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At least 145 records · Page 8

NASA Tech Briefs, March 2014

Topics include: Data Fusion for Global Estimation of Forest Characteristics From Sparse Lidar Data; Debris and Ice Mapping Analysis Tool - Database; Data Acquisition and Processing Software - DAPS; Metal-Assisted Fabrication of Biodegradable Porous Silicon Nanostructures; Post-Growth, In Situ Adhesion of Carbon Nanotubes to a Substrate for Robust CNT Cathodes; Integrated PEMFC Flow Field Design for Gravity-Independent Passive Water Removal; Thermal Mechanical Preparation of Glass Spheres; Mechanistic-Based Multiaxial-Stochastic-Strength Model for Transversely-Isotropic Brittle Materials; Methods for Mitigating Space Radiation Effects, Fault Detection and Correction, and Processing Sensor Data; Compact Ka-Band Antenna Feed with Double Circularly Polarized Capability; Dual-Leadframe Transient Liquid Phase Bonded Power Semiconductor Module Assembly and Bonding Process; Quad First Stage Processor: A Four-Channel Digitizer and Digital Beam-Forming Processor; Protective Sleeve for a Pyrotechnic Reefing Line Cutter; Metabolic Heat Regenerated Temperature Swing Adsorption; CubeSat Deployable Log Periodic Dipole Array; Re-entry Vehicle Shape for Enhanced Performance; NanoRacks-Scale MEMS Gas Chromatograph System; Variable Camber Aerodynamic Control Surfaces and Active Wing Shaping Control; Spacecraft Line-of-Sight Stabilization Using LWIR Earth Signature; Technique for Finding Retro-Reflectors in Flash LIDAR Imagery; Novel Hemispherical Dynamic Camera for EVAs; 360 deg Visual Detection and Object Tracking on an Autonomous Surface Vehicle; Simulation of Charge Carrier Mobility in Conducting Polymers; Observational Data Formatter Using CMOR for CMIP5; Propellant Loading Physics Model for Fault Detection Isolation and Recovery; Probabilistic Guidance for Swarms of Autonomous Agents; Reducing Drift in Stereo Visual Odometry; Future Air-Traffic Management Concepts Evaluation Tool; Examination and A Priori Analysis of a Direct Numerical Simulation Database for High-Pressure Turbulent Flows; and Resource-Constrained Application of Support Vector Machines to Imagery.

Source record↗

Resilient, untethered soft robot

A pneumatically powered, fully untethered mobile soft robot is described. Composites consisting of silicone elastomer, polyaramid fabric, and hollow glass microspheres were used to fabricate a sufficiently large soft robot to carry the miniature air compressors, battery, valves, and controller needed for autonomous operation. Fabrication techniques were developed to mold a 0.65 meter long soft body with modified Pneumatic network actuators capable of operating at the elevated pressures (up to 138 kPa) required to actuate the legs of the robot and hold payloads of up to 8 kg. The soft robot is safe to handle, and its silicone body is innately resilient to a variety of adverse environmental conditions including snow, puddles of water, direct (albeit limited) exposure to flames, and the crushing force of being run over by an automobile.

42 ENGINEERING↗

A Flight Replanning Tool for Terminal Area Urban Air Mobility Operations

In this presentation we describe and evaluate a flight replanning tool, called the trial planner, for terminal area air transport applications. The trial planner employs predefined airspace structures to generate rerouting options between vertiports. In a simplified definition, vertiports are facilities that provide services for managing the take-off and landing of autonomous or manned electric vertical take-off or landing (eVTOL) aircraft. The airspace structures involved in our test cases are arrival routes that consist of predefined entry points to which a transitional path is computed dynamically from the current position of the aircraft. Rerouting options include the transitional path and approach segment along the arrival route; these rerouting options are not vetted for potential conflicts with other operations until a human operator commits to a choice and forwards the flight plan modification for approval from an automated airspace management service. A selected rerouting option is executed by loading a flight plan file to the aircraft ground control station. We conducted a qualitative evaluation of the trial planner using ratings provided by flight crews and air transportation human factors experts with relevant experience from air traffic control. Evaluation criteria included trust in the route recommendations and adequate explanation for the route options. We detail the logic and implementation of the trial planner, as well as report the results of the evaluation of the implementation herein.

Trial planning↗

Intelligent Contingency Management for Urban Air Mobility

The third aviation revolution is seeking to enable transportation where users have access to immediate and flexible air travel; the users dictate trip origin, destination and timing. One of the major components of this vision is urban air mobility (UAM) for the masses. UAM means a safe and efficient system for vehicles to move passengers and cargo within a city. In order to reach UAM’s full market potential the vehicle will have to be autonomous. One of the primary challenges of autonomous flight is dealing with off-nominal events, both common and unforeseen; thus, intelligent contingency management (ICM) is one of the enabling technologies. This paper proposes an ICM architecture with associated tools that would help enable the UAM vision.

UAM↗

Intelligent Contingency Management for Urban Air Mobility

The third aviation revolution is seeking to enable transportation where users have access to immediate and flexible air travel; the users dictate trip origin, destination and timing. One of the major components of this vision is urban air mobility (UAM) for the masses. UAM means a safe and efficient system for vehicles to move passengers and cargo within a city. In order to reach UAM’s full market potential the vehicle will have to be autonomous. One of the primary challenges of autonomous flight is dealing with off-nominal events, both common and unforeseen; thus, intelligent contingency management (ICM) is one of the enabling technologies. This paper proposes an ICM architecture with associated tools that would help enable the UAM vision.

UAM;↗

The Influence of Viability, Independence, and Self-Governance on Trust and Public Acceptance of Uncrewed Air Vehicle Operations

Trust is expected to be a critical construct that drives successful use of advanced air mobility (AAM) technologies. As yet, though, the role of trust in human-autonomy interaction is underexplored. Kaber (2018) argues that autonomy requires the highest level of three independent dimensions -- viability, independence, and self-governance. The present study examined whether trust varies across the three dimensions of autonomy under varying levels of risk. Participants in the high-risk group read a series of vignettes on a drone that delivers medical supplies over a city where the current study was conducted. Participants in the low-risk group read a series of vignettes on a drone that delivers fast food over a fictitious city. Each vignette described a drone that is either autonomous (i.e., possesses all dimensions) or automated (i.e., one of the dimensions is compromised). Results imply that the three dimensions of autonomy do not equally influence human-technology trust and behavior.

Advanced Air Mobility↗

Designing for Advanced Aerial Mobility: Human-Autonomy Teaming and In-Time System-Wide Safety Assurance

The continued growth of aviation shall require new innovative technologies and operational concepts to meet the ever-increasing demands on air transportation. The NASA Advanced Air Mobility (AAM) project focuses on emerging aviation markets, such as Urban Air Mobility (UAM). UAM is defined as “...a safe and efficient system for air passenger and cargo transportation within an urban area. It is inclusive of small package delivery and other urban unmanned aerial system services and supports a mix of onboard/ground-piloted and increasingly autonomous operations” ([1]). The AAM project emphasizes technology development and validating system-level concepts and solutions in coordination with other NASA Aeronautics Research Mission Directorate (ARMD) projects to enable UAM metro- and micro-plex vertiport and airspace concepts of operations. The NASA AAM research portfolio includes the concepts of Remote Supervisor-in-Command (RSC) and Fleet and Airspace Manager (FAM) as possible human roles for consumer fleet providers. NASA research in RSC is focused on development of guidelines and standards for remote pilots/operators passively and actively controlling a large fleet of autonomous aircraft. For FAM, flight and ground system concepts and technologies to enable high density homogeneous operations at increased scale from vertiport(s), and coordination with other humans in the systems (e.g., UAM urban airspace manager, Air Traffic Control) are key research areas. The envisioned UAM operations are posited to require autonomous systems to enable functions ranging from fleet and resource management to vehicle control. Although automation has become increasingly sophisticated and ubiquitous in civil aviation, autonomy represents a significant evolution in automation, which has generally been limited in functional scope and capability. As autonomy takes on increasing responsibilities, humans and machines will be required to work together in new and different ways [2], rather than traditional design approaches focused on how machines (i.e., autonomy) can do the work of people. The emerging field of human-autonomy teaming (HAT) represents a comprehensive and prioritized research-driven approach to enable the success of future emerging aviation market applications through capabilities and principles that facilitate humans and machine working and thinking better together. The NASA Transformational Tools and Technologies (TTT) Autonomous System (AS) Sub-project was created to assist with the transition into higher levels of autonomy to enable new modes of air transportation, such as UAM. TTT-AS has identified HAT as a key research need to enable UAM while maintaining today’s ultra-safe aviation system safety levels. The latter challenge has been taken up by the NASA System-Wide Safety (SWS) Project, which recognizes that aviation safety, as it evolves, shall require new ways of thinking about safety to include integration of a wide-range of existing and new safety systems and practices, enhanced tools and technologies, increased access to data and data fusion, improved data analysis capabilities, enhanced in-time risk monitoring and detection, hazard prioritization and mitigation, safety assurance decision-support, and in-time integrated system analytics [3].The operational concept of UAM represents a variety of work that has been termed, “work-as-imagined” to characterize the idea that how people think that work is done and how work is actually done are often not the same [4]. To ensure design success and system safety, looking at “work-as-done” provides a comparative approach toward UAM concept and technology design through examination of corresponding analogs found today in aviation (e.g., on-demand operations) and other transportation domains (e.g., port operations). The paper shall discuss various alternative applications with specific focus on airline operation center (AOC) operations, and unmanned aerial system (UAS) command-and-control to inform scaled-versions of FAM and RSC, respectively, and with consideration of the national airspace system contextual environment. The tenets and principles of the HAT field and current NASA research efforts under the TTT-AS sub-project shall also be described. Finally, the SWS sub-project efforts to develop In-Time System-Wide Safety Assurance (ISSA) and In-Time Safety Management Systems (IASMS) are discussed in terms of how “in-time” safety assurance may be conceptualized for the on-demand mobility air taxi “work-as-imagined” operational concept [5]. As part of this effort, concepts from the emerging field of resilience engineering, are being studied. Traditional approaches to aviation safety have focused on what can go wrong and how to prevent it. Another approach to thinking about system safety should reflect not only “avoiding things that go wrong” (protective safety) but also “ensuring that things go right” (productive safety), that enables a system to exhibit the resilient performance [6] necessary for the success of the future aviation system emerging concepts of operations. The paper shall describe efforts focused on how productive safety and resilience may enable a more complete approach to system safety thinking and design of ISSA and IASMS for UAM. Future directions and research needs shall also be discussed.

resilience↗

Separation Assurance in Urban Air Mobility Systems Using Shared Scheduling Protocols

Ensuring safe separation between aircraft is a critical challenge in air traffic management, particularly in urban air mobility (UAM) environments where high traffic density and low altitudes require precise control. In these environments, conflicts often arise at the intersections of flight corridors, posing significant risks. We propose a tactical separation approach leveraging shared scheduling protocols, originally designed for Ethernet networks and operating systems, to coordinate access to these intersections. Using a decentralized Markov decision process framework, the proposed approach enables aircraft to autonomously adjust their speed and timing as they navigate these critical areas, maintaining safe separation without a central controller. We evaluate the effectiveness of this approach in simulated UAM scenarios, demonstrating its ability to reduce separation violations to zero while acknowledging trade-offs in flight times as traffic density increases. Additionally, we explore the impact of non-compliant aircraft, showing that while shared scheduling protocols can no longer guarantee safe separation, they still provide significant improvements over systems without scheduling protocols.

Separation Assurance↗

AAM and ATM-X Flight Activities and Demonstrations

The presentation will provide an overview of the Advanced Air Mobility efforts that are currently underway at NASA across a number of projects. The focus of the presentation is on key partnerships with industry and the associated flight tests that have been conducted under the Pathfinding for Airspace with Autonomous Vehicles subproejct and the National Campaign.

AAm↗

Initial Performance Evaluation of Flight Path Management Onboard Automation

Significant developments in automation are necessary to achieve safe and efficient operations in advanced aerial mobility related concepts. Urban Air Mobility (UAM) is rapidly growing, emerging field that poses a challenging use case with a tighter scale of operations compared to the traditional commercial transport paradigm. A large part of the challenge is the uncharted territory; as of this paper, no set of operational standards or guidelines for UAM operations have been established and automated en route operations for UAM level 4 (UML-4) have not been studied. Flight Path Management (FPM) automation provides a set of capabilities that are critical toward enabling airborne vehicles to achieve mission success while maintaining operational safety. An initial performance evaluation of FPM automation was conducted using a UAM-adapted version of the Autonomous Operations Planner (AOP), an onboard trajectory management capability developed over years of research targeting commercial transport operations, as its reference implementation. This paper describes the evaluation, including the approach and methodology for simulating FPM automation in UML-4, key results, future work, and conclusions.

flight path management↗

Share the Sky: Concepts and Technologies That Will Shape Future Airspace Use

The airspace challenge for the United States is to protect national sovereignty and ensure the safety and security of those on the ground and in the air, while at the same time ensuring the efficiency of flight, reducing the costs involved, protecting the environment, and protecting the freedom of access to the airspace. Many visions of the future NAS hold a relatively near-term perspective, focusing on existing uses of the airspace and assuming that new uses will make up a small fraction of total use. In the longer term, the skies will be filled with diverse and amazing new air vehicles filling our societal needs. Anticipated new vehicles include autonomous air vehicles acting both independently and in coordinated groups, unpiloted cargo carriers, and large numbers of personal air vehicles and small-scale point-to-point transports. These vehicles will enable new capabilities that have the potential to increase societal mobility, transport freight at lower cost and with lower environmental impact, improve the study of the Earth s atmosphere and ecosystem, and increase societal safety and security by improving or drastically lowering the cost of critical services such as firefighting, emergency medical evacuation, search and rescue, border and neighborhood surveillance, and the inspection of our infrastructure. To ensure that uses of the airspace can continue to grow for the benefit of all, a new paradigm for operations is needed: equitably and safely sharing the airspace. This paper is an examination of such a vision, concentrating on the operations of all types of air vehicles and future uses of the National Airspace. Attributes of a long-term future airspace system are provided, emerging operations technologies are described, and initial steps in research and development are recommended.

Ballin, Mark G.↗

FT-01: Autonomous Helicopter Flight Testing Over Long Island Sound Special Session - Hazard Perception and Avoidance Tech Area

This presentation is included as part of a panel reporting on the Integration of Automated Systems (IAS) flight test series. The IAS series concluded in October 2023 and was conducted under NASA’s Advanced Air Mobility project and in partnership with Sikorsky and the Defense Advanced Research Projects Agency (DARPA). The flight test effort included two crewed rotorcraft platforms. The first, a modified S-76B helicopter, served as the “ownship” for the duration of the flight test. The second vehicle, a modified S-70, served as the intruder aircraft. One Sikorsky pilot and one NASA test pilot was onboard each aircraft for every test point, with the NASA test pilot responsible for interacting with the research systems under test. This portion of the panel presentation focuses on the results of the flight test that assessed the Federal Aviation Administration’s (FAA) next-generation collision avoidance system, the Airborne Collision Avoidance System X for Rotorcraft (ACAS Xr). The two configurations available within ACAS Xr – the Collision Avoidance System (CAS) configuration and the Detect and Avoid (DAA) configuration – were flown with an onboard pilot under Visual Flight Rules in controlled airspace over the Long Island Sound (Connecticut, USA). A total of 33 flight test cards were flown with ACAS Xr active. Results showed that the ACAS Xr alerting and guidance was largely effective and rated positively by the NASA test pilots, exemplified by zero instances of the pilots overriding an ACAS Xr Resolution Advisory (RA). Key areas of improvement, however, were noted, particularly with regards to the lack of an aural alert indicating a need to accelerate when receiving an RA at low speed and the occurrence of multiple RAs that the pilots found to be unacceptable.

detect and avoid↗

Initial Performance Evaluation of Flight Path Management Onboard Automation

Significant developments in automation are necessary to achieve safe and efficient operations in advanced aerial mobility related concepts. Urban Air Mobility (UAM) is rapidly growing, emerging field that poses a challenging use case with a tighter scale of operations compared to the traditional commercial transport paradigm. A large part of the challenge is the uncharted territory; as of this paper, no set of operational standards or guidelines for UAM operations have been established and automated en route operations for UAM level 4 (UML-4) have not been studied. Flight Path Management (FPM) automation provides a set of capabilities that are critical toward enabling airborne vehicles to achieve mission success while maintaining operational safety. An initial performance evaluation of FPM automation was conducted using a UAM-adapted version of the Autonomous Operations Planner (AOP), an onboard trajectory management capability developed over years of research targeting commercial transport operations, as its reference implementation. This paper describes the evaluation, including the approach and methodology for simulating FPM automation in UML-4, key results, future work, and conclusions.

flight path management↗

Exploring Concepts of Operations for On-Demand Passenger Air Transportation

In recent years, a surge of interest in "flying cars" for city commutes has led to rapid development of new technologies to help make them and similar on-demand mobility platforms a reality. To this end, this paper provides analyses of the stakeholders involved, their proposed operational concepts, and the hazards and regulations that must be addressed. Three system architectures emerged from the analyses, ranging from conventional air taxi to revolutionary fully autonomous aircraft operations, each with vehicle safety functions allocated differently between humans and machines. Advancements for enabling technologies such as distributed electric propulsion and artificial intelligence have had major investments and initial experimental success, but may be some years away from being deployed for on-demand passenger air transportation at scale.

Nneji, Victoria Chibuogu↗

Autonomy Operating System for UAVs: Pilot-in-a-Box

The Autonomy Operating System (AOS) is an open flight software platform with Artificial Intelligence for smart UAVs. It is built to be extendable with new apps, similar to smartphones, to enable an expanding set of missions and capabilities. AOS has as its foundations NASAs core flight executive and core flight software (cFEcFS). Pilot-in-a-Box (PIB) is an expanding collection of interacting AOS apps that provide the knowledge and intelligence onboard a UAV to safely and autonomously fly in the National Air Space, eventually without a remote human ground crew. Longer-term, the goal of PIB is to provide the capability for pilotless air vehicles such as air taxis that will be key for new transportation concepts such as mobility-on-demand. PIB provides the procedural knowledge, situational awareness, and anticipatory planning (thinking ahead of the plane) that comprises pilot competencies. These competencies together with a natural language interface will enable Pilot-in-a-Box to dialogue directly with Air Traffic Management from takeoff through landing. This paper describes the overall AOS architecture, Artificial Intelligence reasoning engines, Pilot-in-a-box competencies, and selected experimental flight tests to date.

Lowry, Michael↗

NASA's Aeronautics Vision

Six long-term technology focus areas are: 1. Environmentally Friendly, Clean Burning Engines. Focus: Develop innovative technologies to enable intelligent turbine engines that significantly reduce harmful emissions while maintaining high performance and increasing reliability. 2. New Aircraft Energy Sources and Management. Focus: Discover new energy sources and intelligent management techniques directed towards zero emissions and enable new vehicle concepts for public mobility and new science missions. 3. Quiet Aircraft for Community Friendly Service. Focus: Develop and integrate noise reduction technology to enable unrestricted air transportation service to all communities. 4. Aerodynamic Performance for Fuel Efficiency. Focus: Improve aerodynamic efficiency,structures and materials technologies, and design tools and methodologies to reduce fuel burn and minimize environmental impact and enable new vehicle concepts and capabilities for public mobility and new science missions. 5. Aircraft Weight Reduction and Community Access. Focus: Develop ultralight smart materials and structures, aerodynamic concepts, and lightweight subsystems to increase vehicle efficiency, leading to high altitude long endurance vehicles, planetary aircraft, advanced vertical and short takeoff and landing vehicles and beyond. 6. Smart Aircraft and Autonomous Control. Focus: Enable aircraft to fly with reduced or no human intervention, to optimize flight over multiple regimes, and to provide maintenance on demand towards the goal of a feeling, seeing, sensing, sentient air vehicle.

Tenney, Darrel R.↗

Intelligent Change Detection System: Autonomous Intelligent Machine Agent Model Development

NASA’s significant role in facilitating the harmonious integration of unmanned aircraft systems (UAS), with other aerial vehicles operating in the National Airspace System (NAS), has revealed a need for more advanced technological tools than are being utilized currently. This technology would lend itself to significantly assisting Direct-Action Aviation Personnel (DAAP) with the ingress and egress of UAS operations within the NAS. Providing research findings that would reduce technical barriers, associated with UAS-NAS integration, has been a persistent effort by both NASA and the FAA. One such research effort, pursued by NASA’s Transformative Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) project, is the development of an autonomous intelligent machine (AIM) agent that would aid DAAP functioning as implemented in remote ground control stations (RGCS). This evolution of the “human-machine” symbiosis, within the aviation environment, is necessary for many reasons. For example, there are projections of large increases to the 864,000 registered UAS and 45,000 aviation operations taking place in the NAS each day. With a data output range from 1 to 20 terabytes per flight or each aerial vehicle, which is projected to have proportional rate increase to that of registered UASs. It is evident, that due to the projected increase of UASs and their generated data, the human-agent’s data managing capabilities will be quickly overwhelmed by the enormous amounts of data emanating in the NAS. The research efforts presented in this paper puts forward results from the development, assessment, and verification of a previously conceptualized AIM-Agent that combats actionable-data (information) errors resulting from the visual perception phenomenon known as “change blindness” (CB). CB has been identified as one of the main culprits of information erroring encountered within the ground control station operator (GCSO) community.

Change Blindness↗

Evolving Relationship between Humans and Machines

Traditional design typically consists of a master-servant relationship between humans and machines where the human directly controls what the machine will do and when it will do it through an interface. The current archetypical path encompasses moving from informational displays, where the human directly controls the machine based on information displayed, to automation where the human still directs the machine that then caries out the request using predefined set of instructions. Rapid pace of technological advancement makes it possible now, or in a near future, for machines to reach a level of intelligence that enables for systems to execute tasks/missions without predefined specific instructions; thus attaining a status of non- human autonomous agents. Now the course of human-machine interface technology changes from an information system to automation to an autonomous agent—essentially moving from a master-servant relationship to teammates. This paper discusses these changing relationships and challenges associated with progressing from a master-servant relationship with technology to more of an equal teammate. Examples of this progression includes current work encompassing rotorcraft noise minimization for urban air mobility.

Trujillo, Anna C.↗