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NASA NTRS2013

Cratos: The Evolution of a Robotic Vehicle

Cratos was originally designed to evaluate a small footprint, low-power, tracked vehicle for traversing a crater face and for scraping regolith from a crater basin on the lunar surface. These activities require a power-to-weight ratio such that the vehicle is able to pull its entire mass vertically off the ground with the power from one track. Further complicating matters, the available power-units that fit the vehicles approximate one cubic meter volume, restrict power consumption to 100 watts. Lastly, the vehicle is required to telemeter data from an array of sensors to a remote control station for further study. This unique mix of design constraints lead to the creation of a versatile mobile sensor platform, described in this paper, capable of performing a myriad of functions beyond the scope of its original purpose.

Greer, Lawrence C.↗

NASA NTRS2012

Design for the Structure and the Mechanics of Moballs

The moball is envisioned to be a round, self-powered, and wind-driven multifunctioning sensor used in the Gone with the Wind ON-Mars (GOWON) [http://www.lpi.usra.edu/meetings/ marsconcepts2012/pdf/4238.pdf]: A Wind-Driven Networked System of Mobile sensors on Mars. The moballs would have sensing, processing, and communication capabilities. The moballs would perform in situ detection of key environmental elements such as vaporized water, trace gases, wind, dust, clouds, light and UV exposure, temperature, as well as minerals of interest, possible biosignatures, surface magnetic and electric fields, etc. The embedded various low-power micro instruments could include a Multispectral Microscopic Imager (to detect various minerals), a compact curved focal plane array camera (UV/Vis/NIR) with a large field of view, a compact UV/Visible spectrometer, a micro-weather station, etc. The moballs could communicate with each other and an orbiter. Their wind- or gravity-driven rolling movement could be used to harvest and store electric energy. They could also generate and store energy using the sunlight, when available, and the diurnal temperature variations on Mars. The moballs would be self-aware of their (and their neighbors ) positions, energy storage, and memory availability; they would have processing power and could intelligently cooperate with neighboring moballs by distributing tasks, sharing data, and fusing information. The major advantages of using the wind-driven and spherical moball network over rovers or other fixed sensor webs to explore Mars would be: (1) moballs could explore a much larger expanse of Mars in a much faster fashion, (2) they could explore the difficult terrains such as steep slopes and sand dunes, and (3) they would be self-energy- generating and could work together and move around autonomously. The challenge in designing the structure and the mechanics of the moball would be that it should be sturdy enough to withstand the impact of its initial fall, as well as other impacts from obstacles in its way. A mechanism would be needed that could enable hundreds of moballs to be carried while they would be deflated and compact, then would inflate them just after deploying them to their drop site. Furthermore, the moballs should also be light enough to allow them to move easily over obstacles by force of the wind. They also should have some kind of maneuvering mechanism in place to help them avoid very hazardous sharp objects or events, and to enable them to get closer to the objects of interest. The structure of the moballs was designed so that they would have different layers. The outer layer should comprise a sturdy, yet light, polymer that could withstand both the impact of the initial drop, as well as the impact of the different obstacles it would encounter while traversing the surface of Mars. This polymer should not deteriorate with the 100 K daily temperature swings on Mars. The inner layer should consist of a very light gas such as nitrogen or helium. In terms of maneuvering, six very light weights placed at strategic locations would give moballs the ability to turn, or even hop, over hazardous (e.g., sharp) obstacles, or even initiate a movement (before getting more help from the wind to be carried around) when stuck. Maneuvering would be necessary in order to get closer to objects of interest. If the weights would be allowed to move freely, they could also be used to generate energy.

Davoodi, Faranak↗

NASA NTRS2013

NASA Tech Briefs, January 2013

Topics include: Single-Photon-Sensitive HgCdTe Avalanche Photodiode Detector; Surface-Enhanced Raman Scattering Using Silica Whispering-Gallery Mode Resonators; 3D Hail Size Distribution Interpolation/Extrapolation Algorithm; Color-Changing Sensors for Detecting the Presence of Hypergolic Fuels; Artificial Intelligence Software for Assessing Postural Stability; Transformers: Shape-Changing Space Systems Built with Robotic Textiles; Fibrillar Adhesive for Climbing Robots; Using Pre-Melted Phase Change Material to Keep Payloads in Space Warm for Hours without Power; Development of a Centrifugal Technique for the Microbial Bioburden Analysis of Freon (CFC-11); Microwave Sinterator Freeform Additive Construction System (MS-FACS); DSP/FPGA Design for a High-Speed Programmable S-Band Space Transceiver; On-Chip Power-Combining for High-Power Schottky Diode-Based Frequency Multipliers; FPGA Vision Data Architecture; Memory Circuit Fault Simulator; Ultra-Compact Transputer-Based Controller for High-Level, Multi-Axis Coordination; Regolith Advanced Surface Systems Operations Robot Excavator; Magnetically Actuated Seal; Hybrid Electrostatic/Flextensional Mirror for Lightweight, Large-Aperture, and Cryogenic Space Telescopes; System for Contributing and Discovering Derived Mission and Science Data; Remote Viewer for Maritime Robotics Software; Stackfile Database; Reachability Maps for In Situ Operations; JPL Space Telecommunications Radio System Operating Environment; RFI-SIM: RFI Simulation Package; ION Configuration Editor; Dtest Testing Software; IMPaCT - Integration of Missions, Programs, and Core Technologies; Integrated Systems Health Management (ISHM) Toolkit; Wind-Driven Wireless Networked System of Mobile Sensors for Mars Exploration; In Situ Solid Particle Generator; Analysis of the Effects of Streamwise Lift Distribution on Sonic Boom Signature; Rad-Tolerant, Thermally Stable, High-Speed Fiber-Optic Network for Harsh Environments; Towed Subsurface Optical Communications Buoy; High-Collection-Efficiency Fluorescence Detection Cell; Ultra-Compact, Superconducting Spectrometer-on-a-Chip at Submillimeter Wavelengths; UV Resonant Raman Spectrometer with Multi-Line Laser Excitation; Medicine Delivery Device with Integrated Sterilization and Detection; Ionospheric Simulation System for Satellite Observations and Global Assimilative Model Experiments - ISOGAME; Airborne Tomographic Swath Ice Sounding Processing System; flexplan: Mission Planning System for the Lunar Reconnaissance Orbiter; Estimating Torque Imparted on Spacecraft Using Telemetry; PowderSim: Lagrangian Discrete and Mesh-Free Continuum Simulation Code for Cohesive Soils; Multiple-Frame Detection of Subpixel Targets in Thermal Image Sequences; Metric Learning to Enhance Hyperspectral Image Segmentation; Basic Operational Robotics Instructional System; Sheet Membrane Spacesuit Water Membrane Evaporator; Advanced Materials and Manufacturing for Low-Cost, High-Performance Liquid Rocket Combustion Chambers; Motor Qualification for Long-Duration Mars Missions.

Source record↗

DOE OSTI2025

GRUMDN: A Multi-Task Model for Predicting Human Patterns-of-Life from Stay Transition Data

Understanding human patterns-of-life (PoL) is essential towards ensuring safe and secure indoor facility environment as well as outdoor urban environment. Prediction of human movement in between places of interest is vital in understanding human PoL. Movement between spaces maybe represented and detected in one of the two forms: 1) trajectories: locations measured at regular time intervals by mobile sensors, bluetooth or GPS sensors; or 2) stay transitions: semantic PoI (points of interest) and stay duration data measurable by eventbased sensors that collect data when a check-in or check-out event is detected. Stay transition data provides a more compressed data format compared to trajectories data, especially in situations with longer stay durations, while preserving the information necessary for PoL analysis. Now as introduced briefly in the paper, our deployed end application (Digital Twin of a facility with non-player characters, besides the interactive user in virtual reality) needed a well-performing and validated AI/ML model for simulating high quality stay transitions behavior. In this study we thus primarily present our findings with developing and validating that model, which is a multi-task neural network for stay transition prediction. The neural network consists of two heads, for corresponding two tasks of stay category prediction and stay duration prediction. We evaluated gated recurrent units and multi-layer perceptrons of varying network sizes for stay category prediction; while mixture density networks, noisy generator-only networks, and generative adversarial networks of varying network sizes for stay duration prediction. We have then evaluated four multi-task models, constructed by combining these specialized models, on their ability to predict stay transition data. We tested our models on datasets from two different cases: 1) a simulation-generated dataset of indoor movement within the HFIR (high flux isotope reactor) nuclear reactor facility at Oak Ridge National Laboratory (ORNL); and 2) the GeoLife human mobility dataset of outdoor urban movement available in literature. Our results indicate that GRUMDN, which combines gated recurrent units (GRU) for stay category prediction task, and mixture density networks (MDN) for stay duration prediction task, did overall outperform other multitask models and the current state-of-the-art.

Gunaratne, Chathika [ORNL] (ORCID:0000000225088745↗

DOE OSTI2025

Advancing Development of Emissions Detection (Final Report)

This document is the final report to the U.S. Department of Energy (DOE for contract DE-FE0031873) awarded to Colorado State University (CSU). CSU and partners at Harrisburg University of Science and Technology, University of Texas Arlington, and University of Texas at Austin organized several testing rounds to provide knowledge focused on advancing the detection capabilities of emissions monitoring devices. With this funding opportunity the research group began by establishing the Advancing the Development of Emission Detection (ADED) program, with the goal focused on enhancing the accuracy, reliability, and field applicability of methane detection technologies. This effort aimed to address the critical challenges of identifying and quantifying methane emissions while enabling industry stakeholders to meet regulatory compliance and environmental sustainability goals. The program engaged with industry, government, and technology stakeholders to promote adoption and consensus on testing techniques for methane detection solutions. Methane, a potent greenhouse gas, contributes significantly to global warming, and the oil and natural gas (O&G) sector is a primary source of methane emissions. Regulatory measures such as leak detection and repair (LDAR) programs have been implemented to address emissions. However, traditional LDAR approaches, reliant on handheld and component-level measurements, are resource-intensive. To address these limitations and move with evolving regulations, advanced methane technologies are emerging. These solutions include ground-based sensors, mobile systems (e.g., drones, vehicles, and aircraft), and satellite-based platforms. They offer innovative capabilities for autonomous monitoring, larger spatial coverage, and emission quantification using methods such as tracer gas techniques and inverse modeling with Gaussian plume analysis. The ADED program began with creating protocols for methane controlled release (CR) testing these continuous monitoring (CM) and survey technologies that detect and monitor methane emissions at O&G facilities. The protocols were then implemented throughout testing of CM and survey devices at CSU’s Methane Emissions Technology Evaluation Center (METEC) facility from 2021 through 2024. As apart of the protocol, solutions that tested under the ADED program installed their solutions at METEC, documented their system under test, and provided detection reports to the METEC team for analysis. The METEC team would provide the solutions with analyzed reports of their emissions and ground truth data of the releases conducted during their testing session. Under the ADED program, CMs were also tested at O&G facilities for a six week test run of challenge release (ChR) releases. The findings from the ADED program underscore the critical role of collaborative research and innovation in tackling methane emissions, offering a pathway for the oil and gas sector to achieve significant environmental and economic benefits. Results from METEC testing saw improvement of performance and accuracy across all solutions over the extent of the ADED experiments. The results also showed a variance in CM solution performance between CRs and ChRs. That variance pushed the team to further analyze the differences between CR testing environments and field conditions. With the drive from regulations and that variance in field conditions, the ADED team began designing a new CR testing protocol and additions to the METEC testing facility. The METEC team is furthering the progress made through the ADED program with awarded funding from DE-FE0032276. This funding pushes the development of METEC’s addition with new equipment, allowing for an updated facility layout. METEC still facilitates for traditional facilities, with a legacy pad, while expanding an new design based on how O&G infrastructure has Final Report - Contract Number: DE-FE0031873 been changed over the last decade. Throughout the ADED program the team has also been working with international partners to ensure staying in the trend globally. International partners have been essential in moving the new protocol forward to implement into CR testing at the METEC facility in Spring 2025.

42 ENGINEERING↗

NASA NTRS1989

A comparison of the Shuttle remote manipulator system and the Space Station Freedom mobile servicing center

The Shuttle Remote Manipulator System is a mature system which has successfully completed 18 flights. Its primary functional design driver was the capability to deploy and retrieve payloads from the Orbiter cargo bay. The Space Station Freedom Mobile Servicing Center is still in the requirements definition and early design stage. Its primary function design drivers are the capabilities: to support Space Station construction and assembly tasks; to provide external transportation about the Space Station; to provide handling capabilities for the Orbiter, free flyers, and payloads; to support attached payload servicing in the extravehicular environment; and to perform scheduled and un-scheduled maintenance on the Space Station. The differences between the two systems in the area of geometric configuration, mobility, sensor capabilities, control stations, control algorithms, handling performance, end effector dexterity, and fault tolerance are discussed.

Taylor, Edith C.↗

NASA NTRS1991

Non-volatile, high density, high speed, Micromagnet-Hall effect Random Access Memory (MHRAM)

The micromagnetic Hall effect random access memory (MHRAM) has the potential of replacing ROMs, EPROMs, EEPROMs, and SRAMs because of its ability to achieve non-volatility, radiation hardness, high density, and fast access times, simultaneously. Information is stored magnetically in small magnetic elements (micromagnets), allowing unlimited data retention time, unlimited numbers of rewrite cycles, and inherent radiation hardness and SEU immunity, making the MHRAM suitable for ground based as well as spaceflight applications. The MHRAM device design is not affected by areal property fluctuations in the micromagnet, so high operating margins and high yield can be achieved in large scale integrated circuit (IC) fabrication. The MHRAM has short access times (less than 100 nsec). Write access time is short because on-chip transistors are used to gate current quickly, and magnetization reversal in the micromagnet can occur in a matter of a few nanoseconds. Read access time is short because the high electron mobility sensor (InAs or InSb) produces a large signal voltage in response to the fringing magnetic field from the micromagnet. High storage density is achieved since a unit cell consists only of two transistors and one micromagnet Hall effect element. By comparison, a DRAM unit cell has one transistor and one capacitor, and a SRAM unit cell has six transistors.

Wu, Jiin C.↗

NASA NTRS2016

Astrobee: A New Platform for Free-Flying Robotics on the International Space Station

The Astrobees are next-generation free-flying robots that will operate in the interior of the International Space Station (ISS). Their primary purpose is to provide a flexible platform for research on zero-g freeflying robotics, with the ability to carry a wide variety of future research payloads and guest science software. They will also serve utility functions: as free-flying cameras to record video of astronaut activities, and as mobile sensor platforms to conduct surveys of the ISS. The Astrobee system includes two robots, a docking station, and a ground data system (GDS). It is developed by the Human Exploration Telerobotics 2 (HET-2) Project, which began in Oct. 2014, and will deliver the Astrobees for launch to ISS in 2017. This paper covers selected aspects of the Astrobee design, focusing on capabilities relevant to potential users of the platform.

robotics↗

NASA NTRS2019

Astrobee Free Flyers: Integrated and Tested. Ready for Launch!

As of March 2019, four Astrobee free-flying robots have been integrated, tested and shipped to NASA’s Johnson Space Center, Texas, ready to be launched to space. Two of these Astrobee units (Honey and Bumble) will be launched to the International Space Station (ISS) on April 17, 2019, on the Cygnus NG-11 (Northrop Grumman) cargo resupply spacecraft from the Mid-Atlantic Regional Spaceport (MARS) launch facility, at NASA's Wallops Flight Facility, in Virginia, while the third unit (Queen) will be launched in mid-July 2019, with the cargo resupply mission Space-X 18, from Cape Canaveral, at NASA’s Kennedy Space Center. The primary purpose of the Astrobee system is to provide an autonomous and flexible platform for research on zero-g free-flying robotics, with the ability to accommodate guest researchers looking to utilize the unique capabilities of this platform in the microgravity of low earth orbit, and to advance the state of the art of guest science software and research payloads, which range from gecko-inspired adhesives for perching on smooth surfaces, to augmented reality interfaces to help astronauts and robots work together effectively, to RFID reader, performing inventory of RFID tagged items inside the ISS. Astrobee will also serve utility functions, such as free-flying cameras to record video and provide assistance during astronaut activities, and as mobile sensor platforms to conduct surveys of the ISS. In this paper we will give an overview of the status of the Astrobee system, which includes the docking station already launched and mounted in the JAXA JEM module of the ISS, the Astrobee robots, the Astrobee robotic arms, the ground data system (GDS) and the development of the several guest science payloads.

Carlino, Roberto↗

NASA NTRS2012

Methods of determining complete sensor requirements for autonomous mobility

A method of determining complete sensor requirements for autonomous mobility of an autonomous system includes computing a time variation of each behavior of a set of behaviors of the autonomous system, determining mobility sensitivity to each behavior of the autonomous system, and computing a change in mobility based upon the mobility sensitivity to each behavior and the time variation of each behavior. The method further includes determining the complete sensor requirements of the autonomous system through analysis of the relative magnitude of the change in mobility, the mobility sensitivity to each behavior, and the time variation of each behavior, wherein the relative magnitude of the change in mobility, the mobility sensitivity to each behavior, and the time variation of each behavior are characteristic of the stability of the autonomous system.

Curtis, Steven A.↗

NASA NTRS2008

Video Guidance Sensor for Surface Mobility Operations

Robotic systems and surface mobility will play an increased role in future exploration missions. Unlike the LRV during Apollo era which was an astronaut piloted vehicle future systems will include teleoperated and semi-autonomous operations. The tasks given to these vehicles will run the range from infrastructure maintenance, ISRU, and construction to name a few. A common task that may be performed would be the retrieval and deployment of trailer mounted equipment. Operational scenarios may require these operations to be performed remotely via a teleoperated mode,or semi-autonomously. This presentation describes the on-going project to adapt the Automated Rendezvous and Capture (AR&C) sensor developed at the Marshall Space Flight Center for use in an automated trailer pick-up and deployment operation. The sensor which has been successfully demonstrated on-orbit has been mounted on an iRobot/John Deere RGATOR autonomous vehicle for this demonstration which will be completed in the March 2008 time-frame.

Fernandez, Kenneth R.↗

NASA NTRS2004

Environmental Monitoring for Situation Assessment using Mobile and Fixed Sensors

This project was co-led by Dr. Sheila McIlraith and Prof. Richard Fikes. Substantial research results and published papers describing those results were produced in multiple technology areas, including the following: 1) Monitoring a Complex Physical System using a Hybrid Dynamic Bayes Net; 2) A Formal Theory of Testing for Dynamical Systems; 3) Diagnosing Hybrid Systems Using a Bayesian Model Selection Approach.

Fikes, Richard↗

NASA NTRS2008

NASA NDE Applications for Mobile MEMS Devices and Sensors

NASA would like new devices and sensors for performing nondestructive evaluation (NDE) of aerospace vehicles. These devices must be small in size/volume, mass, and power consumption. The devices must be autonomous and mobile so they can access the internal structures of aircraft and spacecraft and adequately monitor the structural health of these craft. The platforms must be mobile in order to transport NDE sensors for evaluating structural integrity and determining whether further investigations will be required. Microelectromechanical systems (MEMS) technology is crucial to the development of the mobile platforms and sensor systems. This paper presents NASA s needs for micro mobile platforms and MEMS sensors that will enable NDE to be performed on aerospace vehicles.

Wilson, William C.↗

NASA NTRS2014

Mobilization Protocols for Hybrid Sensors for Environmental AOP Sampling (HySEAS) Observations

The protocols presented here enable the proper mobilization of the latest-generation instruments for measuring the apparent optical properties (AOPs) of aquatic ecosystems. The protocols are designed for the Hybrid Sensors for Environmental AOP Sampling (HySEAS) class of instruments, but are applicable to the community of practice for AOP measurements. The protocols are organized into eleven sections beyond an introductory overview: a) cables and connectors, b) HySEAS instruments, c) platform preparation, d) instrument installation, e) cable installation, f) test deployment, g) test recovery, h) maintenance, i) shipping, j) storage, and k) smallboat operations. Each section concentrates on documenting how to prevent the most likely faults, remedy them should they occur, and accomplishing both with the proper application of a modest set of useful tools. Within the twelve sections, there are Socratic exercises to stimulate thought, and the answers to these exercises appear in Appendix A. Frequently asked questions (FAQs) are summarized in a separate section after the answers to the exercises in Appendix B. For practitioners unfamiliar with the nautical terms used throughout this document plus others likely encountered at sea, an abbreviated dictionary of nautical terms appears in Appendix C. An abbreviated dictionary of radiotelephone terms is presented in Appendix D. To ensure familiarity with many of the tools that are presented, Appendix E provides a description of the tools alongside a thumbnail picture. Abbreviated deployment checklists and cable diagrams are provided in Appendix F. The document concludes with an acknowledgments section, a glossary of acronyms, a definition of symbols, and a list of references.

Mobilizarion↗

NASA NTRS2020

Air Quality Monitoring Case Study Using Mobile Low-cost Sensors Mounted on Trash-Trucks: Methods Development and Lessons Learned

Air quality monitoring (AQM) is crucial for cities to develop management plans supporting population health. However, there is a dearth of measurements due to the high cost of standard reference instruments. Mobile AQM using low-cost sensors deployed on routine fleets of vehicles can enable the continuous detection of fine-scale pollutant variations in cities at a lower cost. New methods need to be developed to interpret these measurements. This paper presents three such methods. First, we propose a technique to identify aerosol hotspots. Second, we employ techniques published previously to assess the generalizable map of fine and coarse particle number concentrations, to understand qualitatively the contribution of local and regional sources across the region sampled. By using the raw number concentration of differently sized particles from the Optical Particle Counters (OPCs) instead of the noisier mass concentrations, we obtain more robust results. Third, in order to evaluate source signatures in cities, we propose another technique, in which we cluster the entire range of aerosol size-distribution measurements acquired. The properties of each cluster provide insight into the aerosol source characteristics in the sampling environment. We test these methods using a dataset we collected by mounting OPCs on two trash-trucks in Cambridge, Massachusetts.

Drive-by sensing↗

NASA NTRS2020

Air Quality Monitoring Case Study Using Mobile Low-cost Sensors mounted on Trash-Trucks: Methods Development and Lessons Learned

Drive-by sensing↗

NASA NTRS2009

High-Sensitivity GaN Microchemical Sensors

Systematic studies have been performed on the sensitivity of GaN HEMT (high electron mobility transistor) sensors using various gate electrode designs and operational parameters. The results here show that a higher sensitivity can be achieved with a larger W/L ratio (W = gate width, L = gate length) at a given D (D = source-drain distance), and multi-finger gate electrodes offer a higher sensitivity than a one-finger gate electrode. In terms of operating conditions, sensor sensitivity is strongly dependent on transconductance of the sensor. The highest sensitivity can be achieved at the gate voltage where the slope of the transconductance curve is the largest. This work provides critical information about how the gate electrode of a GaN HEMT, which has been identified as the most sensitive among GaN microsensors, needs to be designed, and what operation parameters should be used for high sensitivity detection.

Son, Kyung-ah↗

NASA NTRS2005

Development of GaN-based microchemical sensor nodes

Sensors based III-N technology are gaining significant interest due to their potential for monolithic integration of RF transceivers and light sources and the capability of high temperature operations. We are developing a GaN-based micro chemical sensor node for remote detection of chemical toxins, and present electrical responses of AlGaN/GaN HEMT (High Electron Mobility Transistor) sensors to chemical toxins as well as other common gases.

extreme environment↗