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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Overview of Challenges to Integrating Remotely-Piloted Operations into the National Airspace System

An oral presentation summarizing key challenges to integrating remotely-piloted operations into the National Airspace System. The presentation provides an overview of NASA's Pathfinding for an Airspace with Autonomous Vehicles sub-project, recent research activities focused on enabling autonomous cargo delivery, and some of the challenges that have been learned so far from these activities.

Husni Idris↗
NASA NTRS2004

Daytime Water Detection by Fusing Multiple Cues for Autonomous Off-Road Navigation

Detecting water hazards is a significant challenge to unmanned ground vehicle autonomous off-road navigation. This paper focuses on detecting the presence of water during the daytime using color cameras. A multi-cue approach is taken. Evidence of the presence of water is generated from color, texture, and the detection of reflections in stereo range data. A rule base for fusing water cues was developed by evaluating detection results from an extensive archive of data collection imagery containing water. This software has been implemented into a run-time passive perception subsystem and tested thus far under Linux on a Pentium based processor.

COMPONENT REPORTS↗
NASA NTRS2001

Human-Vehicle Interface for Semi-Autonomous Operation of Uninhabited Aero Vehicles

The robustness of autonomous robotic systems to unanticipated circumstances is typically insufficient for use in the field. The many skills of human user often fill this gap in robotic capability. To incorporate the human into the system, a useful interaction between man and machine must exist. This interaction should enable useful communication to be exchanged in a natural way between human and robot on a variety of levels. This report describes the current human-robot interaction for the Stanford HUMMINGBIRD autonomous helicopter. In particular, the report discusses the elements of the system that enable multiple levels of communication. An intelligent system agent manages the different inputs given to the helicopter. An advanced user interface gives the user and helicopter a method for exchanging useful information. Using this human-robot interaction, the HUMMINGBIRD has carried out various autonomous search, tracking, and retrieval missions.

Jones, Henry L.↗
NASA NTRS1989

Telerobotic workstation design aid

Telerobot systems are being developed to support a number of space mission applications. In low earth orbit, telerobots and teleoperated manipulators will be used in shuttle operations and space station construction/maintenance. Free flying telerobotic service vehicles will be used at low and geosynchronous orbital operations. Rovers and autonomous vehicles will be equipped with telerobotic devices in planetary exploration. In all of these systems, human operators will interact with the robot system at varied levels during the scheduled operations. The human operators may be in either orbital or ground-based control systems. To assure integrated system development and maximum utility across these systems, designers must be sensitive to the constraints and capabilities that the human brings to system operation and must be assisted in applying these human factors to system development. The simulation and analysis system is intended to serve the needs of system analysis/designers as an integrated workstation in support of telerobotic design.

Corker, K.↗
NASA NTRS1992

Microrover Operates With Minimal Computation

Small, light, highly mobile robotic vehicles called "microrovers" use sensors and artificial intelligence to perform complicated tasks autonomously. Vehicle navigates, avoids obstacles, and picks up objects using reactive control scheme selected from among few preprogrammed behaviors to respond to environment while executing assigned task. Under development for exploration and mining of other planets. Also useful in firefighting, cleaning up chemical spills, and delivering materials in factories. Reactive control scheme and principle of behavior-description language useful in reducing computational loads in prosthetic limbs and automotive collision-avoidance systems.

Miller, David P.↗
NASA NTRS2016

Design Considerations for Spacecraft Operations During Uncrewed Dormant Phases of Human Exploration Missions

NASA is transforming human spaceflight. The Agency is shifting from an exploration-based program with human activities in low Earth orbit (LEO) and targeted robotic missions in deep space to a more sustainable and integrated pioneering approach. However, pioneering space involves daunting technical challenges of transportation, maintaining health, and enabling crew productivity for long durations in remote, hostile, and alien environments. Subject matter experts from NASA's Human Exploration and Operations Mission Directorate (HEOMD) are currently studying a human exploration campaign that involves deployment of assets for planetary exploration. This study, called the Evolvable Mars Campaign (EMC) study, explores options with solar electric propulsion as a central component of the transportation architecture. This particular in-space transportation option often results in long duration transit to destinations. The EMC study is also investigating deployed human rated systems like landers, habitats, rovers, power systems and ISRU system to the surface of Mars, which also will involve long dormant periods when these systems are staged on the surface. In order to enable the EMC architecture, campaign and element design leads along with system and capability development experts from HEOMD's System Maturation Team (SMT) have identified additional capabilities, systems and operation modes that will sustain these systems especially during these dormant phases of the mission. Dormancy is defined by the absence of crew and relative inactivity of the systems. For EMC missions, dormant periods could range from several months to several years. Two aspects of uncrewed dormant operations are considered herein: (1) the vehicle systems that are placed in a dormant state and (2) the autonomous vehicle systems and robotic capabilities that monitor, maintain, and repair the vehicle and systems. This paper describes the mission stages of dormancy operations, phases of dormant operations, and critical system capabilities that are needed for dormant operations. This paper will compare dormancy operations of past robotic missions to identify lessons that can be applied to planned human exploration missions. Finally, this paper will also identify future work and analysis planned to assess system performance metrics and integrated system operations.

Williams-Byrd, Julie↗
NASA NTRS2023

An MBSE Approach for Developing an Autonomous Rover Platform

The proliferation of increasingly autonomous systems calls for new ways to address how safety is assured. As these systems become more advanced and complex, it becomes more important to model and prototype autonomous functions at the systems level and the functions that assure they are operating safely and as expected. To that effect, researchers at the National Aeronautics and Space Administration (NASA) 's Robust Software Engineering (RSE) group are working on prototyping a Research Autonomous Vehicle, commonly referred to as R-RAV. The R-RAV is an autonomous rover platform designed to act as a case study for assured autonomy research. Moreover, an overarching goal is for the R-RAV to serve as a training ground for other mission projects. In this paper, we will detail how we have used a Model-Based Systems Engineering (MBSE) approach to model a prototype of the R-RAV and test and verify its different functionalities.

MBSE↗
NASA NTRS2019

SAFE50 Reference Design Study for Large-Scale High-Density Low-Altitude UAS Operations in Urban Areas

Enabling safe, routine, and high-density flight operations of small UAS at low-altitude over heavily populated urban centers presents a difficult challenge for emerging UAS Traffic Management (UTM) system concepts. Urban operations by definition involve flight over people, property, and infrastructure. Low-altitude urban environments - such as urban canyons – are one of the most difficult areas for UTM to consider. Mission concepts require routine operations in a cluttered radio-frequency (RF) environment with degraded or denied Global Positioning System (GPS) reception. Flights with any appreciable distance will be beyond visual and communications line-of-sight from ground operators. Timely detection and response to emergencies and onboard failures, which is critical for safe aircraft operation, will be difficult. This work seeks to establish a feasible reference autonomy architecture for autonomous vehicles in an urban UTM system, then verifying and validating this architecture within a complete UTM concept point-design and systems analysis study. In this paper, we present the results from the NASA SAFE50 conceptual design and systems study that investigates the trade-space of urban UTM operations. This advanced conceptual design study develops a feasible, verified, validated point-design solution. The SAFE50 point-design concept places emphasis on advanced, highly-autonomous, and highly-capable vehicles that favors intelligent onboard autonomy over direct human control with today's technologies and operating in today's urban environments. This paper focuses on an general overview of the design study, highlighting decisions made in the architectural solution. This paper will presents a summary of the study, architectures, and requirements. We present an overview of the architecture designs as derived from the top-level UTM system. The point-design has been implemented in both simulation and through flight testing of hardware design prototypes. The results from simulation and flight testing as part of the verification and validation process of the reference design study.

Ippolito, Corey A.↗
NASA NTRS1988

Automated orbital rendezvous considerations

The control of the rendezvous vehicle during proximity operations is considered. It is shown how fuzzy sets can be used for autonomous vehicle control to model the human capability of common sense reasoning. Such models are integrated with expert systems and engineering control systems technology to create a system that performs comparably to a manned system.

Lea, Robert N.↗
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.

unmanned aircraft systems (UAS)↗
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 NTRS2018

SAM 3.0 Workshop Alliance SV Lab

Nissan is building a Seamless Autonomy Mobility (SAM) which is a cloud-based system of artificial intelligence that manages a fleet of autonomous vehicles. It pairs artificial intelligence with human intelligence in order to create a seamless solution that allows autonomous drive to be viable and marketable. They have created a Mobility Manager function which is a laborer who executed human-in-the-loop functions within SAM system. Nissan invited the HAT Lab to discuss NASA's lessons learned on remote operator support and to participate in a workshop discussion of one of their use cases. This presentation covers some of the HAT Lab's work on a human-autonomy teaming Agent and previous Reduced Crew Operations ground station development.

Human-Autonomy Teaming↗
NASA NTRS1993

A parallel implementation of a multisensor feature-based range-estimation method

There are many proposed vision based methods to perform obstacle detection and avoidance for autonomous or semi-autonomous vehicles. All methods, however, will require very high processing rates to achieve real time performance. A system capable of supporting autonomous helicopter navigation will need to extract obstacle information from imagery at rates varying from ten frames per second to thirty or more frames per second depending on the vehicle speed. Such a system will need to sustain billions of operations per second. To reach such high processing rates using current technology, a parallel implementation of the obstacle detection/ranging method is required. This paper describes an efficient and flexible parallel implementation of a multisensor feature-based range-estimation algorithm, targeted for helicopter flight, realized on both a distributed-memory and shared-memory parallel computer.

Suorsa, Raymond E.↗
NASA NTRS1993

A parallel implementation of a multisensor feature-based range-estimation method

There are many proposed vision based methods to perform obstacle detection and avoidance for autonomous or semi-autonomous vehicles. All methods, however, will require very high processing rates to achieve real time performance. A system capable of supporting autonomous helicopter navigation will need to extract obstacle information from imagery at rates varying from ten frames per second to thirty or more frames per second depending on the vehicle speed. Such a system will need to sustain billions of operations per second. To reach such high processing rates using current technology, a parallel implementation of the obstacle detection/ranging method is required. This paper describes an efficient and flexible parallel implementation of a multisensor feature-based range-estimation algorithm, targeted for helicopter flight, realized on both a distributed-memory and shared-memory parallel computer.

Suorsa, Raymond E.↗
NASA NTRS2016

Safe and Autonomous Drones for Urban Flight

Autonomous vehicles are no longer futuristic technology; in fact, there are already cars with self-driving features on the road. Over the next five years, the connected vehicles will disrupt the entire automotive and UAS ecosystems. The industry will undergo fundamental change as semi-autonomous driving and flying emerges, followed by an eventual shift to full autonomy.

Safety↗
DOE OSTI2023

Toward implementing autonomous adaptive data acquisition for scanning hyperspectral imaging of biological systems

Autonomous experimentation is an emerging area of research, primarily related to autonomous vehicles, scientific combinatorial discovery approaches in materials science and drug discovery, and iterative research loops of planning, experimentation, and analysis. However, autonomous approaches developed in these contexts are difficult to apply to high-dimensional mapping technologies, such as scanning hyperspectral imaging of biological systems, due to sample complexity and heterogeneity. We briefly cover the history of adaptive sampling algorithms and surrogate modeling in order to define autonomous adaptive data acquisition as an objective-based, flexible building block for future biological imaging experimentation driven by intelligent infrastructure. We subsequently summarize the recent implementations of autonomous adaptive data acquisition (AADA) for scanning hyperspectral imaging, assess how these address the difficulties of autonomous approaches in hyperspectral imaging, and highlight the AADA design variation from a goal-oriented perspective. Finally, we present a modular AADA architecture that embeds AADA-driven flexible building blocks to address the challenge of time resolution for high-dimensional scanning hyperspectral imaging of nonequilibrium dynamical systems. In our example research-driven experimental design case, we propose an AADA infrastructure for time-resolved, noninvasive, and label-free scanning hyperspectral imaging of living biological systems. This AADA infrastructure can accurately target the correct state of the system for experimental workflows that utilize subsequent expensive, high-information-content analytical techniques.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2024

Concept, Design, & Implementation of a Remote Vehicle Operations Center for Autonomous Missions

The National Aeronautics and Space Administration is supporting research to develop a prototype remote vehicle operations center at Langley Research Center to explore current and future advanced air mobility operations using small unmanned aerial systems vehicles as surrogates for future, larger-scale passenger carrying vehicles. The prototype facility known as the Remote Operations for Autonomous Missions (ROAM) Unmanned Aerial Systems (UAS) Operations Center is being used to explore different roles and responsibilities of remote operators managing multiple autonomous vehicles, with the goal of exploring human-autonomy teaming concepts that enable m:N operations (i.e., m operators managing N vehicles). ROAM has developed into a world-class research, development, and technology (RD&T) environment that can support both the collection of human factors data and the command and control of remote vehicles in beyond visual line of sight conditions. ROAM provides a key capability to enable full end-to-end hardware- and human-in-the-loop simulation testing, connecting with simulated small-UAS and creating a seamless Live-Virtual-Constructive (LVC) environment. This report describes the development of the ROAM UAS Operations Center from concept through design, culminating in the current implementation at NASA’s Langley Research Center.

CERTAIN↗
DOE OSTI2021

Methods and Comparisons Between Computer Vision and Radar Based Vehicle Location

Measuring vehicle locations relative to a driver's vehicle is a critical component in the analysis of driving data from both postanalysis (such as in naturalistic driving studies) or in autonomous vehicle navigation. In this work we describe a method to estimate vehicle positions from a forward-looking video camera using intrinsic camera calibration, estimates of extrinsic parameters, and a convolutional neural network trained to detect and locate vehicles in video data. We compare the measurements we achieve with this method with ground truth and with radar data available from a naturalistic driving study. We identify regions where video is preferred, where radar is preferred, and explore trade-offs between the two methods in regions where the preference is more ambiguous. We describe applications of these measurements for transportation analysis.

Aykac, Deniz↗