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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Astrobee: Improving Capabilities for Free Flying Robotic Technology Demonstrations

The Astrobee Project has completed three years operating inside the ISS. Three Astrobee Free Flyers reached the ISS in April 2019 and are currently hosting a variety of users. During this time, Astrobee has advanced the state of the art in free-flying robots on ISS, operated over 100 sessions, logged over 750 hours of free-flyer operation, and made several capability improvements. Astrobee’s primary objective is to provide a highly flexible and capable free-flying robotic research platform to enable future guest scientist investigations. However, Astrobee is also demonstrating the feasibility of intra-vehicular robots (IVR) for performing key caretaking functions within exploration vehicles as part of NASA’s Moon-to-Mars exploration strategy. IVR capabilities will be especially vital during uncrewed mission phases. For example, current plans call for the lunar Gateway to be uncrewed >85% of the time. Astrobee’s baseline implementation supports free-flying camera and sensor survey use cases. Astrobee guest scientists can deploy software updates and hardware payloads to extend its capabilities. Astrobee is continuously improving its navigation robustness, general flight software maturity, and ISS interior maps, both through the baseline Astrobee operations and with the help of the ISAAC project. Astrobee began with mapping, localization, and operations in the Japanese Experiment Module (JEM), and has expanded to mapping in Node 2 and the US Lab. Astrobee has improved localization and operational robustness through improved mapping processes, algorithm updates (Soussan 2022) that reduce the occurrences of lost localization as well as developed recovery techniques to return to a good localization fix when loss of localization does occur. Future guest science experiments currently in development could demonstrate cargo transfer, fault isolation, free flyer and stationary robot collaboration, microgravity fluid transfer, and new docking mechanisms, among others. This presentation will focus on 1) Astrobee technical capabilities 2) What Astrobee can provide to a guest science experiment 3) Astrobee’s recent improvements 4) Possibilities for using Astrobee for future investigations. Soussan, R., Kumar, V., Coltin, B. and Smith, T. (2022) AstroLoc: An Efficient and Robust Localizer for a Free-flying Robot, Proc. Int. Conf. Rob. Autom. (ICRA) [to appear]

Astrobee↗
NASA NTRSDate not supplied

Pathfinding for Airspace with Autonomous Vehicles (PAAV) Multi-Vehicle Operations with Digital Trajectories

The Path Finding for Airspace with Autonomous Vehicles (PAAV) subproject under ATM-X is developing concepts and solutions to allow pilots to supervise multiple uncrewed flights at a time. This line of research stems from industry's desire to leverage Uncrewed Aircraft (UA) operations to achieve maximum productivity from pilot and aircraft resources, driven partially by pilot staffing shortages. Trajectory based solutions delivered by data link offer a potential solution to the multi-vehicle (m:N) problem by minimizing the number of instructions between remote pilots and air traffic controllers. Furthermore, such solutions avoid the need for pilots to monitor multiple voice frequencies at a time for air traffic control instructions to manage multiple flights. This panel presentation will give a brief introduction to PAAV followed by a description of NASA's AutoResolver capability for generating comprehensive air traffic control clearances and communicating them via data link for controller approval and flight execution.

multi vehicle control, trajectory based operations↗
NASA NTRSDate not supplied

Experimental Testing of Data Fusion in A Distributed Ground-Based Sensing Network for Advanced Air Mobility

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles(UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with two independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10%increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by one of the two radars.

Federica Vitiello↗
NASA NTRS2024

Exploration Extravehicular Mobility Unit (xEMU) Chamber B Thermal Vacuum “Suit 2” Pressure Garment System Hardware and Test Design

NASA’s Exploration Extravehicular Mobility Unit (xEMU) is the government reference next-generation space suit design and is engineered to protect astronauts from extreme lunar environmental temperatures. To evaluate the xEMU hardware thermal requirements, the xEMU Testing Team invented, designed, and executed a dual-suit, uncrewed thermal vacuum (TVAC) test at Johnson Space Center’s (JSC) Chamber B. This paper details the test hardware design and test methodology for the “Suit 2” Pressure Garment System (PGS) test article. The uncrewed “Suit 2” PGS test article consisted of a full PGS assembly with simulated Portable Life Support System (PLSS) functionality provided by test equipment, including a ventilation loop and two distinct thermal control loops. This paper will discuss in depth the test hardware design, including internal suit thermal boundary simulation, sensor quantity and placement, test support equipment rigs for gas flow, water flow, and power. Custom hardware designed to add additional penetrations to the suit or provide additional interfaces for sensors will also be discussed. This paper will also address the assembly and integration sequence for the test article. In addition to test hardware design, this paper will provide insights into the test methodology for this test article, including a discussion of thermal steady-state testing, simultaneous dual suit thermal vacuum testing, and hazard mitigation and controls.

xEMU↗
NASA NTRS2024

Considerations for Using Autonomous Flight Termination Software in Crewed Launch Vehicles

Autonomous flight termination systems (AFTS) are being progressively employed onboard launch vehicles to replace ground personnel and infrastructure needed to terminate flight or destruct the vehicle should an anomaly occur. This automation uses on-board real-time data and encoded logic to determine if the flight should be self-terminated. For uncrewed launch vehicles, FTS systems are required to protect the public and governed by the United States Space Force (USSF). For crewed missions, NASA must augment range AFTS requirements for crew safety and certify each flight according to human rating standards, thus adding unique requirements for reuse of software originally intended for uncrewed missions. This bulletin summarizes new information relating to AFTS to raise awareness of key distinctions, summarize considerations and outline best practices for incorporating AFTS into human-rated systems.

Avionics↗
NASA NTRS2025

Demonstration of Data Processing and Fusion from Distributed Radars for AAM Surveillance

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles (UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with three independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10% increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by two of the radars.

Federica Vitiello↗
NASA NTRS2025

Distributed Sensing Node Configuration

A vision and radar sensor integration strategy for surveillance of Advance Air Mobility Mission concept of airspace is contained in the CAD drawing in this publication developed as part of NASA's Transformational Tools and Technology project. High-density airspace operations with multiple aircraft type and potentially noncooperative aircraft require distributed sensor detection and tracking systems to monitor airspace for safe, autonomous flight operations for advanced air mobility, urban air mobility, and high density small uncrewed air systems (SUAS) flight concepts. Contained herein are drawings that are available in the stp and creo file formats of the distributed sensing nodes. Additional dovetail integration is included to enable rapid changing of embedded system. A day in the life node deployment is included in the 2023_last_flight_day.mp4. Please cite this publication if you use these drawings. This sensor configuration methodology is presented in detail in the publication reference below. Chester Dolph, Thomas Lombaerts, Corey A. Ippolito, Vahram Stepanyan, Evan Kawamura, Keerthana Kannan, George Szatkowski, Todd Ferante, Christopher Morris, Federica Vitiello, Flavia Causa, Roberto Opromolla and Giancarmine Fasano. "Distributed Sensor Fusion of Ground and Air Nodes using Vision and Radar Modalities for Tracking Multirotor Small Uncrewed Air Systems and Birds," AIAA 2024-1781. AIAA SCITECH 2024 Forum. January 2024.

Chester V Dolph↗
DOE OSTI2024

A Study of Intermittent Turbulence in Stable Arctic Boundary Layers

Abstract Polar boundary layers are difficult to model due to the existence of intermittent turbulence within stable layers. Here we present a case study evaluation of coherent structures in a stable boundary layer observed during a series of flights with an uncrewed aircraft system (DataHawk2) on 19 October 2016 at Oliktok Point, Alaska as part of the ERASMUS (Evaluation of Routine Atmospheric Sounding Measurements using Unmanned Systems) field campaign. During a sequence of five flights over a nine-hour period, 57 profiles of atmospheric properties (0–400 m a.g.l) were collected. Turbulence was identified using derived Richardson Number, temperature structure function parameter, and turbulence kinetic energy dissipation. Throughout all flights on this strongly stable day, intermittent turbulence was observed. These turbulent layers showed well-mixed potential temperature profiles embedded within otherwise stable potential temperature profiles; often resulting in a characteristic staircase pattern. Turbulent layers ranged from 1 to 30 m deep, with most individual layers being 1–2 m deep. Vertical propagation velocities of layers in the lower atmosphere were on the order of a few cm s −1 , typical of non-convective environments. In different regions of the profile, turbulence was driven by a different balance of buoyancy and shear forces, with turbulence in the near surface environment driven by strong shear forces overcoming strong resistance to buoyancy, while turbulence in elevated layers characterized by weaker shear forces overcoming weaker resistance to buoyancy. We discuss the potential of such datasets for improving subgrid parameterizations of small-scale turbulence embedded within stable boundary layers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Relationships between summertime surface albedo and melt pond fraction in the central Arctic Ocean: The aggregate scale of albedo obtained on the MOSAiC floe

As part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), the HELiX uncrewed aircraft system (UAS) was deployed over the sea ice in the central Arctic Ocean during summer 2020. Albedo measurements were obtained with stabilized pyranometers, and melt pond fraction was calculated from orthomosaic imagery from a surface-imaging multispectral camera. This study analyzed HELiX flight data to provide insights on the temporal and spatial evolution of albedo and melt pond fraction of the MOSAiC floe during the melt season as it drifted south through Fram Strait. The surface albedo distributions showed peak values changing from high albedo (0.55–0.6) to lower values (0.3) as the season advanced. Inspired by methods developed for satellite data, an algorithm was established to retrieve melt pond fraction from the orthomosaic images. We demonstrate that the near-surface observations of melt pond fraction were highly dependent on sample area, offering insight into the influence of subgrid scale features and spatial heterogeneity in satellite observations. Vertical observations conducted with the HELiX were used to quantify the influence of melt pond scales on observed surface albedo as a function of sensor footprint. These scaling results were used to link surface-based measurements collected during MOSAiC to broader-scale satellite data to investigate the influence of surface features on observed albedo. Albedo values blend underlying features within the sensor footprint, as determined by the melt pond size and concentration. This study framed the downscaling (upscaling) problem related to the airborne (surface) observations of surface albedo across a variety of spatial scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Measurements of TRACER pre-convective conditions and mesoscale circulations using small unmanned aircraft systems (sUAS)

Improved comprehension of the physical processes governing convective cloud formation and lifecycle are of critical importance for understanding and predicting future climate states. The influence of these clouds on the planetary energy budget, including on precipitation, is significant. Things are particularly complex in coastal regimes, where gradients in aerosol particle properties, localized circulations such as sea breezes, and large population centers are found. To date, numerical models struggle to accurately represent these critical clouds and are therefore challenged to provide a realistic view on the planetary energy budget. Through the proposed research, we deployed two uncrewed aircraft systems (UAS) equipped with a variety of instruments alongside sensors deployed by the US Department of Energy Atmospheric Radiation Measurement (ARM) program for the TRACER (Tracking Aerosol Convection Interactions Experiment) field campaign. The two small UAS platforms consisted of a CU RAAVEN fixed-wing airplane and an OU CopterSonde system, with the copter collecting frequent vertical profiles of thermodynamic and kinematic variables such as temperature, pressure, wind and humidity. At the same time, the fixed-wing captured horizontal gradients of these quantities and aerosol size distribution. These systems were deployed south of the Houston metro area, in an area that is impacted by the Gulf of Mexico sea breeze on a daily basis. These observations offer enhanced and complementary perspectives to those provided by the DOE ARM Mobile Facility (AMF) which is was deployed in southeast Houston, and an ancillary site in a more rural location west of the urban Houston area. Quality-controlled versions of the UAS data were collected and posted on the DOE ARM data archive after the conclusion of the campaign where they are accessible by the research community and general public. The UAS perspective offers revolutionary insight into key spatial and temporal effects that have not been evaluated previously.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Surface Systems Capability Gaps for Enabling NASA’s Sustainable Lunar Operations

This paper discusses the NASA Ground, Test, and Surface Systems Taxonomy (TX-13) related capability gaps, including details of architecture, technology, engineering, and policy gaps for enabling sustainable lunar surface operations and subsequent Mars missions. Architecture gaps include standardized architectures and interfaces, multi-element systems engineering and integration, design for supportability, and nuclear payload processing and launch approach. Technology gaps, primarily focused on uncrewed surface operations, include automated/autonomous cryogenic loading, transfer, servicing, and storage of commodities; health determination and fault management; automated/autonomous planning and scheduling; automated/autonomous inspection, maintenance and repair; logistics management and reliability; launch and landing site preparation; commodity management; and advanced umbilicals and dust tolerant interfaces. Engineering gaps include high-purity propellant production for ground and surface applications and large-scale xenon servicing capabilities. The policy gap includes nuclear propulsion acceptance testing and qualification approach. Strategically identifying human/automation roles and tasks and infusing automation and autonomy practices early in a system’s lifecycle is essential for achieving the mission objectives for a sustainable human lunar presence, improving performance and mission effectiveness, reducing operations costs and reliance on humans to perform tasks, and accommodating ground communication delays.

Surface Systems↗
NASA NTRS2022

PAAV Concept Document

The Pathfinding for Airspace with Autonomous Vehicles (PAAV) Concept Document, version 1.0, lays out the key challenges and potential solutions for the use of uncrewed aircraft (UA) technology for future regional air cargo operations. The challenges and solutions described in this document were informed by communications with the UA industry community (e.g., RTCA, the Federal Aviation Administration, and regional air cargo business operators), as well as the PAAV team’s research activities during the last two years including four tabletop exercises, a human-in-the-loop simulation study, a numerical simulation study, a functional allocation study, and flight data analysis (Appendix A). This document first describes the expected operational context of PAAV (Section 2), such as the flight mission, baseline UAS components, nominal operations, m:N operations (i.e., "m" remote pilots per "N" aircraft), and off-nominal operations. This context sets the scope for the PAAV concept development work. PAAV concept development assumes that UA operations will be increasingly autonomous. Thus, near- and far-term assumptions are defined (Section 3). PAAV identified seven key challenges for UA operations (Section 4): - Flight route planning - Separation and flow management - Traffic pattern integration - Contingency management - Taxi, takeoff, and landing - m:N operations - Communications operations The following 13 potential solutions to these challenges are then described (Section 5): - Scalable communications architecture - Data link - Designated UAS corridors - Crew planning for m:N operations - Flight route optimization - Traffic load-level control - Trajectory solutions with data link - Automated hazard avoidance for m:N operations - Traffic pattern integration (TPI) tool - Standard lost command and control (C2) link (LC2L) procedures - Automated hazard avoidance under LC2L - Auto-taxi, auto-takeoff, and auto-land - Ground control station (GCS) user interface for m:N operations The document attempts to link each of these solutions to one or more of the challenge areas. Novel solutions involving numerous automation technologies are needed to mitigate traffic and airspace management challenges, especially for realizing m:N operations and ensuring safety under LC2L conditions. The purpose of this document is to help understand alternatives and tradeoffs among potential solutions and provide a foundation for a cohesive PAAV concept that will be described and refined in subsequent concept versions.

Unmanned aircraft, uncrewed aircraft, regional air↗
NASA NTRSDate not supplied

Foundational Human-Autonomy Teaming Research and Development in Scalable Remotely Operated Advanced Air Mobility Operations: Research Model and Initial Work

To achieve the scalability envisioned for many Advanced Air Mobility (AAM) applications, uncrewed aerial system (UAS) concepts are being pursued with the goal of enabling fewer human operators to manage more increasingly autonomous vehicles. NASA’s Transformational Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) subproject has identified human-autonomy teaming (HAT) as a critical area of research required to support these operations. Under T3-RAM, the HAT Foundational Research Activity has been tasked with providing basic research to identify HAT and human-automation interaction (HAI) principles that can be used to achieve scalable multi-vehicle UAS operations. This paper first outlines a research model to produce ecologically relevant basic research, then contextualizes completed and planned research and development activities within this model. Proposed research threads are presented, along with their practical and theoretical implications.

Human-Autonomy Teaming↗
NASA NTRSDate not supplied

Remote Pilot Handoffs in Large UAS Multi-Vehicle Operations: Best Practices and Supportive Technologies

In response to pilot shortages and increasing air cargo demands, NASA's Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project conducted the fourth in a series of tabletop studies investigating scalable solutions for integrating large Uncrewed Aircraft Systems (UAS) into the National Airspace System (NAS). This study solicited subject matter expertise to identify solutions to potential challenges for a further term vision, guiding participants through scenario-based discussions where the remote pilot (RP)-to-vehicle ratio has been scaled from 1:1 to m:N. Of those challenges, remote pilot handoffs were found throughout all phases of flight, both in nominal and non-nominal scenarios. The current paper details participant-suggested procedural and technological solutions for overcoming the handoff challenge, including determining the accepting RP, which aircraft to release, the location and timing of the transition, and options for supporting personnel, tools, and automation that could facilitate safe and efficient handoffs.

uncrewed aircraft systems↗
NASA NTRSDate not supplied

Assessment of Remote Pilot Maneuver Taskload under Multi-Vehicle Control

Multi-vehicle control schemes where a number of remote pilots (m) supervise a number of uncrewed vehicles (m:N) are desired to enable scalability of operations, such as air cargo delivery, in the face of pilot shortage and other constraints. We use queuing models derived from historical track data to assess the increased task load on a remote pilot due to maneuvering demands as the number of supervised vehicles increase. We quantify metrics such as the probability that the inter-maneuver time and inter-communication time.

Multi-Vehicle Control↗
NASA NTRSDate not supplied

Pathfinding for Airspace with Autonomous Vehicles (PAAV) Overview for RTCA SC-228

The Pathfinding for Airspace with Autonomous Vehicles (PAAV) sub-project started in 2021 under NASA’s Air Traffic Management – eXploration (ATM-X) project. ATM-X as a project is conducting research to support the growth of traditional aviation and new entrants. This presentation discusses the background of the PAAV project as well as it’s current areas of focus around uncrewed aircraft system (UAS) operations. The areas include the development of a flight test ecosystem, detect and avoid, traffic pattern integration, aircraft-to-aircraft communications, and contingency management. The aim of these research areas is to help inform the development of performance standards and FAA-approved procedures for integrating UAS into the national airspace system (NAS). The presentation seeks to describe the PAAV research objectives in sufficient detail to allow the committee to provide feedback on the sub-project's approach and main areas of interest.

uncrewed aircraft systems↗
NASA NTRSDate not supplied

Advancements in Remote Ground Control Station Operator Pilot in Command Training Program for Beyond Visual Line of Sight Flight Operations

The training program for a Remote Ground Control Station Operator Pilot in Command (R-GCSO PIC) at NASA Langley Research Center marks a pivotal evolution in preparing operators for Beyond Visual Line of Sight (BVLOS) operations. This program, developed within the Advanced Air Mobility (AAM) project High Density Vertiplex (HDV) subproject, was crafted to bridge the gap between traditional Ground Control Station Operators (GCSO) and R-GCSO PICs, focusing on uncrewed aircraft systems (UAS). It encompassed extensive theoretical and practical training, including hands-on experience with advanced simulators and live flight operations, while ensuring a deep understanding of BVLOS complexities. The training leveraged NASA technologies like the MPATH (Measuring Performance for Autonomy Teaming with Humans) ground control station software and incorporated human factors principles to enhance operational readiness. This paper details the program's development, execution, and the critical insights gained, emphasizing the necessity of continuous adaptation in training methodologies to meet the evolving demands of UAS operations in the National Airspace System.

Ground control station operator↗
NASA NTRSDate not supplied

Advancing Wildland Fire Response with NASA’s Second Shift Capabilities

Novel “Second-Shift” capabilities—leveraging Uncrewed Aerial Systems and Optionally Piloted Vehicles—are identified that could extend wildfire aerial logistics support into night or low-visibility conditions. Expert elicitations with subject-matter experts informed the development of these conceptual capabilities and identified key challenges in wildfire logistics operations. Furthermore, the potential of these capabilities could extend beyond aerial logistics support, encompassing aerial suppression, observation, and emergency extraction support for wildland firefighting. An approach to development, implementation and validation of the novel capabilities is described.

Wildfire logistics↗