navigation accuracy of the LN-100G. Twenty-seven closed-loop tests were also performed to evaluate the performance of the X-33 Guidance, Navigation and Control (GN&C) algorithms with the real navigation hardware. These closed-loop tests were also designed to expose any integration or operational issues with the real-time X-33 vehicle simulation. Dynamic road tests of the INS/GPS were conducted by Litton to assess the performance of differential and nondifferential INS/GPS hybrid navigation solutions. The results of the simulations and road testing demonstrate that this novel solution is capable of meeting the demanding requirements of take-off, in-flight navigation, and autonomous landing of the X-33 RLV. This paper describes the test environment developed to stimulate the LN-100G and discusses the results of this test effort. This paper also presents recommendations for a navigation system suitable to an operational RLV system.

Lomas, James J.↗

NASA NTRS1998

A Self-Tuning Kalman Filter for Autonomous Spacecraft Navigation

Most navigation systems currently operated by NASA are ground-based, and require extensive support to produce accurate results. Recently developed systems that use Kalman Filter and Global Positioning System (GPS) data for orbit determination greatly reduce dependency on ground support, and have potential to provide significant economies for NASA spacecraft navigation. Current techniques of Kalman filtering, however, still rely on manual tuning from analysts, and cannot help in optimizing autonomy without compromising accuracy and performance. This paper presents an approach to produce a high accuracy autonomous navigation system fully integrated with the flight system. The resulting system performs real-time state estimation by using an Extended Kalman Filter (EKF) implemented with high-fidelity state dynamics model, as does the GPS Enhanced Orbit Determination Experiment (GEODE) system developed by the NASA Goddard Space Flight Center. Augmented to the EKF is a sophisticated neural-fuzzy system, which combines the explicit knowledge representation of fuzzy logic with the learning power of neural networks. The fuzzy-neural system performs most of the self-tuning capability and helps the navigation system recover from estimation errors. The core requirement is a method of state estimation that handles uncertainties robustly, capable of identifying estimation problems, flexible enough to make decisions and adjustments to recover from these problems, and compact enough to run on flight hardware. The resulting system can be extended to support geosynchronous spacecraft and high-eccentricity orbits. Mathematical methodology, systems and operations concepts, and implementation of a system prototype are presented in this paper. Results from the use of the prototype to evaluate optimal control algorithms implemented are discussed. Test data and major control issues (e.g., how to define specific roles for fuzzy logic to support the self-learning capability) are also discussed. In addition, architecture of a complete end-to-end candidate flight system that provides navigation with highly autonomous control using data from GPS is presented.

Truong, Son H.↗

NASA NTRS2013

NASA Tech Briefs, July 2013

Dielectrophoresis-Based Particle Sensor Using Nanoelectrode Arrays; Multi-Dimensional Damage Detection for Surfaces and Structures; ULTRA: Underwater Localization for Transit and Reconnaissance Autonomy; Autonomous Cryogenic Leak Detector for Improving Launch Site Operations; Submillimeter Planetary Atmospheric Chemistry Exploration Sounder; Method for Reduction of Silver Biocide Plating on Metal Surfaces; Silicon Micromachined Microlens Array for THz Antennas; Forward-Looking IED Detector Ground Penetrating Radar; Fully Printed, Flexible, Phased Array Antenna for Lunar Surface Communication, Battery Charge Equalizer with Transformer Array; An Efficient, Highly Flexible Multi-Channel Digital Downconverter Architecture; Dimmable Electronic Ballast for a Gas Discharge Lamp; Conductive Carbon Nanotube Inks for Use with Desktop Inkjet Printing Technology; Enhanced Schapery Theory Software Development for Modeling Failure of Fiber-Reinforced Laminates; High-Performance, Low-Temperature-Operating, Long-Lifetime Aerospace Lubricants; Carbon Nanotube Microarrays Grown on Nanoflake Substrates; Differential Muon Tomography to Continuously Monitor Changes in the Composition of Subsurface Fluids; Microgravity Drill and Anchor System; 20 Granular Media-Based Tunable Passive Vibration Suppressor; 21 Miga Aero Actuator and 2D Machined Mechanical Binary Latch; Micro-XRF for In Situ Geological Exploration of Other Planets; Hydrogen-Enhanced Lunar Oxygen Extraction and Storage Using Only Solar Power; Uplift of Ionospheric Oxygen Ions During Extreme Magnetic Storms; Miniaturized, High-Speed, Modulated X-Ray Source; Hollow-Fiber Spacesuit Water Membrane Evaporator 25 High-Power Single-Mode 2.65-micrometers InGaAsSb/AlInGaAsSb Diode Lasers; Optical Device for Converting a Laser Beam Into Two Co-aligned but Oppositely Directed Beams; A Hybrid Fiber/Solid-State Regenerative Amplifier with Tunable Pulse Widths for Satellite Laser Ranging; X-Ray Diffractive Optics; SynGenics Optimization System (SynOptSys); 29 CFD Script for Rapid TPS Damage Assessment; radEq Add-On Module for CFD Solver Loci-CHEM; Science Opportunity Analyzer (SOA) Version 8; 30 Autonomous Byte Stream Randomizer; Distributed Engine Control Empirical/Analytical Verification Tools; Dynamic Server-Based KML Code Generator Method for Level-of-Detail Traversal of Geospatial Data; Automated Planning of Science Products Based on Nadir Overflights and Alerts for Onboard and Ground Processing; Linked Autonomous Interplanetary Satellite Orbit Navigation; Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing; Scheduling Operations for Massive Heterogeneous Clusters; Deepak Condenser Model (DeCoM); Flight Software Math Library; Recirculating 1-K-Pot for Pulse-Tube Cryostats; 35 Method for Processing Lunar Regolith Using Microwaves; Wells for In Situ Extraction of Volatiles from Regolith (WIEVR); and Estimating the Backup Reaction Wheel Orientation Using Reaction Wheel Spin Rates Flight Telemetry from a Spacecraft.

Source record↗

NASA NTRS2020

In-Time UAV Flight-Trajectory Estimation and Tracking Using Bayesian Filters

Rapid increase of UAV operation in the next decade in areas of on-demand delivery, medical transportation services, law enforcement, traffic surveillance and several others pose potential risks to the low altitude airspace above densely populated areas. Safety assessment of airspace demands the need for a novel UAV traffic management (UTM) framework for regulation and tracking of the vehicles. Particularly for low-altitude UAV operations, quality of GPS measurements feeding into the UAV is often compromised by loss of communication link caused by presence of trees or tall buildings in proximity to the UAV flight path. Inaccurate GPS locations may yield to unreliable monitoring and inaccurate prognosis of remaining battery life and other safety metrics which rely on future expected trajectory of the UAV. This work therefore proposes a generalized monitoring and prediction methodology for autonomous UAVs using in-time GPS measurements. Firstly, a typical 4D smooth trajectory generation technique from a series of waypoint locations with associated expected times-of-arrival based on B-spline curves is presented. Initial uncertainty in the vehicle's expected cruise velocity is quantified to compute confidence intervals along the entire flight trajectory using error interval propagation approach. Further, the generated planned trajectory is considered as the prior knowledge which is updated during its flight with incoming GPS measurements in order to estimate its current location and corresponding kinematic profiles. Estimation of position is denoted in dicrete state-space representation such that position at a future time step is derived from position and velocity at current time step and expected velocity at the future time step. A linear Bayesian filtering algorithm is employed to efficiently refine position estimation from noisy GPS measurements and update the confidence intervals. Further, a dynamic re-planning strategy is implemented to incorporate unexpected detour or delay scenarios. Finally, critical challenges related to uncertainty quantification in trajectory prognosis for autonomous vehicles are identified, and potential solutions are discussed at the end of the paper. The entire monitoring framework is demonstrated on real UAV flight experiments conducted at the NASA Langley Research Center.

Banerjee, Portia↗

NASA NTRSDate not supplied

Status of Venus Global Reference Atmospheric Model (Venus-GRAM) Upgrades

Venus-GRAM Overview - Engineering-oriented atmospheric model that estimates mean values and statistical variations of Venus atmospheric properties - Outputs include atmospheric density, temperature, pressure, chemical composition, and wind components along a user-defined path - Widely used by the engineering community because of its ability to create realistic atmospheric dispersions - Can be integrated into high fidelity flight dynamic simulations of launch, entry, descent and landing (EDL), aerobraking and aerocapture - Has been used in multiple studies and proposals including NASA Engineering and Safety Center (NESC) Autonomous Aerobraking Study and various Discovery proposals - Optional trajectory input file consisting of time, height, latitude, and longitude can be used to provide the Venus-GRAM trajectory path - Optional auxiliary profile consisting of height, latitude, longitude, temperature, pressure, density, eastward wind, and northward wind may be used to replace model data in Venus-GRAM - Not a forecast model - GRAMs are also available for Earth, Mars, Titan, Neptune, Uranus, and Jupiter - Available through the NASA Software Catalog https://software.nasa.gov/software/MFS-33888-1

atmospheric models↗

NASA NTRS1994

Grasping objects autonomously in simulated KC-135 zero-g

The KC-135 aircraft was chosen for simulated zero gravity testing of the Extravehicular Activity Helper/retriever (EVAHR). A software simulation of the EVAHR hardware, KC-135 flight dynamics, collision detection and grasp inpact dynamics has been developed to integrate and test the EVAHR software prior to flight testing on the KC-135. The EVAHR software will perform target pose estimation, tracking, and motion estimation for rigid, freely rotating, polyhedral objects. Manipulator grasp planning and trajectory control software has also been developed to grasp targets while avoiding collisions.

Norsworthy, Robert S.↗

NASA NTRS2005

Experimenting with an Evolving Ground/Space-based Software Architecture to Enable Sensor Webs

A series of ongoing experiments are being conducted at the NASA Goddard Space Flight Center to explore integrated ground and space-based software architectures enabling sensor webs. A sensor web, as defined by Steve Talabac at NASA Goddard Space Flight Center(GSFC), is a coherent set of distributed nodes interconnected by a communications fabric, that collectively behave as a single, dynamically adaptive, observing system. The nodes can be comprised of satellites, ground instruments, computing nodes etc. Sensor web capability requires autonomous management of constellation resources. This becomes progressively more important as more and more satellites share resource, such as communication channels and ground station,s while automatically coordinating their activities. There have been five ongoing activities which include an effort to standardize a set of middleware. This paper will describe one set of activities using the Earth Observing 1 satellite, which used a variety of ground and flight software along with other satellites and ground sensors to prototype a sensor web. This activity allowed us to explore where the difficulties that occur in the assembly of sensor webs given today s technology. We will present an overview of the software system architecture, some key experiments and lessons learned to facilitate better sensor webs in the future.

mandl, Daniel↗

NASA NTRS2013

Autonomous Formations of Multi-Agent Systems

Autonomous formation control of multi-agent dynamic systems has a number of applications that include ground-based and aerial robots and satellite formations. For air vehicles, formation flight ("flocking") has the potential to significantly increase airspace utilization as well as fuel efficiency. This presentation addresses two main problems in multi-agent formations: optimal role assignment to minimize the total cost (e.g., combined distance traveled by all agents); and maintaining formation geometry during flock motion. The Kuhn-Munkres ("Hungarian") algorithm is used for optimal assignment, and consensus-based leader-follower type control architecture is used to maintain formation shape despite the leader s independent movements. The methods are demonstrated by animated simulations.

Dhali, Sanjana↗

NASA NTRS2018

Developed AprilNav, an Indoor Navigation and Localization System for Autonomous Testing of Electric Sail Dynamics

An electrostatic sail (E-sail) is a new type of propulsion which harnesses the Sun's solar wind to propel a spacecraft. Voyager I took about 40 years to reach interstellar space using solid rocket propellant, whereas electrostatic sails can travel the same distance in 6-10 years by using small but constant acceleration. As part of Marshall Space Flight Center's (MSFC) Space Systems Dept. and Advanced Concepts Office, we are continuing research for the HERTS (Heliopause Electrostatic Rapid Transit System) E-sail project. Previous researchers developed a Nano Air-bearing Simulator (NAS) prototype for initial testing of E-sails; this prototype was properly documented in CAD (Computer-Aided Drafting) in order to build a second improved NAS. MSFC's Robotic Lab (Flat Floor) allows for 2-dimensional simulations of spacecraft dynamics by attaching air bearings to a system. An indoor navigation system AprilNav, was developed and has been implemented on the ceiling of the flat floor for localization and autonomous testing of the two bearing-equipped NAS. With two NAS, tether dynamics between the two simulators as well as steering control algorithms are being tested on the flat floor using AprilNav.

Schuler, Tristan↗

NASA NTRS1990

Design and implementation of a ground control console prototype for OMV

One of the primary uses of the Flat Floor facility of The Marshall Flight Center is to perform autonomous and teleoperated docking of vehicles similar to NASA's Orbital Maneuvering Vehicle (OMV). Using both the air-bearing vehicle and the 8 DOF Dynamic Overhead Target Simulator (DOTS) in tandem, even the most difficult OMV docking problems can be simulated. The OMV was planned to be flown from the ground by a pilot via teleoperation. Specifications were developed for a prototype Ground Control Console (GCC) from where the vehicle will be flown. In order for testing of the OMV to occur at Flat Floor facility, this GCC must be replicated. The project was divided into three primary tasks: (1) the design and development of the video display; (2) the design and development of the switch panel using the micro switch programmable display pushbutton switches; and (3) the design and development of the hand controllers. A final task is to perform system integration on the results of these three primary tasks.

Walcott, Bruce L.↗

NASA NTRSDate not supplied

An Experimental System for Strategic Flight Path Management in Advanced Air Mobility

In the concept envisioned for Urban Air Mobility (UAM) operations, fleets of electric vertical takeoff and landing (eVTOL) vehicles would operate between vertiports distributed within a densely populated area. These operations would be largely independent from the existing air traffic control system and would place the responsibility for flight planning and aircraft separation on fleet operators. The fourth major level on the UAM Maturity Level scale, UML-4, relies on “collaborative and responsible” automation to enable operations in non-visual conditions with medium traffic density (hundreds of aircraft in one metropolitan region) and medium complexity. This level of service places many requirements on automation systems to assist the operators of these aircraft. NASA has developed the Autonomous Operations Planner (AOP), a reference prototype Flight Path Management automation system, and has modified AOP to support research of anticipated UML-4 operations. AOP creates a four-dimensional flight plan conforming to the constraints of these operations, evaluates and modifies the flight plan during flight as conditions and constraints evolve, and coordinates the flight plan with other airspace users and with service providers. This version of AOP has been integrated into the Sikorsky Autonomy Research Aircraft and used in a flight test activity. In this paper we discuss anticipated characteristics of UAM operations, modifications that were made to AOP to adapt to that environment or to support the flight test, and observations of software and aircraft performance during the flight test. The aircraft achieved four-dimensional conformance with the flight plan and AOP provided adequate planning in almost all cases. We discuss improvements that could be made to AOP to address deficiencies that were observed.

Autonomous Operations Planner↗

NASA NTRSDate not supplied

An Experimental System for Strategic Flight Path Management in Advanced Air Mobility

Autonomous Operations Planner↗