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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Promoting Crew Autonomy: Current Advances and Novel Techniques

Since the dawn of the era of human space flight, mission control centers around the world have played an integral role in guiding space travelers toward mission success. In the International Space Station (ISS) program, astronauts and cosmonauts have the benefit of near constant access to the expertise and resources within mission control, as well as lifeboat capability to quickly return to Earth if something were to go wrong. As we move into an era of longer duration missions to more remote locations, rapid and ready access to mission control on earth will no longer be feasible. To prepare for such missions, long duration crews must be prepared to operate more autonomously, and the mission control paradigm that has been successfully employed for decades must be re-examined. The team at NASA's Payload Operations and Integration Center (POIC) in Huntsville, Alabama is playing an integral role in the development of concepts for a more autonomous long duration crew of the future via research on the ISS.

Harris, Samantha↗
NASA NTRS2015

Safety Related Considerations in Autonomy

In this talk I will describe NASA strategy and research efforts to provide safety assurance for increasingly autonomous systems used in aviation. In the near future, autonomy will play an important role in civil aviation, and its applications will range from vehicles and platforms (UAVs, transport-class, including supersonic to hypersonic, aircraft) to airspace operations, or health management systems. This infusion of autonomy is driven by a need for optimizing airspace operations to accommodate increasing traffic density (e.g., adaptive trajectory-based operations, autonomous tugs, close parallel runways, and dynamic separation assurance), reducing operation costs to ensure that US operators can compete with emergent countries, and enabling new business models (e.g., fire fighting, UAS-based package delivery and precise aerial photography). In essence virtually every component of the National Airspace System will become increasingly autonomous. Yet we need to do so in a safe manner and have techniques and processes in place to ensure the safety of the public. This talk describes NASA plans to address this problem

Air Traffic Management↗
NASA NTRS2016

Intelligent (Autonomous) Power Controller Development for Human Deep Space Exploration

As NASAs Evolvable Mars Campaign and other exploration initiatives continue to mature they have identified the need for more autonomous operations of the power system. For current human space operations such as the International Space Station, the paradigm is to perform the planning, operation and fault diagnosis from the ground. However, the dual problems of communication lag as well as limited communication bandwidth beyond GEO synchronous orbit, underscore the need to change the operation methodology for human operation in deep space. To address this need, for the past several years the Glenn Research Center has had an effort to develop an autonomous power controller for human deep space vehicles. This presentation discusses the present roadmap for deep space exploration along with a description of conceptual power system architecture for exploration modules. It then contrasts the present ground centric control and management architecture with limited autonomy on-board the spacecraft with an advanced autonomous power control system that features ground based monitoring with a spacecraft mission manager with autonomous control of all core systems, including power. It then presents a functional breakdown of the autonomous power control system and examines its operation in both normal and fault modes. Finally, it discusses progress made in the development of a real-time power system model and how it is being used to evaluate the performance of the controller and well as using it for verification of the overall operation.

Power Systems↗
NASA NTRS1999

Monitoring and Correcting Autonomic Function Aboard Mir: NASA Technology Used in Space and on Earth to Facilitate Adaptation

The broad objective of the research was to study individual characteristics of human adaptation to long duration spaceflight and possibilities of their correction using autonomic conditioning. The changes in autonomic state during adaptation to microgravity can have profound effects on the operational efficiency of crewmembers and may result in debilitating biomedical symptoms. Ground-based and inflight experiment results showed that certain responses of autonomic nervous system were correlated with, or consistently preceded, reports of performance decrements or the symptoms. Autogenic-Feedback-Training Exercise (AFTE) is a physiological conditioning method that has been used to train people to voluntary control several of their own physiological responses. The specific objectives were: 1) To study human autonomic nervous system (ANS) responses to sustained exposure to microgravity; 2) To study human behavior/performance changes related to physiology; 3) To evaluate the effectiveness of preflight autonomic conditioning (AFTE) for facilitating adaptation to space and readaptation to Earth; and 4) To archive these data for the NASA Life Sciences Data Archive and thereby make this information available to the international scientific community.

Cowings, P.↗
NASA NTRS1988

Telerobotic manipulator developments for ground-based space research

New opportunities for the application of telerobotic systems to enhance human intelligence and dexterity in the hazardous environment of space are presented by the National Aeronautics and Space Administration (NASA) Space Station Program. Because of the need for significant increases in extravehicular activity and the potential increase in hazards associated with space programs, emphasis is being heightened on telerobotic systems research and development. The Automation Technology Branch at NASA Langley Research Center currently is sponsoring the Laboratory Telerobotic Manipulator (LTM) program at Oak Ridge National Laboratory to develop and demonstrate ground-based telerobotic manipulator system hardware for research and demonstrations aimed at future NASA applications. The LTM incorporates traction drives, modularity, redundant kinematics, and state-of-the-art hierarchical control techniques to form a basis for merging the diverse technological domains of robust, high-dexterity teleoperations and autonomous robotic operation into common hardware to further NASA's research.

Herndon, J. N.↗
NASA NTRS1989

The laboratory telerobotic manipulator program

New opportunities for the application of telerobotic systems to enhance human intelligence and dexterity in the hazardous environment of space are presented by the NASA Space Station Program. Because of the need for significant increases in extravehicular activity and the potential increase in hazards associated with space programs, emphasis is being heightened on telerobotic systems research and development. The Laboratory Telerobotic Manipulator (LTM) program is performed to develop and demonstrate ground-based telerobotic manipulator system hardware for research and demonstrations aimed at future NASA applications. The LTM incorporates traction drives, modularity, redundant kinematics, and state-of-the-art hierarchical control techniques to form a basis for merging the diverse technological domains of robust, high-dexterity teleoperations and autonomous robotic operation into common hardware to further NASA's research.

Herndon, J. N.↗
DOE OSTI2025

GPR_calculator: An on-the-fly surrogate model to accelerate massive nudged elastic band calculations

We present GPR_calculator, a package based on Python and C++ programming languages to build an on-the-fly surrogate model using Gaussian Process Regression (GPR) to approximate computationally expensive electronic structure calculations. The key idea is to dynamically train a GPR model during the simulation that can accurately predict energies and forces with uncertainty quantification. When the uncertainty is high, the costly electronic structure calculation is performed to obtain the ground truth data, which is then used to update the GPR model. To illustrate the effectiveness of GPR_calculator, we demonstrate its application in Nudged Elastic Band (NEB) simulations of surface diffusion and reactions, achieving 3-10 times acceleration compared to pure ab initio calculations. The source code is available at https://github.com/MaterSim/GPR_calculator.

Gaussian process regression↗
DOE OSTI2017

On the Viability of Using Autonomous Three-Component Nodal Geophones to Calculate Teleseismic Ps Receiver Functions with an Application to Old Faithful, Yellowstone

Recent advances in seismic data-acquisition technology paired with an increasing interest from the academic passive source seismological community have opened up new scientific targets and imaging possibilities, often referred to as Large-N experiments (large number of instruments). The success of these and other deployments has motivated individual researchers, as well as the larger seismological community, to invest in the next generation of nodal geophones. Although the new instruments have battery life and bandwidth limitations compared to broadband instruments, the relatively low deployment and procurement cost of these new nodal geophones provides an additional novel tool for researchers. In this paper, we explore the viability of using autonomous three-component nodal geophones to calculate teleseismic Ps receiver functions by comparison of co-located broadband stations and highlight some potential advantages with a dense nodal array deployed around the Upper Geyser basin in Yellowstone National Park. Two key findings from this example include (1) very dense nodal arrays can be used to image small-scale features in the shallow crust that typical broadband station spacing would alias, and (2) nodal arrays with a larger footprint could be used to image deeper features with greater or equal detail as typical broadband deployments but at a reduced deployment cost.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Real-time sensing of bioaerosols: Review and current perspectives

Detection of bioaerosols, or primary biological aerosol particles (PBAPs), has become increasingly important for a wide variety of research communities and scientific questions. In particular, real-time (RT) techniques for autonomous, online detection and characterization of PBAP properties in both outdoor and indoor environments are becoming more commonplace and have opened avenues of research. With advances in technology, however, come challenges to standardize practices so that results are both reliable and comparable across technologies and users. Here, we present a critical review of major RT instrument classes that have been applied to PBAP research, especially with respect to environmental science, allergy monitoring, agriculture, public health, and national security. Eight major classes of RT techniques are covered, including the following: (i) fluorescence spectroscopy, (ii) elastic scattering, microscopy, and holography, (iii) Raman spectroscopy, (iv) mass spectrometry, (v) breakdown spectroscopy, (vi) remote sensing, (vii) microfluidic techniques, and (viii) paired aqueous techniques. For each class of technology we present technical limitations, misconceptions, and pitfalls, and also summarize best practices for operation, analysis, and reporting. The final section of the article presents pressing scientific questions and grand challenges for RT sensing of PBAP as well as recommendations for future work to encourage high-quality results and increased cross-community collaboration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2016

Using Multimodal Input for Autonomous Decision Making for Unmanned Systems

Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.

Neilan, James H.↗
DOE OSTI2024

Test Vector Development for Verification and Validation of Heavy-Duty Autonomous Vehicle Operations

The current focus in the ongoing development of autonomous driving systems (ADS) for heavy duty vehicles is that of vehicle operational safety. To this end, developers and researchers alike are working towards a complete understanding of the operating environments and conditions that autonomous vehicles are subject to during their mission. This understanding is critical to the testing and validation phases of the development of autonomous vehicles and allows for the identification of both the nominal and edge case scenarios encountered by these systems. Previous work by the authors saw the development of a comprehensive scenario generation framework to identify an operating domain specification (ODS), or external and internal conditions an autonomous driving system can expect to encounter on its mission to form critical scenario groups for autonomous vehicle testing and validating using statistical patterns, clustering, and correlation. Continuing this prior work, this paper focuses on the generation of test cases based on the critical scenarios identified that can be used to prioritize either the most common nominal driving scenarios or the least common severe driving scenarios. These test cases can then be used validate, through simulation or real-world testing, the operating design domain (ODD) for a generalized driving mission and built upon to identify spatial and temporal impacts on the driving mission of an autonomous vehicle.

Siekmann, Adam↗
NASA NTRS1994

WTEC panel report on research submersibles and undersea technologies

This report covers research submersibles and related subsea technologies in Finland, France, Russia, Ukraine and the United Kingdom. Manned, teleoperated, and autonomous submersibles were of interest. The panel found that, in contrast to the United States, Europe is making substantial progress in cooperative and coordinated research in subsea technology, including the development of standards. France is a leader in autonomous vehicle technology. Because much less was known a priori about the technologies in Russia and Ukraine, there were more new findings in those countries than in those Western European nations visited. However, Russia and Ukraine have a sizeable (and currently underutilized) infrastructure in this field, including a highly educated and experienced manpower pool, impressive (in some cases unique) facilities for physical testing, extensive fleets of seagoing research vessels capable of long voyages, and state-of-the-art facilities for conducting oceanographic investigations. The panel visited newly-formed commercial companies associated with long-standing submersible R&D and production centers in Russia and Ukraine. So far, these new efforts are undercapitalized, and as such represent opportunities at very low cost for Western nations, as detailed in the site reports.

Seymore, Richard J.↗
DOE OSTI2024

The Rise of Intelligent Materials Science: Unleashing the Power of Machine Intelligence in Characterization

Machine intelligence has the potential to revolutionize materials science, enabling autonomous synthesis, self-driving characterization, and accelerated modeling. However, despite the promise, successful implementation of these methods in day-to-day research remains a challenge. This talk will delve into the reasons behind this, exploring how truly intelligent experiments are hindered by opaque experiment control, a lack of domain-specific models, and human-centric design. Through a focus on the characterization of next-generation microelectronics and energy storage materials, I will share insights from both successful and failed attempts to implement machine intelligence. We will then explore the next steps necessary to unlock the full potential of machine intelligence in materials science, creating a future where intelligent systems work seamlessly alongside researchers to drive innovation and discovery.

autonomous↗
DOE OSTI2022

Extracting energy from ocean thermal and salinity gradients to power unmanned underwater vehicles: State of the art, current limitations, and future outlook

Thermal gradient energy-generation technologies for powering unmanned underwater vehicles (UUVs) or autonomous sensing systems in the ocean are mainly in the research development phase or commercially available at a limited scale, and salinity-gradient energy-generation technologies have not been adequately researched yet. The demand for self-powered UUVs suitable for long-term deployments has been growing, and further research related to small-scale ocean gradient energy systems is needed. In this study, we conducted a comprehensive review about harvesting energy from ocean thermal or salinity gradients for powering UUVs, focusing on gliders and profiling floats. Thermal gradient energy systems for UUVs based on phase change materials (PCM) cannot provide the energy required for powering autonomous sensing systems because of the systems' low energy conversion efficiency. Besides reducing energy consumption by developing more efficient electrical-mechanical systems, enhancing the thermal conductivity of the PCMs may help address this challenge by increasing the power generation rate of the UUVs. Several other emerging technologies, such as thermoelectric generators, shape memory alloys, and small-scale thermodynamic cycle systems, have shown potential for powering UUVs, but they are still only at the laboratory testing or conceptual design phase. The most advanced power generation technologies based on salinity gradients, reverse electrodialysis and pressure-retarded osmosis, are still not economically viable for large-scale deployment, mainly because of the high cost of the components required to operate in harsh saline environments. Our feasibility evaluation showed that existing salinity gradient power generation technologies are not directly feasible for powering UUVs in the open ocean.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Analysis of Tasks in Autonomous Systems Using the EMRALD Dynamic Risk Assessment Tool

An autonomous system refers to the system that has the power and ability for self-governance in the performance of system functions. Autonomous systems have been actively pursued in a variety of domains such as automotive, aviation, maritime, medicine, and nuclear fields. As an unmanned concept employing the highest automation level, the autonomous system basically performs most of the work in normal operations or emergency situations. However, despite advances in technology, many researchers have noted these systems still require human actions. The nature of human actions on autonomous systems is different than the human actions that are considered in existing systems. Nevertheless, only a few studies have been conducted on 1) characterizing the different types of errors and risks associated with human actions interacting with autonomous systems and 2) how to evaluate human actions in the autonomous operations. As a starting point, this study aims to investigate differences of tasks in autonomous operation compared to those in existing nuclear power plant operation using the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software. In this paper, insights aspect of human error and time are derived out and discussed based on the output of the EMRALD models.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2018

Evaluation of Crew-Centric Onboard Mission Operations Planning and Execution Tool: Year 2

Currently, mission planning for the International Space Station (ISS) is largely affected by ground operators in mission control. The task of creating a week-long mission plan for ISS crew takes dozens of people multiple days to complete, and is often created far in advance of its execution. As such, re-planning or adapting to changing real-time constraints or emergent issues is similarly taxing. As we design for future mission operations concepts to other planets or areas with limited connectivity to Earth, more of these ground-based tasks will need to be handled autonomously by the crew onboard.There is a need for a highly usable (including low training time) tool that enables efficient self-scheduling and execution within a single package. The ISS Program has identified Playbook as a potential option. It already has high crew acceptance as a plan viewer from previous analogs and can now support a crew self-scheduling assessment on ISS or on another mission. The goals of this work, a collaboration between the Human Research Program and the ISS Program, are to inform the design of systems for more autonomous crew operations and provide a platform for research on crew autonomy for future deep space missions. Our second year of the research effort have included new insights on the crew self-scheduling sessions performed by the crew through use on the HERA (Human Exploration Research Analog) and NEEMO (NASA Extreme Environment Mission Operations) analogs. Use on the NEEMO analog involved two self-scheduling strategies where the crew planned and executed two days of EVAs (Extra-Vehicular Activities). On HERA year two represented the first HERA campaign where we were able to perform research tasks. This involved selected flexible activities that the crew could schedule, mock timelines where the crew completed more complex planning exercises, usability evaluation of the crew self-scheduling features, and more insights into the limit of plan complexity that the crew could effectively self-schedule. In parallel we have added in new features and functionality in the Playbook tool based off of our insights from crew self-scheduling in the NASA analogs. In particular this year we have added in the ability for the crew to add, edit, and remove their own activities in the Playbook tool, expanding the type of planning and re-planning possible in the tool and opening up the ability for more free form plan creation. The ability to group and manipulate groups of activities from the plan task list was also added, allowing crew members to add predefined sets of activities onto their mission timeline. In addition we also added a way for crew members to roll back changes in their plan, in order to allow an undo like capability. These features expand and complement the initial self-scheduling features added in year one with the goal of making crew autonomous planning more efficient. As part of this work we have also finished developing the first version of our Playbook Data Analysis Tool, a research tool built to interpret and analyze the unobtrusively collected data obtained during the NASA analog missions through Playbook. This data which includes user click interaction as well as plan change information, through the Playbook Data Analysis Tool, allows us to playback this information as if a video camera was mounted over the crewmember's tablet. While the primary purpose of this tool is to allow usability analysis of crew self-scheduling sessions used on the NASA analog, since the data collected is structured, the tool can automatically derive metrics that would be traditionally tedious to achieve without manual analysis of video playback. We will demonstrate and discuss the ability for future derived metrics to be added to the tool. In addition to the current data and results gathered in year two we will also discuss the preparation and goals of our International Space Station (ISS) onboard technology demonstration with Playbook. This technology demonstration will be preformed as part of the CAST payload starting in late 2016.

onboard planning↗
NASA NTRS2016

SIG: Multiple Views on Safety-Critical Automation: Aircraft, Autonomous Vehicles, Air Traffic Management and Satellite Ground Segments Perspectives

This SIG focuses on the engineering of automation in interactive critical systems. Automation has already been studied in a number of (sub-) disciplines and application fields: design, human factors, psychology, (software) engineering, aviation, health care, games. One distinguishing feature of the area we are focusing on is that in the field of interactive critical systems properties such as reliability, dependability, fault tolerance are as important as usability, user experience or overall acceptance issues. The SIG targets at two problem areas: first the engineering of the user interaction with (partly-) autonomous systems: how to design, build and assess autonomous behavior, especially in cases where there is a need to represent on the user interface both autonomous and interactive objects. An example of such integration is the representation of an unmanned aerial vehicle (UAV) (where no direct interaction is possible), together with aircrafts (that have to be instructed by an air traffic controller to avoid the UAV). Second the design and engineering of user interaction in general for autonomous objects/systems (for example a cruise control in a car or an autopilot in an aircraft). The goal of the SIG is to raise interest in the CHI community on the general aspects of automation and to identify a community of researchers and practitioners interested in those increasingly prominent issues of interfaces towards (semi)-autonomous systems. The expected audience should be interested in addressing the issues of integration of mainly unconnected research domains to formulate a new joint research agenda.

human-automation interaction↗