SEARCH · Search NASA

Results for “command generation process”

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 199 records · Page 11

All sources NASA NTRS DOE OSTI

NASA NTRS2002

The Maneuver Planning Process for the Microwave Anisotropy Probe (MAP) Mission

The Microwave Anisotropy Probe (MAP) was successfully launched from Kennedy Space Center's Eastern Range on June 30, 2001. MAP will measure the cosmic microwave background as a follow up to NASA's Cosmic Background Explorer (COBE) mission from the early 1990's. MAP will take advantage of its mission orbit about the Sun-Earth/Moon L2 Lagrangian point to produce results with higher resolution, sensitivity, and accuracy than COBE. A strategy comprising highly eccentric phasing loops with a lunar gravity assist was utilized to provide a zero-cost insertion into a lissajous orbit about L2. Maneuvers were executed at the phasing loop perigees to correct for launch vehicle errors and to target the lunar gravity assist so that a suitable orbit at L2 was achieved. This paper will discuss the maneuver planning process for designing, verifying, and executing MAP's maneuvers. A discussion of the tools and how they interacted will also be included. The maneuver planning process was iterative and crossed several disciplines, including trajectory design, attitude control, propulsion, power, thermal, communications, and ground planning. Several commercial, off-the-shelf (COTS) packages were used to design the maneuvers. STK/Astrogator was used as the trajectory design tool. All maneuvers were designed in Astrogator to ensure that the Moon was met at the correct time and orientation to provide the energy needed to achieve an orbit about L2. The Mathworks Matlab product was used to develop a tool for generating command quaternions. The command quaternion table (CQT) was used to drive the attitude during the perigee maneuvers. The MatrixX toolset, originally written by Integrated Systems, Inc., now distributed by Mathworks, was used to create HiFi, a high fidelity simulator of the MAP attitude control system. HiFi was used to test the CQT and to make sure that all attitude requirements were met during the maneuver. In addition, all ACS data plotting and output were generated in MatrixX. A final test used FlatSat, a real-time hardware-in-the-loop simulator, which used identical MAP flight code to simulate operations on the spacecraft. Simulations in FlatSat allowed the MAP team to verify maneuver commands, timing, and spacecraft configuration before the commands were sent up to the spacecraft for execution. The MAP maneuver team successfully pieced together all of these COTS tools for designing MAP's maneuvers and MAP is now collecting data at L2.

Mesarch, Michael A.↗

NASA NTRS2010

MOS 2.0: The Next Generation in Mission Operations Systems

A Mission Operations System (MOS) or Ground System constitutes that portion of an overall space mission Enterprise that resides here on Earth. Over the past two decades, technological innovations in computing and software technologies have allowed an MOS to support ever more complex missions while consuming a decreasing fraction of Project development budgets. Despite (or perhaps, because of) such successes, it is routine to hear concerns about the cost of MOS development. At the same time, demand continues for Ground Systems which will plan more spacecraft activities with fewer commanding errors, provide scientists and engineers with more autonomous functionality, process and manage larger and more complex data more quickly, all while requiring fewer people to develop, deploy, operate and maintain them. One successful approach to such concerns over this period is a multimission approach, based on the reuse of portions (most often software) developed and used in previous missions. The Advanced Multi-Mission Operations System (AMMOS), developed for deep-space science missions, is one successful example of such an approach. Like many computing-intensive systems, it has grown up in a near-organic fashion from a relatively simple set of tools into a complexly interrelated set of capabilities. Such systems, like a city lacking any concept of urban planning, can and will grow in ways that are neither efficient nor particularly easy to sustain. To meet the growing demands and unyielding constraints placed on ground systems, a new approach is necessary. Under the aegis of a multi-year effort to revitalize the AMMOS's multimission operations capabilities, we are utilizing modern practices in systems architecting and model-based engineering to create the next step in Ground Systems: MOS 2.0. In this paper we outline our work (ongoing and planned) to architect and design a multimission MOS 2.0, describe our goals and measureable objectives, and discuss some of the benefits that this top-down, architectural approach holds for creating a more flexible and capable MOS for Missions while holding the line on cost.

ground systems↗

NASA NTRS2008

ATHLETE's Feet: Mu1ti-Resolution Planning for a Hexapod Robot

ATHLETE is a large six-legged tele-operated robot. Each foot is a wheel; travel can be achieved by walking, rolling, or some combination of the two. Operators control ATHLETE by selecting parameterized commands from a command dictionary. While rolling can be done efficiently with a single command, any motion involving steps is cumbersome - walking a few meters through difficult terrain can take hours. Our goal is to improve operator efficiency by automatically generating sequences of motion commands. There is increasing uncertainty regarding ATHLETE s actual configuration over time and decreasing quality of terrain data farther away from the current position. This, combined with the complexity that results from 36 degrees of kinematic freedom, led to an architecture that interleaves planning and execution at multiple levels, ranging from traditional configuration space motion planning algorithms for immediate moves to higher level task and path planning algorithms for overall travel. The modularity of the architecture also simplifies the development process and allows the operator to interact with and control the system at varying levels of autonomy depending on terrain and need.

Smith, Tristan B.↗

NASA NTRS2007

Robust, Flexible Motion Control for the Mars Explorer Rovers

The Mobility Flight Software, running on computers aboard the Mars Explorer Rover (MER) robotic vehicles Spirit and Opportunity, affords the robustness and flexibility of control to enable safe and effective operation of these vehicles in traversing natural terrain. It can make the vehicles perform specific maneuvers commanded from Earth, and/or can autonomously administer multiple aspects of mobility, including choice of motion, measurement of actual motion, and even selection of targets to be approached. Motion of a vehicle can be commanded by use of multiple layers of control, ranging from motor control at a low level, direct drive operations (e.g., motion along a circular arc, motion along a straight line, or turn in place) at an intermediate level to goal-position driving (that is, driving to a specified location) at a high level. The software can also perform high-level assessment of terrain and selection of safe paths across the terrain: this involves processing of the digital equivalent of a local traversability map generated from images acquired by stereoscopic pairs of cameras aboard the vehicles. Other functions of the software include interacting with the rest of the MER flight software and performing safety checks.

Maimone, Mark↗

NASA NTRS1989

Applications of artificial intelligence to space station and automated software techniques: High level robot command language

The objective is to develop a system that will allow a person not necessarily skilled in the art of programming robots to quickly and naturally create the necessary data and commands to enable a robot to perform a desired task. The system will use a menu driven graphical user interface. This interface will allow the user to input data to select objects to be moved. There will be an imbedded expert system to process the knowledge about objects and the robot to determine how they are to be moved. There will be automatic path planning to avoid obstacles in the work space and to create a near optimum path. The system will contain the software to generate the required robot instructions.

Mckee, James W.↗

NASA NTRSDate not supplied

Natural Language Processing Methods for Air Traffic Management Text and Speech Data

This presentation discusses two efforts of the NARI AI/ML Intern team during the Fall 2021 OSTEM Internship term. For Letters of Agreement (LoA), we have studied how LoAs are structured and explored the question ‘What is an LoA constraint?’ To do this, our approach is data-driven, iterative, and assisted by machine learning when available. In this presentation, we will walk through our tasks of manually scanning through documents, performing a preliminary entity labelling task, and our unsupervised analysis on LoA procedures sections. After this research phase, we define the smallest constraint unit in an LoA, and start to perform entity extraction. Looking towards constraint extraction, we are also exploring the use of a one-class support vector machine (OneClassSVM) model to identify patterns within the data. The second effort of our team this term is focused on Air Traffic Control System Command Center (ATCSCC) advisory meetings, and the subsequent advisory documents that get published from their content. These advisory documents are important to give readily accessible summaries of daily operations, so that data centers, airline officials, and other stakeholders can easily understand the context of these meetings in real time. In applying machine learning to this scenario, two natural language processing tasks are used. First is developing machine learning models to convert the meeting speech data into text. With this text, use of extractive and abstractive text summarization models are used to automatically generate preliminary versions of the advisory documents.

Natural Language Processing↗

NASA NTRS2017

Launch Control System Software Development System Automation Testing

The Spaceport Command and Control System (SCCS) is the National Aeronautics and Space Administration's (NASA) launch control system for the Orion capsule and Space Launch System, the next generation manned rocket currently in development. This system requires high quality testing that will measure and test the capabilities of the system. For the past two years, the Exploration and Operations Division at Kennedy Space Center (KSC) has assigned a group including interns and full-time engineers to develop automated tests to save the project time and money. The team worked on automating the testing process for the SCCS GUI that would use streamed simulated data from the testing servers to produce data, plots, statuses, etc. to the GUI. The software used to develop automated tests included an automated testing framework and an automation library. The automated testing framework has a tabular-style syntax, which means the functionality of a line of code must have the appropriate number of tabs for the line to function as intended. The header section contains either paths to custom resources or the names of libraries being used. The automation library contains functionality to automate anything that appears on a desired screen with the use of image recognition software to detect and control GUI components. The data section contains any data values strictly created for the current testing file. The body section holds the tests that are being run. The function section can include any number of functions that may be used by the current testing file or any other file that resources it. The resources and body section are required for all test files; the data and function sections can be left empty if the data values and functions being used are from a resourced library or another file. To help equip the automation team with better tools, the Project Lead of the Automated Testing Team, Jason Kapusta, assigned the task to install and train an optical character recognition (OCR) tool to Brandon Echols, a fellow intern, and I. The purpose of the OCR tool is to analyze an image and find the coordinates of any group of text. Some issues that arose while installing the OCR tool included the absence of certain libraries needed to train the tool and an outdated software version. We eventually resolved the issues and successfully installed the OCR tool. Training the tool required many images and different fonts and sizes, but in the end the tool learned to accurately decipher the text in the images and their coordinates. The OCR tool produced a file that contained significant metadata for each section of text, but only the text and coordinates of the text was required for our purpose. The team made a script to parse the information we wanted from the OCR file to a different file that would be used by automation functions within the automated framework. Since a majority of development and testing for the automated test cases for the GUI in question has been done using live simulated data on the workstations at the Launch Control Center (LCC), a large amount of progress has been made. As of this writing, about 60% of all of automated testing has been implemented. Additionally, the OCR tool will help make our automated tests more robust due to the tool's text recognition being highly scalable to different text fonts and text sizes. Soon we will have the whole test system automated, allowing for more full-time engineers working on development projects.

Automation↗

NASA NTRS2006

Modification of a Limbed Robot to Favor Climbing

The figure shows the LEMUR IIb, which is a modified version of the LEMUR II the second generation of the Limbed Excursion Mechanical Utility Robot (LEMUR). Except as described below, the LEMUR IIb hardware is mostly the same as that of the LEMUR II. The IIb and II versions differ in their kinematic configurations and characteristics associated with their kinematic configurations. The differences are such that relative to the LEMUR II, the LEMUR IIb is simpler and is better suited to climbing on inclined surfaces. The first-generation LEMUR, now denoted the LEMUR I, was described in Six-Legged Experimental Robot (NPO-20897), NASA Tech Briefs, Vol. 25, No. 12 (December 2001), page 58. The LEMUR II was described in Second-Generation Six-Limbed Experimental Robot (NPO-35140) NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 55. To recapitulate: the LEMUR I and LEMUR II were six-legged or sixlimbed robots for demonstrating robotic capabilities for assembly, maintenance, and inspection. They were designed to be capable of walking autonomously along a truss structure toward a mechanical assembly at a prescribed location. They were equipped with stereoscopic video cameras and image-data-processing circuitry for navigation and mechanical operations. They were also equipped with wireless modems, through which they could be commanded remotely. Upon arrival at a mechanical assembly, the LEMUR I would perform simple mechanical operations by use of one or both of its front legs (or in the case of the LEMUR II, any of its limbs could be used to perform mechanical operations). Either LEMUR could also transmit images to a host computer. The differences between the LEMUR IIb and the LEMUR II are the following: Whereas the LEMUR II had six limbs, the LEMUR IIb has four limbs. This change has reduced both the complexity and mass of the legs and of the overall robot. Whereas each limb of the LEMUR II had four degrees of freedom (DOFs), each limb of the LEMUR IIb has three DOFs. This change has also reduced both complexity and mass. Notwithstanding the decrease in the number of DOFs, the three remaining DOFs are configured to provide greater dexterity for motion along a surface. To extend reach, the limbs of the LEMUR IIb are 25 percent longer than those of the LEMUR II. Additional benefits stemming from the modifications are that the robot body supported by the limbs is now less massive and its center of gravity is now closer to the surface along which the robot is to move. These benefits have been obtained without sacrificing load-carrying capacity. Hence, overall, the LEMUR IIb is a more adept climber.

Okon, Avi↗

NASA NTRS2007

ISPATOM: A Generic Real-Time Data Processing Tool Without Programming

Information Sharing Protocol Advanced Tool of Math (ISPATOM) is an application program allowing for the streamlined generation of comps, which subscribe to streams of incoming telemetry data, perform any necessary computations on the data, then send the data to other programs for display and/or further processing in NASA mission control centers. Heretofore, the development of comps was difficult, expensive, and time-consuming: Each comp was custom written manually, in a low-level computing language, by a programmer attempting to follow requirements of flight controllers. ISPATOM enables a flight controller who is not a programmer to write a comp by simply typing in one or more equation( s) at a command line or retrieving the equation(s) from a text file. ISPATOM then subscribes to the necessary input data, performs all of necessary computations, and sends out the results. It sends out new results whenever the input data change. The use of equations in ISPATOM is no more difficult than is entering equations in a spreadsheet. The time involved in developing a comp is thus limited to the time taken to decide on the necessary equations. Thus, ISPATOM is a real-time dynamic calculator.

Dershowitz, Adam↗

NASA NTRS2011

Nanosail-D: The Small Satellite That Could!

Three years from its initial design review, NanoSail-D successfully deployed its sail on January 20th, 2011. It became the first solar sail vehicle to orbit the earth and the second sail ever unfurled in space. The NanoSail-D mission had two main objectives: eject a nanosatellite from a microsatellite; deploy its sail from a highly compacted volume and low mass system to validate large structure deployment and potential de-orbit technologies. These objectives were successfully achieved and the de-orbit analysis is in process. This paper presents an overview of the NanoSail-D project and insights into how potential setbacks were overcome. Many lessons have been learned during these past three years and are discussed in light of the phenomenal success and interest that this small satellite has generated. NanoSail-D was jointly designed and built by NASA's Marshall Space Flight Center and NASA's Ames Research Center. ManTech/NeXolve Corporation also provided key sail design support. The NanoSail-D experiment is managed by Marshall and jointly sponsored by the Army Space and Missile Defense Command, the Von Braun Center for Science and Innovation and Dynetics Inc. Ground operations support was provided by Santa Clara University, with radio beacon packets received from amateur operators around the world.

Alhorn, Dean C.↗

NASA NTRS1991

Model reference adaptive control of flexible robots in the presence of sudden load changes

Direct command generator tracker based model reference adaptive control (MRAC) algorithms are applied to the dynamics for a flexible-joint arm in the presence of sudden load changes. Because of the need to satisfy a positive real condition, such MRAC procedures are designed so that a feedforward augmented output follows the reference model output, thus, resulting in an ultimately bounded rather than zero output error. Thus, modifications are suggested and tested that: (1) incorporate feedforward into the reference model's output as well as the plant's output, and (2) incorporate a derivative term into only the process feedforward loop. The results of these simulations give a response with zero steady state model following error, and thus encourage further use of MRAC for more complex flexibile robotic systems.

Steinvorth, Rodrigo↗

NASA NTRS2017

Spaceport Command and Control System Automated Testing

The Spaceport Command and Control System (SCCS) is the National Aeronautics and Space Administrations (NASA) launch control system for the Orion capsule and Space Launch System, the next generation manned rocket currently in development. This large system requires high quality testing that will properly measure the capabilities of the system. Automating the test procedures would save the project time and money. Therefore, the Electrical Engineering Division at Kennedy Space Center (KSC) has recruited interns for the past two years to work alongside full-time engineers to develop these automated tests, as well as innovate upon the current automation process.

LCS↗

NASA NTRS2017

Spaceport Command and Control System Automation Testing

Testing↗

NASA NTRSDate not supplied

NASA's Moon to Mars Autonomous Habitat Status

NASA is developing a strategy for sending humans to the Mars vicinity, known broadly as the Moon to Mars (M2M) Campaign. A critical part of this campaign is the development of in-space and surface habitation systems capable of substantially extending human presence beyond Low Earth Orbit (LEO). Mars missions feature an in-space transit habitat capable of supporting crews of four on ~850-1200-day missions, including transit to and from Mars and time in Mars orbit. Surface and transit habitats are complex elements which must keep crewmembers healthy and productive in deep-space environments with limited resources, long rescue times in contingency situations, and communication delays; all within constrained mass, volume, and power budgets. These habitats provide crew both living and workspace as well as most of the resources needed to support crew life. For deep space habitats, automation needs to be employed due to latency and for significant amounts of time when the habitats are uncrewed. Automation of systems is possible in space applications, but there are limitations. Outside of the Earth’s (or any) magnetosphere, radiation environments are harsh to both the physical hardware and the software components. Radiation (charged particles and ionizing electromagnetic waves) degrades and damages the hardware and causes single event upsets (SEUs) in software. If the hardware is damaged, data can be lost, or control actions not made. For software, SEUs cause algorithms to result in different solutions, or incorrect commands to be sent out. This means that algorithms and hardware used for deep space systems are different than what is used on Earth. Radiation-tolerant hardware is generations behind the current state-of-the-art hardware. Recent NASA missions, such as James Webb Space Telescope, continue to rely on older technologies such as the RAD750 processor, and the most advanced processors are still single core and less than 1.5 GHz. There have been attempts to use higher performance processors, but these often take multiple mitigation steps to handle the radiation environments, which limits the processing power and/or throughput. Current techniques for radiation mitigation have been redundancies, voting, physical separation of hardware, encasing materials, under-clocking hardware, and more. Some radiation mitigation techniques do provide benefits such as having a redundant system to improve the probability that a system will be available when needed. Autonomous software systems will have fewer interactions with humans on deep space missions and therefore need to be able to handle more off-nominal conditions. Microgravity also complicates the autonomous aspects of the mission because autonomous systems are usually built from known deterministic states, but microgravity causes physical objects to shift and move changing the location an autonomous system placed the object. Not only does the software need to be reliable and deterministic, losing resources due to a software error is not only costly but detrimental to reputation. The combination of having lower performance hardware and having to be able to verify and deterministically run software and an ever-changing environment makes deep space autonomous systems more complicated. Multiple gaps have been identified including verification of autonomous software algorithms (including artificial intelligence and machine learning), higher performance processors (graphics and general purpose), high speed networks (onboard and transmissions), memory, power distribution, data security, and variations from these. These gaps need to be closed for more advanced systems to be deployed and reduce the size, weight, and power impacts on the habitats.

Scott B. Tashakkor↗

NASA NTRS2019

Active Flutter Suppression Using Reduced-Order Modeling for Transonic Aeroservoelastic Control Law Development

In this paper, several aerodynamic reduced-order models (ROMs) are generated and coupled with structural models to form aeroelastic ROMs. The aerodynamic ROMs generated here include the effects of control surface motion and are appropriate for use in aeroservoelastic applications. Simple observer-based full-state feedback controllers were designed from these aeroelastic ROMs. Additionally, observer gain matrices were designed from and coupled to the aeroelastic ROMs. Each (linear) observer was then used to estimate the dynamics of a (nonlinear) stand-alone computational fluid-structure dynamics simulation. Then, using the estimated states and the full-state feedback controller, control surface commands were fed back into the computational fluid-structure dynamics simulation to successfully achieve active flutter suppression. The process, as well as some results, are presented in this paper.

Waite, Josiah M.↗

NASA NTRS2007

XML Flight/Ground Data Dictionary Management

A computer program generates Extensible Markup Language (XML) files that effect coupling between the command- and telemetry-handling software running aboard a spacecraft and the corresponding software running in ground support systems. The XML files are produced by use of information from the flight software and from flight-system engineering. The XML files are converted to legacy ground-system data formats for command and telemetry, transformed into Web-based and printed documentation, and used in developing new ground-system data-handling software. Previously, the information about telemetry and command was scattered in various paper documents that were not synchronized. The process of searching and reading the documents was time-consuming and introduced errors. In contrast, the XML files contain all of the information in one place. XML structures can evolve in such a manner as to enable the addition, to the XML files, of the metadata necessary to track the changes and the associated documentation. The use of this software has reduced the extent of manual operations in developing a ground data system, thereby saving considerable time and removing errors that previously arose in the translation and transcription of software information from the flight to the ground system.

Wright, Jesse↗

NASA NTRSDate not supplied

Emulation of Core Flight System Applications for Flight Software Development and Validation

The Mars Sample Return (MSR) campaign is an unprecedented attempt in the return of Martian samples back to Earth. The ascent from the surface will be performed by the Mars Ascent Vehicle (MAV), a critical element in the mission that National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC) is developing. To this end, innovations in flight software development, verification, and validation are occurring. The MAV flight computer will run Core Flight System (cFS), an open-source software environment developed by NASA Goddard Space Flight Center (GSFC). NASA Marshall’s MAV Mission and Fault Management (M&FM) Team has implemented an emulation of two applications of this architecture: Limit Checker and Stored Command. Using an emulation of the functionalities of these applications allows for rapid prototyping of table-based algorithms. Further, M&FM is leveraging an in-house, low-fidelity but high-throughput State Analysis Model (SAM), an integrated MATLAB Stateflow Plant and Software model. This model is run in parallel with the cFS emulation for full flyout testing of the M&FM algorithms, verification of intent of these algorithms, and for future auto-generation of application-ingestible M&FM tables. The tables can then be delivered to the MAV Flight Software (FSW) team in a seamless process, reducing the cost of traditional FSW development and the risk of starting M&FM FSW development at later points in the NASA program life cycle.

Cody Wheeler↗

NASA NTRSDate not supplied

Emulation of Core Flight System Applications for Flight Software Development and Validation

Cody Wheeler↗