Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Autonomous research”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

Asset Analysis and Operational Concepts for Separation Assurance Flight Testing at Dryden Flight Research Center

A preliminary survey of existing separation assurance and collision avoidance advancements, technologies, and efforts has been conducted in order to develop a concept of operations for flight testing autonomous separation assurance at Dryden Flight Research Center. This effort was part of the Unmanned Aerial Systems in the National Airspace System project. The survey focused primarily on separation assurance projects validated through flight testing (including lessons learned), however current forays into the field were also examined. Comparisons between current Dryden flight and range assets were conducted using House of Quality matrices in order to allow project management to make determinations regarding asset utilization for future flight tests. This was conducted in order to establish a body of knowledge of the current collision avoidance landscape, and thus focus Dryden s efforts more effectively towards the providing of assets and test ranges for future flight testing within this research field.

Costa, Guillermo J.↗

New Concepts and Perspectives on Micro-Rotorcraft and Small Autonomous Rotary-Wing Vehicles

A key part of the strategic vision for rotorcraft research as identified by senior technologists within the Army/NASA Rotorcraft Division at NASA Ames Research Center is the development and use of small autonomous rotorcraft. Small autonomous rotorcraft are defined for the purposes of this paper to be a class of vehicles that range in size from rotary-wing micro air vehicles (MAVs) to larger, more conventionally sized, rotorcraft uninhabited aerial vehicles (UAVs) - i.e. vehicle gross weights ranging from hundreds of grams to thousands of kilograms. The development of small autonomous rotorcraft represents both a technology challenge and a potential new vehicle class that will have substantial societal impact for: national security, personal transport, planetary science, and public service.

Young, Larry A.↗

Autonomous experimentation systems for materials development: A community perspective

Solutions to many of the world's problems depend upon materials research and development. However, advanced materials can take decades to discover and decades more to fully deploy. Humans and robots have begun to partner to advance science and technology orders of magnitude faster than humans do today through the development and exploitation of closed-loop, autonomous experimentation systems. This review discusses the specific challenges and opportunities related to materials discovery and development that will emerge from this new paradigm. Our perspective incorporates input from stakeholders in academia, industry, government laboratories, and funding agencies. We outline the current status, barriers, and needed investments, culminating with a vision for the path forward. We intend the article to spark interest in this emerging research area and to motivate potential practitioners by illustrating early successes. We also aspire to encourage a creative reimagining of the next generation of materials science infrastructure. To this end, we frame future investments in materials science and technology, hardware and software infrastructure, artificial intelligence and autonomy methods, and critical workforce development for autonomous research.

36 MATERIALS SCIENCE↗

Flame stability analysis of flame spray pyrolysis by artificial intelligence

Flame spray pyrolysis (FSP) is a process used to synthesize nanoparticles through the combustion of an atomized precursor solution; this process has applications in catalysts, battery materials, and pigments. Current limitations revolve around understanding how to consistently achieve a stable flame and the reliable production of nanoparticles. Machine learning and artificial intelligence algorithms that detect unstable flame conditions in real time may be a means of streamlining the synthesis process and improving FSP efficiency. In this study, the FSP flame stability is first quantified by analyzing the brightness of the flame's anchor point. This analysis is then used to label data for both unsupervised and supervised machine learning approaches. The unsupervised learning approach allows for autonomous labeling and classification of new data by representing data in a reduced dimensional space and identifying combinations of features that most effectively cluster it. The supervised learning approach, on the other hand, requires human labeling of training and test data but is able to classify multiple objects of interest (such as the burner and pilot flames) within the video feed. The accuracy of each of these techniques is compared against the evaluations of human experts. Both the unsupervised and supervised approaches can track and classify FSP flame conditions in real time to alert users of unstable flame conditions. This research has the potential to autonomously track and manage flame spray pyrolysis as well as other flame technologies by monitoring and classifying the flame stability.

42 ENGINEERING↗

Bioinformatics for Exploration

For the purpose of this paper, bioinformatics is defined as the application of computer technology to the management of biological information. It can be thought of as the science of developing computer databases and algorithms to facilitate and expedite biological research. This is a crosscutting capability that supports nearly all human health areas ranging from computational modeling, to pharmacodynamics research projects, to decision support systems within autonomous medical care. Bioinformatics serves to increase the efficiency and effectiveness of the life sciences research program. It provides data, information, and knowledge capture which further supports management of the bioastronautics research roadmap - identifying gaps that still remain and enabling the determination of which risks have been addressed.

Johnson, Kathy A.↗

Simulating Microwave and Radar Signals in Severe Weather Conditions

The development of radiative transfer simulators for radar and microwave signals, spanning a range of frequencies from 10 to 800 GHz, is paramount for enhancing weather forecasting accuracy, particularly for severe weather events. These tools facilitate the assimilation of microwave and radar observations into numerical weather prediction models, thereby improving accuracy of weather forecasts. Additionally, they directly simulate radar signals crucial for autonomous vehicle operation, with frequencies commonly used in radar systems such as 24, 74, 77, and 79 GHz. However, these frequencies are susceptible to weather phenomena like severe rain and snow, which can significantly impact vehicle safety and performance. These simulation tools, including radiative transfer simulators, serve a dual purpose. Firstly, they enhance forecasts for severe weather events, contributing to autonomous vehicle safety by providing early warnings and risk assessments. Secondly, they enable the direct simulation of radar signals in autonomous vehicle driving systems, allowing researchers and engineers to evaluate radar system performance under various weather conditions. In addition to the radar signal simulator, this abstract discusses the incorporation of advanced scattering properties developed using the discrete dipole approximation (DDA). The DDA technique enhances scattering calculations for frozen hydrometeors at microwave frequencies, thereby improving the accuracy of radar signal simulations and enabling more accurate assessments of radar system performance in adverse weather conditions. In summary, this abstract explores the development and utilization of comprehensive simulation tools, emphasizing their significance in simulating microwave and radar signals and improving weather forecasts. Special attention is given to the simulation of radar signals at critical frequencies for autonomous vehicle sensing and navigation, addressing challenges posed by severe weather phenomena and their effects on signal propagation and detection

Isaac Moradi↗

Microencapsulation Technologies for Corrosion Protective Coating Applications

Microencapsulation technologies for functional smart Coatings for autonomous corrosion control have been a research area of strong emphasis during the last decade. This work concerns the development of pH sensitive micro-containers (microparticles and microcapsules) for autonomous corrosion control. This paper presents an overview of the state-of-the-art in the field of microencapsulation for corrosion control applications, as well as the technical details of the pH sensitive microcontainer approach, such as selection criteria for corrosion indicators and corrosion inhibitors; the development and optimization of encapsulation methods; function evaluation before and after incorporation of the microcontainers into coatings; and further optimization to improve coating compatibility and performance.

Microencapsulation↗

Next Generation Remote Agent Planner

In May 1999, as part of a unique technology validation experiment onboard the Deep Space One spacecraft, the Remote Agent became the first complete autonomous spacecraft control architecture to run as flight software onboard an active spacecraft. As one of the three components of the architecture, the Remote Agent Planner had the task of laying out the course of action to be taken, which included activities such as turning, thrusting, data gathering, and communicating. Building on the successful approach developed for the Remote Agent Planner, the Next Generation Remote Agent Planner is a completely redesigned and reimplemented version of the planner. The new system provides all the key capabilities of the original planner, while adding functionality, improving performance and providing a modular and extendible implementation. The goal of this ongoing project is to develop a system that provides both a basis for future applications and a framework for further research in the area of autonomous planning for spacecraft. In this article, we present an introductory overview of the Next Generation Remote Agent Planner. We present a new and simplified definition of the planning problem, describe the basics of the planning process, lay out the new system design and examine the functionality of the core reasoning module.

Jonsson, Ari K.↗

Telerobotics: Research needs for evolving space stations

It is argued that triplicate planning for telerobotics applicable to space stations is needed. It is important to carry out research to accomplish tasks: (1) with man alone (such as extra-vehicular activities), (2) with autonomous robots, and (3) with telerobotics. The research necessary to carry out these approaches is compared and contrasted in order to clarify present problems.

Stark, L.↗

Autonomous star identification for spacecraft attitude control

Research is being conducted to enhance the Advanced Star and Target Reference Optical Scanner (ASTROS I) so that it will be able to automatically track a star and recognize the star's pointing position. Previously developed field identification algorithms, coded on a flight-scale computer, are linked to a breadboard ASTROS star tracker to calculate pointing vectors in real time. A simple graph-searching algorithm was used in an initial study to find stellar positions based on pattern recognition. Results from this study and plans for further development are presented.

Rappaport, Barry↗

Robotic Manipulation Testbeds with HPSC

Interoperability and scalability of robotic manipulators will be key to develop and sustain a lunar surface and cislunar ecosystem. From in-space servicing, assembly, and manufacturing (ISAM) to logistics, maintenance, and science operations, robotic manipulation is a critical NASA capability need and the demand for high-performance spaceflight computing will only rise as robotic tasks become more autonomous. With increased complexity, testbeds for research, feasibility studies, and technology demonstrations will be essential. The Dexterous Robotics Team at NASA Johnson Space Center has established multiple robotic manipulation testbeds taking a supervised autonomous remote operations approach and plans to infuse High-Performance Spaceflight Computing (HPSC) to emulate the flight environment and close the gap between space technology development and flight operations.

Alex Sowell↗

Towards A Theory of Autonomous Reconstitution of Compromised Cyber-Systems

The ability to maintain mission-critical operations in cyber-systems in the face of disruptions is critical. Faults in cyber systems can come from accidental sources (e.g., natural failure of a component) or deliberate sources (e.g., an intelligent adversary). Natural and intentional manipulation of data, computing, or coordination are the most impactful ways that an attacker can prevent an infrastructure from realizing its mission goals. Under these conditions, the ability to reconstitute critical infrastructure becomes important. Specifically, the question is: Given an intelligent adversary, how can cyber systems respond to keep critical infrastructure operational? In cyber systems, the distributed nature of the system poses serious difficulties in maintaining operations, in part due to the fact that a centralized command and control apparatus is unlikely to provide a robust framework for resilience. Resilience in cyber-systems, in general, has several components, and requires the ability to anticipate and withstand attacks or faults, as well as recover from faults and evolve the system to improve future resilience. The recovery effort (and any subsequent evolution) may require significant reconfiguration of the system (at all levels – hardware, software, services, permissions, etc.) if the system is to be made resilient to further attack or faults. This is especially important in the case of ongoing attacks, where reconfiguration decisions must be taken with care to avoid further compromising the system while maintaining continuity of operations. Collectively, we will label this recovery and evolution process as “reconstitution”. Currently, reconstitution is performed manually, generally after-the-fact, and usually consists of either standing up redundant systems, check-points (rolling back the configuration to a “clean” state), or re-creating the system using “gold-standard” copies. For enterprise systems, such reconstitution may be performed either directly on hardware, or using virtual machines. A significant challenge within this context is the ability to verify that the reconstitution is performed in a manner that renders the cyber-system resilient to ongoing and future attacks or faults. Fundamentally, the need is to determine optimal configuration of the cyber system when a fault is determined to be present. While existing theories for fault tolerance (for example, Byzantine fault tolerance) can guarantee resilience under certain conditions, in practice, these theories can break down in the face of an intelligent adversary. Further, it is difficult, in a dynamically evolving environment, to determine whether the necessary conditions for resilience have been met, resulting in difficulties in achieving resilient operation. In addition, existing theories do not sufficiently take into account the cost for attack and defense (the adversary is generally assumed to have infinite resources and time), hierarchy of importance (all network resources are assumed to be equally important), and the dynamic nature of some attacks (i.e., as the attack evolves, can resilience be maintained?). Alternative approaches to resilience based on a centralized command and control structure suffer from a single-point-failure. This paper presents preliminary research towards concepts for effective autonomous reconstitution of compromised cyber systems. We describe a mathematical framework as a first step towards a theoretical basis for autonomous reconstitution in dynamic cyber-system environments. We then propose formulating autonomous reconstitution as an optimization problem and describe some of the challenges associated with this formulation. This is followed by a brief discussion on potential solutions to these challenges.

asymmetric resilience↗

Autonomous Ocean World Exploration: Advancement of a Software Testbed

The search for life signs and potentially habitable bodies in our solar system and beyond is one of NASA’s top priorities. The prime destinations for such exploration are bodies containing liquid water, such as Jupiter’s moon Europa and Saturn’s moon Enceladus. Initial missions to these “ocean worlds” will be robotic, and because of long communication lags and blackouts, harsh environments, and limited battery life, a high degree of onboard autonomy will be required. To this end NASA has developed the Ocean Worlds Autonomy Testbed for Exploration, Research, and Simulation (OceanWATERS), a software testbed for surface mission autonomy. Under grants from NASA’s Autonomous Robotics Research for Ocean Worlds (ARROW) and Concepts for Ocean worlds Life Detection Technology (COLDTech) programs, collectively 6 research teams at universities and companies across the United States have developed autonomy solutions using OceanWATERS, tackling a variety of surface mission challenges and employing state-of-the-art AI-based solutions. This paper provides a self-contained high-level description of OceanWATERS while detailing enhancements made since its 2020 release. It provides a high-level summary of the projects undertaken by participants in the ARROW and COLDTech programs and how these efforts have helped shape OceanWATERS. Finally, potential future work and directions for the testbed are listed.

K Michael Dalal↗

Diagnosing faults in autonomous robot plan execution

A major requirement for an autonomous robot is the capability to diagnose faults during plan execution in an uncertain environment. Many diagnostic researches concentrate only on hardware failures within an autonomous robot. Taking a different approach, the implementation of a Telerobot Diagnostic System that addresses, in addition to the hardware failures, failures caused by unexpected event changes in the environment or failures due to plan errors, is described. One feature of the system is the utilization of task-plan knowledge and context information to deduce fault symptoms. This forward deduction provides valuable information on past activities and the current expectations of a robotic event, both of which can guide the plan-execution inference process. The inference process adopts a model-based technique to recreate the plan-execution process and to confirm fault-source hypotheses. This technique allows the system to diagnose multiple faults due to either unexpected plan failures or hardware errors. This research initiates a major effort to investigate relationships between hardware faults and plan errors, relationships which were not addressed in the past. The results of this research will provide a clear understanding of how to generate a better task planner for an autonomous robot and how to recover the robot from faults in a critical environment.

Lam, Raymond K.↗

Diagnosing faults in autonomous robot plan execution

A major requirement for an autonomous robot is the capability to diagnose faults during plan execution in an uncertain environment. Many diagnostic researches concentrate only on hardware failures within an autonomous robot. Taking a different approach, the implementation of a Telerobot Diagnostic System that addresses, in addition to the hardware failures, failures caused by unexpected event changes in the environment or failures due to plan errors, is described. One feature of the system is the utilization of task-plan knowledge and context information to deduce fault symptoms. This forward deduction provides valuable information on past activities and the current expectations of a robotic event, both of which can guide the plan-execution inference process. The inference process adopts a model-based technique to recreate the plan-execution process and to confirm fault-source hypotheses. This technique allows the system to diagnose multiple faults due to either unexpected plan failures or hardware errors. This research initiates a major effort to investigate relationships between hardware faults and plan errors, relationships which were not addressed in the past. The results of this research will provide a clear understanding of how to generate a better task planner for an autonomous robot and how to recover the robot from faults in a critical environment.

Lam, Raymond K.↗

Influence of weather on gobbling activity of male wild turkeys

Gobbling activity of Eastern wild turkeys (Meleagris gallopavo silvestris; hereafter, turkeys) has been widely studied, focusing on drivers of daily variation. Weather variables are widely believed to influence gobbling activity, but results across studies are contradictory and often equivocal, leading to uncertainty in the relative contribution of weather variables to daily fluctuations in gobbling activity. Previous works relied on road-based auditory surveys to collect gobbling data, which limits data consistency, duration, and quantity due to logistical difficulties associated with human observers and restricted sampling frames. Development of new methods using autonomous recording units (ARUs) allows researchers to collect continuous data in more locations for longer periods of time, providing the opportunity to delve into factors influencing daily gobbling activity. We used ARUs from 1 March to 31 May to detail gobbling activity across multiple study sites in the southeastern United States during 2014–2018. We used state-space modeling to investigate the effects of weather variables on daily gobbling activity. Our findings suggest rainfall, greater wind speeds, and greater temperatures negatively affected gobbling activity, whereas increasing barometric pressure positively affected gobbling activity. Therefore, when using daily gobbling activity to make inferences relative to gobbling chronology, reproductive phenology, and hunting season frameworks, stakeholders should recognize and consider the potential influences of extended periods of inclement weather.

60 APPLIED LIFE SCIENCES↗

Systems autonomy

Information on systems autonomy is given in viewgraph form. Information is given on space systems integration, intelligent autonomous systems, automated systems for in-flight mission operations, the Systems Autonomy Demonstration Project on the Space Station Thermal Control System, the architecture of an autonomous intelligent system, artificial intelligence research issues, machine learning, and real-time image processing.

Lum, Henry, Jr.↗

The Space Station Module Power Management and Distribution automation test bed

The Space Station Module Power Management And Distribution (SSM/PMAD) automation test bed project was begun at NASA/Marshall Space Flight Center (MSFC) in the mid-1980s to develop an autonomous, user-supportive power management and distribution test bed simulating the Space Station Freedom Hab/Lab modules. As the test bed has matured, many new technologies and projects have been added. The author focuses on three primary areas. The first area is the overall accomplishments of the test bed itself. These include a much-improved user interface, a more efficient expert system scheduler, improved communication among the three expert systems, and initial work on adding intermediate levels of autonomy. The second area is the addition of a more realistic power source to the SSM/PMAD test bed; this project is called the Large Autonomous Spacecraft Electrical Power System (LASEPS). The third area is the completion of a virtual link between the SSM/PMAD test bed at MSFC and the Autonomous Power Expert at Lewis Research Center.

Lollar, Louis F.↗