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NASA NTRS2023

Compact Lightweight Aerial Sensor System (CLASSy)

In the wake of increasingly intense wildfires, innovative solutions are imperative to enhance wildfire mitigation strategies. Current technological integrations have hit a communicative limit. Between limited flight time, computational expenses as well as financial expenses, there is a hole in the market for an effective, low-tech, and disposable solution. The Compact Lightweight Aerial Sensor System (CLASSy) is designed to revolutionize active disaster operations through comprehensive decision support. CLASSy consists of a lightweight launch mechanism and a flight body equipped with a sensor package and parachute. The assembly integrates sensor networks with data analytics to provide real-time, high-resolution information to incident commanders, directly facilitating decision-making and resource allocation. Infrared imagery and temperature differentials are processed and analyzed throughout flight, offering valuable insights into fire behavior, hotspot detection, and fire spread trajectories. CLASSy is intended to meet a variety of natural disaster mitigation needs through its variable launch height and disposability. CLASSy’s goal is to assist wildfire fighting without taking up any human or material resources. As a result, CLASSy is as lightweight as possible, easily expendable, inexpensive to manufacture, and only requires one operator for effective use. CLASSy’s integrated sensor suite, real-time analytics, and closed loop active communications empower firefighting teams to proactively address wildfire challenges. As the frequency of wildfires continues to rise, technological innovations like CLASSy are crucial to effective wildfire management systems.

Kyleigh Anderson↗
NASA NTRS2002

Distributed Framework for Dynamic Telescope and Instrument Control

Traditionally, instrument command and control systems have been developed specifically for a single instrument. Such solutions are frequently expensive and are inflexible to support the next instrument development effort. NASA Goddard Space Flight Center is developing an extensible framework, known as Instrument Remote Control (IRC) that applies to any kind of instrument that can be controlled by a computer. IRC combines the platform independent processing capabilities of Java with the power of the Extensible Markup Language (XML). A key aspect of the architecture is software that is driven by an instrument description, written using the Instrument Markup Language (IML). IML is an XML dialect used to describe graphical user interfaces to control and monitor the instrument, command sets and command formats, data streams, communication mechanisms, and data processing algorithms. The IRC framework provides the ability to communicate to components anywhere on a network using the JXTA protocol for dynamic discovery of distributed components. JXTA (see httD://www.jxta.org,) is a generalized protocol that allows any devices connected by a network to communicate in a peer-to-peer manner. IRC uses JXTA to advertise a device's IML and discover devices of interest on the network. Devices can join or leave the network and thus join or leave the instrument control environment of IRC. Currently, several astronomical instruments are working with the IRC development team to develop custom components for IRC to control their instruments. These instruments include: High resolution Airborne Wideband Camera (HAWC), a first light instrument for the Stratospheric Observatory for Infrared Astronomy (SOFIA); Submillimeter And Far Infrared Experiment (SAFIRE), a Principal Investigator instrument for SOFIA; and Fabry-Perot Interferometer Bolometer Research Experiment (FIBRE), a prototype of the SAFIRE instrument, used at the Caltech Submillimeter Observatory (CSO). Most recently, we have been working with the Submillimetre High Angular Resolution Camera IInd Generation (SHARCII) at the CSO to investigate using IRC capabilities with the SHARC instrument.

Ames, Troy J.↗
NASA NTRS2010

Use of Dynamic Models and Operational Architecture to Solve Complex Navy Challenges

The United States Navy established 8 Maritime Operations Centers (MOC) to enhance the command and control of forces at the operational level of warfare. Each MOC is a headquarters manned by qualified joint operational-level staffs, and enabled by globally interoperable C41 systems. To assess and refine MOC staffing, equipment, and schedules, a dynamic software model was developed. The model leverages pre-existing operational process architecture, joint military task lists that define activities and their precedence relations, as well as Navy documents that specify manning and roles per activity. The software model serves as a "computational wind-tunnel" in which to test a MOC on a mission, and to refine its structure, staffing, processes, and schedules. More generally, the model supports resource allocation decisions concerning Doctrine, Organization, Training, Material, Leadership, Personnel and Facilities (DOTMLPF) at MOCs around the world. A rapid prototype effort efficiently produced this software in less than five months, using an integrated process team consisting of MOC military and civilian staff, modeling experts, and software developers. The work reported here was conducted for Commander, United States Fleet Forces Command in Norfolk, Virginia, code N5-0LW (Operational Level of War) that facilitates the identification, consolidation, and prioritization of MOC capabilities requirements, and implementation and delivery of MOC solutions.

Grande, Darby↗
NASA NTRS2009

Converting CSV Files to RKSML Files

A computer program converts, into a format suitable for processing on Earth, files of downlinked telemetric data pertaining to the operation of the Instrument Deployment Device (IDD), which is a robot arm on either of the Mars Explorer Rovers (MERs). The raw downlinked data files are in comma-separated- value (CSV) format. The present program converts the files into Rover Kinematics State Markup Language (RKSML), which is an Extensible Markup Language (XML) format that facilitates representation of operations of the IDD and enables analysis of the operations by means of the Rover Sequencing Validation Program (RSVP), which is used to build sequences of commanded operations for the MERs. After conversion by means of the present program, the downlinked data can be processed by RSVP, enabling the MER downlink operations team to play back the actual IDD activity represented by the telemetric data against the planned IDD activity. Thus, the present program enhances the diagnosis of anomalies that manifest themselves as differences between actual and planned IDD activities.

Trebi-Ollennu, Ashitey↗
NASA NTRS2006

Multimodal Platform Control for Robotic Planetary Exploration Missions

Planetary exploration missions pose unique problems for astronauts seeking to coordinate and control exploration vehicles. These include working in an environment filled with abrasive dust (e.g., regolith compositions), a desire to have effective hands-free communication, and a desire to have effective analog control of robotic platforms or end effectors. Requirements to operate in pressurized suits are particularly problematic due to the increased bulk and stiffness of gloves. As a result, researchers are considering alternative methods to perform fine movement control, for example capitalizing on higher-order voice actuation commands to perform control tasks. This paper presents current research at NASA s Neuro Engineering Laboratory that explores one method-direct bioelectric interpretation-for handling some of these problems. In this type of control system, electromyographic (EMG) signals are used both to facilitate understanding of acoustic speech in pressure-regulated suits 2nd to provide smooth analog control of a robotic platform, all without requiring fine-gained hand movement. This is accomplished through the use of non-invasive silver silver-chloride electrodes located on the forearm, throat, and lower chin, positioned so as to receive electrical activity originating from the muscles during contraction. For direct analog platform control, a small Personal Exploration Rover (PER) built by Carnegie Mellon University Robotics is controlled using forearm contraction duration and magnitudes, measured using several EMG channels. Signal processing is used to translate these signals into directional platform rotation rates and translational velocities. higher order commands were generated by differential contraction patterns called "clench codes."

Jorgensen, Charles↗
NASA NTRS2015

[Determine and Implement Updates to Be Made to MODEAR (Mission Operations Data Enterprise Architecture Repository)]

My main project was to determine and implement updates to be made to MODEAR (Mission Operations Data Enterprise Architecture Repository) process definitions to be used for CST-100 (Crew Space Transportation-100) related missions. Emphasis was placed on the scheduling aspect of the processes. In addition, I was to complete other tasks as given. Some of the additional tasks were: to create pass-through command look-up tables for the flight controllers, finish one of the MDT (Mission Operations Directorate Display Tool) displays, gather data on what is included in the CST-100 public data, develop a VBA (Visual Basic for Applications) script to create a csv (Comma-Separated Values) file with specific information from spreadsheets containing command data, create a command script for the November MCC-ASIL (Mission Control Center-Avionics System Integration Laboratory) testing, and take notes for one of the TCVB (Terminal Configured Vehicle B-737) meetings. In order to make progress in my main project I scheduled meetings with the appropriate subject matter experts, prepared material for the meetings, and assisted in the discussions in order to understand the process or processes at hand. After such discussions I made updates to various MODEAR processes and process graphics. These meetings have resulted in significant updates to the processes that were discussed. In addition, the discussions have helped the departments responsible for these processes better understand the work ahead and provided material to help document how their products are created. I completed my other tasks utilizing resources available to me and, when necessary, consulting with the subject matter experts. Outputs resulting from my other tasks were: two completed and one partially completed pass through command look-up tables for the fight controllers, significant updates to one of the MDT displays, a spreadsheet containing data on what is included in the CST-100 public data, a tool to create a csv file with specific information from spreadsheets containing command data, a command script for the November MCC-ASIL testing which resulted in a successful test day identifying several potential issues, and notes from one of the TCVB meetings that was used to keep the teams up to date on what was discussed and decided. I have learned a great deal working at NASA these last four months. I was able to meet and work with amazing individuals, further develop my technical knowledge, expand my knowledge base regarding human spaceflight, and contribute to the CST-100 missions. My work at NASA has strengthened my desire to continue my education in order to make further contributions to the field, and has given me the opportunity to see the advantages of a career at NASA.

Fanourakis, Sofia↗
NASA NTRS2022

Visualizing Multi-process CPU Utilization using CUSP

The CPU Utilization Statistics Plotter (CUSP) tool automates the interpretation of detailed CPU Utilization trace data and statistics. It puts you on the cusp of understanding how CPU resources are split among the many parallel components of a software system.CUSP combines time-sampled CPU utilization numbers and Event Log annotations to generate human-readable plots and tables. It automatically splits up large CPU usage log files around interesting events, determines and highlights just the tasks of primary relevance by evaluating their changing contribution to each plot's total CPU usage, automatically eliminates irrelevant tasks, provides context by labeling plots with names and durations of all active commands, and uses consistent color-coding to enable quick visual comparison across multiple plots.CUSP has been used to process CPU Utilization trace logs on the Mars Science Laboratory and the Mars 2020 Rover missions during flight software development and Flight Operations on the Martian surface since December 2013.

Maimone, Mark W↗
NASA NTRS2006

Automated Activation and Deactivation of a System Under Test

The MPLM Automated Activation/Deactivation application (MPLM means Multi-Purpose Logistic Module) was created with a three-fold purpose in mind: 1. To reduce the possibility of human error in issuing commands to, or interpreting telemetry from, the MPLM power, computer, and environmental control systems; 2. To reduce the amount of test time required for the repetitive activation/deactivation processes; and 3. To reduce the number of on-console personnel required for activation/ deactivation. All of these have been demonstrated with the release of the software. While some degree of automated end-item commanding had previously been performed for space-station hardware in the test environment, none approached the functionality and flexibility of this application. For MPLM activation, it provides mouse-click selection of the hardware complement to be activated, activates the desired hardware and verifies proper feedbacks, and alerts the user when telemetry indicates an error condition or manual intervention is required. For MPLM deactivation, the product senses which end items are active and deactivates them in the proper sequence. For historical purposes, an on-line log is maintained of commands issued and telemetry points monitored. The benefits of the MPLM Automated Activation/ Deactivation application were demonstrated with its first use in December 2002, when it flawlessly performed MPLM activation in 8 minutes (versus as much as 2.4 hours for previous manual activations), and performed MPLM deactivation in 3 minutes (versus 66 minutes for previous manual deactivations). The number of test team members required has dropped from eight to four, and in actuality the software can be operated by a sole (knowledgeable) system engineer.

Poff, Mark A.↗
NASA NTRS2016

Marshall Space Flight Center Ground Systems Development and Integration

Ground Systems Development and Integration performs a variety of tasks in support of the Mission Operations Laboratory (MOL) and other Center and Agency projects. These tasks include various systems engineering processes such as performing system requirements development, system architecture design, integration, verification and validation, software development, and sustaining engineering of mission operations systems that has evolved the Huntsville Operations Support Center (HOSC) into a leader in remote operations for current and future NASA space projects. The group is also responsible for developing and managing telemetry and command configuration and calibration databases. Personnel are responsible for maintaining and enhancing their disciplinary skills in the areas of project management, software engineering, software development, software process improvement, telecommunications, networking, and systems management. Domain expertise in the ground systems area is also maintained and includes detailed proficiency in the areas of real-time telemetry systems, command systems, voice, video, data networks, and mission planning systems.

Wade, Gina↗
NASA NTRS1976

Reduced state feedback gain computation

Because application of conventional optimal linear regulator theory to flight controller design requires the capability of measuring and/or estimating the entire state vector, it is of interest to consider procedures for computing controls which are restricted to be linear feedback functions of a lower dimensional output vector and which take into account the presence of measurement noise and process uncertainty. Therefore, a stochastic linear model that was developed is presented which accounts for aircraft parameter and initial uncertainty, measurement noise, turbulence, pilot command and a restricted number of measurable outputs. Optimization with respect to the corresponding output feedback gains was performed for both finite and infinite time performance indices without gradient computation by using Zangwill's modification of a procedure originally proposed by Powell. Results using a seventh order process show the proposed procedures to be very effective.

Kaufman, H.↗
NASA NTRS1985

Toward the fully capable AI space mission planner

The necessity of expending numerous ground-side manhours to write extremely concise command codes for deep-space probes in-flight, which carry limited on-board processing capabilities, is encouraging the development of AI modules to perform the same task. An experimental automated sequence planner, Deviser, has proven successful enough, when used on a mainframe computer, to continue with the next generation of the concept, PLAN-IT, an expert scheduler for spacecraft observation targets. The new system will provide the ground-based user with interactive graphic displays for choosing targets and generates an expected time-line. An updated Deviser, using the new modules, will be tested after the Voyager Uranus encounter, and PLAN-IT will be employed to formulate Spacelab activity schedules.

Grenander, S.↗
NASA NTRS1988

Computerized monitoring and control of experiments in space

The computer subsystem of the Villanova University GAS (Get Away Special) experiment apparatus is discussed. The function of the computer subsystem is to provide data acquisition and control system support to the experiments. The computer subsystem will provide high availability, low power consumption and highly reliable data retention. The general layout of the subsystem provides for redundant processing units, control modules, and multiple data acquisition modules. Each of the two redundant processing units will be composed of a microprocessor, control logic, PROM, RAM, non-volitile memory, timers, self-check logic and data ports to the data acquisition and control modules. One unit will control the experiment while the other shadows the primary unit operation. The data acquisition module gathers data from the experiment. The data is transfered to the processing unit in digital form. The control module validates the data, decodes it and executes the command.

Janisch, Thomas V.↗
NASA NTRS1989

Knowledge-based control of an adaptive interface

The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations.

Lachman, Roy↗
NASA NTRS1995

Built-In Diagnostics (BID) Of Equipment/Systems

Diagnostician(TM)-on-Chip (DOC) technology identifies faults and commands systems reconfiguration. Smart microcontrollers operating in conjunction with other system-control circuits, command self-correcting system/equipment actions in real time. DOC microcontroller generates commands for associated built-in test equipment to stimulate unit of equipment diagnosed, collects and processes response data obtained by built-in test equipment, and performs diagnostic reasoning on response data, using diagnostic knowledge base derived from design data.

Granieri, Michael N.↗
NASA NTRS1999

Autonomous Onboard Science Image Analysis for Future Mars Rover Missions

To explore high priority landing sites and to prepare for eventual human exploration, future Mars missions will involve rovers capable of traversing tens of kilometers. However, the current process by which scientists interact with a rover does not scale to such distances. Specifically, numerous command cycles are required to complete even simple tasks, such as, pointing the spectrometer at a variety of nearby rocks. In addition, the time required by scientists to interpret image data before new commands can be given and the limited amount of data that can be downlinked during a given command cycle constrain rover mobility and achievement of science goals. Experience with rover tests on Earth supports these concerns. As a result, traverses to science sites as identified in orbital images would require numerous science command cycles over a period of many weeks, months or even years, perhaps exceeding rover design life and other constraints. Autonomous onboard science analysis can address these problems in two ways. First, it will allow the rover to transmit only "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands. For example, a rover might autonomously acquire and return spectra of "interesting" rocks along with a high resolution image of those rocks in addition to returning the context images in which they were detected. Such approaches, coupled with appropriate navigational software, help to address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing fast, autonomous algorithms to enable such intelligent on-board decision making by spacecraft. Autonomous algorithms developed to date have the ability to identify rocks and layers in a scene, locate the horizon, and compress multi-spectral image data. Output from these algorithms could be used to autonomously obtain rock spectra, determine which images should be transmitted to the ground, or to aid in image compression. We will discuss these and other algorithms and demonstrate their performance during a recent rover field test.

Gulick, V. C.↗
NASA NTRS1999

Autonomous Image Analysis for Future Mars Missions

To explore high priority landing sites and to prepare for eventual human exploration, future Mars missions will involve rovers capable of traversing tens of kilometers. However, the current process by which scientists interact with a rover does not scale to such distances. Specifically, numerous command cycles are required to complete even simple tasks, such as, pointing the spectrometer at a variety of nearby rocks. In addition, the time required by scientists to interpret image data before new commands can be given and the limited amount of data that can be downlinked during a given command cycle constrain rover mobility and achievement of science goals. Experience with rover tests on Earth supports these concerns. As a result, traverses to science sites as identified in orbital images would require numerous science command cycles over a period of many weeks, months or even years, perhaps exceeding rover design life and other constraints. Autonomous onboard science analysis can address these problems in two ways. First, it will allow the rover to preferentially transmit "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands. For example, a rover might autonomously acquire and return spectra of "interesting" rocks along with a high-resolution image of those rocks in addition to returning the context images in which they were detected. Such approaches, coupled with appropriate navigational software, help to address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing fast, autonomous algorithms to enable such intelligent on-board decision making by spacecraft. Autonomous algorithms developed to date have the ability to identify rocks and layers in a scene, locate the horizon, and compress multi-spectral image data. We are currently investigating the possibility of reconstructing a 3D surface from a sequence of images acquired by a robotic arm camera. This would then allow the return of a single completely in focus image constructed only from those portions of individual images that lie within the camera's depth of field. Output from these algorithms could be used to autonomously obtain rock spectra, determine which images should be transmitted to the ground, or to aid in image compression. We will discuss these algorithms and their performance during a recent rover field test.

Gulick, V. C.↗
NASA NTRS2012

Creation of an Upper Stage Trajectory Capability Boundary to Enable Booster System Trade Space Exploration

The problem of trajectory optimization is important in all space missions. The solution of this problem enables one to specify the optimum thrust steering program which should be followed to achieve a specified mission objective, simultaneously satisfying the constraints.1 It is well known that whether or not the ascent trajectory is optimal can have a significant impact on propellant usage for a given payload, or on payload weight for the same gross vehicle weight.2 Consequently, ascent guidance commands are usually optimized in some fashion. Multi-stage vehicles add complexity to this analysis process as changes in vehicle properties in one stage propagate to the other stages through gear ratios and changes in the optimal trajectory. These effects can cause an increase in analysis time as more variables are added and convergence of the optimizer to system closure requires more analysis iterations. In this paper, an approach to simplifying this multi-stage problem through the creation of an upper stage capability boundary is presented. This work was completed as part of a larger study focused on trade space exploration for the advanced booster system that will eventually form a part of NASA s new Space Launch System.3 The approach developed leverages Design of Experiments and Surrogate Modeling4 techniques to create a predictive model of the SLS upper stage performance. The design of the SLS core stages is considered fixed for the purposes of this study, which results in trajectory parameters such as staging conditions being the only variables relevant to the upper stage. Through the creation of a surrogate model, which takes staging conditions as inputs and predicts the payload mass delivered by the SLS upper stage to a reference orbit as the response, it is possible to identify a "surface" of staging conditions which all satisfy the SLS requirement of placing 130 metric tons into low-Earth orbit (LEO).3 This identified surface represents the 130 metric ton capability boundary for the upper stage, such that if the combined first stage and boosters can achieve any one staging point on that surface, then the design is identified as feasible. With the surrogate model created, design and analysis of advanced booster concepts is streamlined, as optimization of the upper stage trajectory is no longer required in every design loop.

Walsh, Ptrick↗
NASA NTRS2015

The Use of Field Programmable Gate Arrays (FPGA) in Small Satellite Communication Systems

This paper will describe the use of digital Field Programmable Gate Arrays (FPGA) to contribute to advancing the state-of-the-art in software defined radio (SDR) transponder design for the emerging SmallSat and CubeSat industry and to provide advances for NASA as described in the TAO5 Communication and Navigation Roadmap (Ref 4). The use of software defined radios (SDR) has been around for a long time. A typical implementation of the SDR is to use a processor and write software to implement all the functions of filtering, carrier recovery, error correction, framing etc. Even with modern high speed and low power digital signal processors, high speed memories, and efficient coding, the compute intensive nature of digital filters, error correcting and other algorithms is too much for modern processors to get efficient use of the available bandwidth to the ground. By using FPGAs, these compute intensive tasks can be done in parallel, pipelined fashion and more efficiently use every clock cycle to significantly increase throughput while maintaining low power. These methods will implement digital radios with significant data rates in the X and Ka bands. Using these state-of-the-art technologies, unprecedented uplink and downlink capabilities can be achieved in a 1/2 U sized telemetry system. Additionally, modern FPGAs have embedded processing systems, such as ARM cores, integrated inside the FPGA allowing mundane tasks such as parameter commanding to occur easily and flexibly. Potential partners include other NASA centers, industry and the DOD. These assets are associated with small satellite demonstration flights, LEO and deep space applications. MSFC currently has an SDR transponder test-bed using Hardware-in-the-Loop techniques to evaluate and improve SDR technologies.

Varnavas, Kosta↗