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NASA NTRS1988

Multisensor robotic system for autonomous space maintenance and repair

The feasibility of realistic autonomous space manipulation tasks using multisensory information is demonstrated. The system is capable of acquiring, integrating, and interpreting multisensory data to locate, mate, and demate a Fluid Interchange System (FIS) and a Module Interchange System (MIS). In both cases, autonomous location of a guiding light target, mating, and demating of the system are performed. Implemented visio-driven techniques are used to determine the arbitrary two-dimensional position and orientation of the mating elements as well as the arbitrary three-dimensional position and orientation of the light targets. A force/torque sensor continuously monitors the six components of force and torque exerted on the end-effector. Both FIS and MIS experiments were successfully accomplished on mock-ups built for this purpose. The method is immune to variations in the ambient light, in particular because of the 90-minute day-night shift in space.

Abidi, M. A.↗

NASA NTRS1989

Learning from external environments using Soar

Soar, like the previous PRODIGY and Theo, is a problem-solving architecture that attempts to learn from experience; unlike them, it takes a more uniform approach, using a single forward-chaining architecture for planning and execution. Its single learning mechanism, designated 'chunking', is domain-independent. Two developmental approaches have been employed with Soar: the first of these allows the architecture to attempt a problem on its own, while the second involves a degree of external guidance. This learning through guidance is integrated with general problem-solving and autonomous learning, leading to an avoidance of human interaction for simple problems that Soar can solve on its own.

Laird, John E.↗

NASA NTRS1998

Integration of the Remote Agent for the NASA Deep Space One Autonomy Experiment

This paper describes the integration of the Remote Agent (RA), a spacecraft autonomy system which is scheduled to control the Deep Space 1 spacecraft during a flight experiment in 1999. The RA is a reusable, model-based autonomy system that is quite different from software typically used to control an aerospace system. We describe the integration challenges we faced, how we addressed them, and the lessons learned. We focus on those aspects of integrating the RA that were either easier or more difficult than integrating a more traditional large software application because the RA is a model-based autonomous system. A number of characteristics of the RA made integration process easier. One example is the model-based nature of RA. Since the RA is model-based, most of its behavior is not hard coded into procedural program code. Instead, engineers specify high level models of the spacecraft's components from which the Remote Agent automatically derives correct system-wide behavior on the fly. This high level, modular, and declarative software description allowed some interfaces between RA components and between RA and the flight software to be automatically generated and tested for completeness against the Remote Agent's models. In addition, the Remote Agent's model-based diagnosis system automatically diagnoses when the RA models are not consistent with the behavior of the spacecraft. In flight, this feature is used to diagnose failures in the spacecraft hardware. During integration, it proved valuable in finding problems in the spacecraft simulator or flight software. In addition, when modifications are made to the spacecraft hardware or flight software, the RA models are easily changed because they only capture a description of the spacecraft. one does not have to maintain procedural code that implements the correct behavior for every expected situation. On the other hand, several features of the RA made it more difficult to integrate than typical flight software. For example, the definition of correct behavior is more difficult to specify for a system that is expected to reason about and flexibly react to its environment than for a traditional flight software system. Consequently, whenever a change is made to the RA it is more time consuming to determine if the resulting behavior is correct. We conclude the paper with a discussion of future work on the Remote Agent as well as recommendations to ease integration of similar autonomy projects.

Dorais, Gregory A.↗

NASA NTRS2008

Expert System Control of Plant Growth in an Enclosed Space

The Expert System is an enclosed, controlled environment for growing plants, which incorporates a computerized, knowledge-based software program that is designed to capture the knowledge, experience, and problem-solving skills of one or more human experts in a particular discipline. The Expert System is trained to analyze crop/plant status, to monitor the condition of the plants and the environment, and to adjust operational parameters to optimize the plant-growth process. This system is intended to provide a way to remotely control plant growth with little or no human intervention. More specifically, the term control implies an autonomous method for detecting plant states such as health (biomass) or stress and then for recommending and implementing cultivation and/or remediation to optimize plant growth and to minimize consumption of energy and nutrients. Because of difficulties associated with delivering energy and nutrients remotely, a key feature of this Expert System is its ability to minimize this effort and to achieve optimum growth while taking into account the diverse range of environmental considerations that exist in an enclosed environment. The plant-growth environment for the Expert System could be made from a variety of structures, including a greenhouse, an underground cavern, or another enclosed chamber. Imaging equipment positioned within or around the chamber provides spatially distributed crop/plant-growth information. Sensors mounted in the chamber provide data and information pertaining to environmental conditions that could affect plant development. Lamps in the growth environment structure supply illumination, and other additional equipment in the chamber supplies essential nutrients and chemicals.

May, George↗

NASA NTRS2015

On-Demand Mobility (ODM) Technical Pathway: Enabling Ease of Use and Safety

On-demand mobility (ODM) through aviation refers to the ability to quickly and easily move people or equivalent cargo without delays introduced by lack of, or infrequently, scheduled service. A necessary attribute of ODM is that it be easy to use, requiring a minimum of special training, skills, or workload. Fully-autonomous vehicles would provide the ultimate in ease-of-use (EU) but are currently unproven for safety-critical applications outside of a few, situationally constrained applications (e.g. automated trains operating in segregated systems). Applied to aviation, the current and near-future state of the art of full-autonomy, may entail undesirable trade-offs such as very conservative operational margins resulting in reduced trip reliability and transportation utility. Furthermore, acceptance by potential users and regulatory authorities will be challenging without confidence in autonomous systems in developed in less critical, but still challenging applications. A question for the aviation community is how we can best develop practical ease-of-use for aircraft that are sized to carry a small number of passengers (e.g. 1-9) or equivalent cargo. Such development is unlikely to be a single event, but rather a managed, evolutionary process where responsibility and authority transitions from human to automation agents as operational experience is gained with increasingly intelligent systems. This talk presents a technology road map being developed at NASA Langley, as part of an overall strategy to foster ODM, for the development of ease-of-use for ODM aviation.

Goodrich, Ken↗

DOE OSTI2022

Need for research and training reactors for advanced reactor designs

Full text of publication follows. Research and training reactors have served a valuable role in helping train workforce for currently operating fleet of light water reactors. These research and training reactors have been used in reactor laboratory classes to familiarize the students with such vital concepts as approach to criticality, reactor period, neutron moderation, reactivity, flux distribution and leakage, etc. As the industry moves toward advanced non-light-water reactor designs, it is critical that research and training reactors be developed and deployed at university campuses to help train the new generation of nuclear and non-nuclear engineers who are likely to design, build, and operate these advanced reactors. Among the designs currently being pursued for nuclear power generation include molten salt, sodium cooled, and gas cooled designs, with options for various fuel forms. Thus, industry and DOE in collaboration with academic institutions should devise plans on how to familiarize the next generation of nuclear workforce with hands-on experience necessary for such designs. These research and training reactors will play a vital role in familiarizing the future workforce with hands-on experience with concepts associated with fast spectrum reactors, gas cooled reactors, and other features not associated with light water reactors. In addition to classical nuclear engineering concepts, these advanced research and training reactors can also be used for hands-on training as well as for research on features being considered in the design of GEN-IV reactors: cyber security for digital control room operations, hybrid energy system, hydrogen generation, district heating, autonomous control... (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1989

Petite Amateur Navy Satellite (PANSAT)

The Naval Postgraduate School's (NPS) Space Systems Academic Group (SSAG) is designing and developing a small communications satellite for launch aboard the shuttle as a complex autonomous payload (CAP). The objectives of PANSAT are three-fold. First, PANSAT will provide an ideal educational tool for the officer students at NPS supporting Space Systems Engineering and Space Systems Operations with hands-on hardware development. Second, the satellite will provide digital store-and-forward communications, or packet radio, for the amateur radio community. The third objective is to provide a low-cost, space-based platform for small experiments. PANSAT will be launched from the shuttle at a nominal altitude of 200 n.m. and an inclination of at least 37 degrees. The satellite weight is 150 lbs. Since there is no attitude control, eight dipole whip antennas will be used to provide isotropic ground coverage for communications. FM digital communications will be used with up-link and down-link on a single frequency in the amateur band of 437.25 MHz. A maximum 50 kHz of bandwidth is envisioned for the satellite. The expected lifetime of the satellite is 1 1/2 to 2 years before atmospheric reentry. The PANSAT design consists of the following: communications subsystem (COMM); computer, or data processor and sequencer (DP&S); power subsystem; structure subsystem; and experiment payload.

Sakoda, D.↗

DOE OSTI2023

Artificial intelligence for materials research at extremes

Abstract Materials development is slow and expensive, taking decades from inception to fielding. For materials research at extremes, the situation is even more demanding, as the desired property combinations such as strength and oxidation resistance can have complex interactions. Here, we explore the role of AI and autonomous experimentation (AE) in the process of understanding and developing materials for extreme and coupled environments. AI is important in understanding materials under extremes due to the highly demanding and unique cases these environments represent. Materials are pushed to their limits in ways that, for example, equilibrium phase diagrams cannot describe. Often, multiple physical phenomena compete to determine the material response. Further, validation is often difficult or impossible. AI can help bridge these gaps, providing heuristic but valuable links between materials properties and performance under extreme conditions. We explore the potential advantages of AE along with decision strategies. In particular, we consider the problem of deciding between low-fidelity, inexpensive experiments and high-fidelity, expensive experiments. The cost of experiments is described in terms of the speed and throughput of automated experiments, contrasted with the human resources needed to execute manual experiments. We also consider the cost and benefits of modeling and simulation to further materials understanding, along with characterization of materials under extreme environments in the AE loop. Graphical abstract AI sequential decision-making methods for materials research: Active learning, which focuses on exploration by sampling uncertain regions, Bayesian and bandit optimization as well as reinforcement learning (RL), which trades off exploration of uncertain regions with exploitation of optimum function value. Bayesian and bandit optimization focus on finding the optimal value of the function at each step or cumulatively over the entire steps, respectively, whereas RL considers cumulative value of the labeling function, where the latter can change depending on the state of the system (blue, orange, or green).

36 MATERIALS SCIENCE↗

NASA NTRS2016

HIAD on ULA (HULA) Orbital Reentry Flight Experiment Concept

This paper describes a proposed orbital velocity reentry flight test of a Hypersonic Inflatable Aerodynamic Decelerator (HIAD). The flight test builds upon ground development activities that continue to advance the materials, design, and manufacturing techniques for the inflatable structure and flexible thermal protection system (F-TPS) that comprise the inflatable heat shield. While certain aspects of material and system performance can be assessed using a variety of ground testing capabilities, only orbital velocity energy on a trajectory through the gradient density of the atmosphere can impart the combined aerodynamic and aeroheating design environments in real time. To achieve this at limited cost, the HIAD would be delivered to a spin-stabilized entry trajectory as a secondary payload on the Centaur stage of a United Launch Alliance (ULA) Atlas V launch vehicle. Initial trajectory studies indicate that the combination of launch vehicle capability and achievable reentry vehicle ballistic numbers make this a strategic opportunity for technology development. This 4 to 6 meter diameter scale aeroshell flight, referred to as HIAD on ULA (HULA), would also contribute to ULA asset recovery development. ULA has proposed that a HIAD be utilized as part of the Sensible, Modular, Autonomous Return Technology (SMART) initiative to enable recovery of the Vulcan launch vehicle booster main engines [1], including a Mid-Air Recovery (MAR) to gently return these assets for reuse. Whereas HULA will attain valuable aerothermal and structural response data toward advancing HIAD technology, it may also provide a largest-to-date scaled flight test of the MAR operation, which in turn would allow the examination of a nearly pristine post-entry aeroshell. By utilizing infrared camera imaging, HULA will also attain aft-side thermal response data, enhancing understanding of the aft side aerothermal environment, an area of high uncertainty. The aeroshell inflation will utilize a heritage design compressed gas system to minimize development costs. The data will be captured to both an onboard recorder and a recorder that is jettisoned and recovered separately from the reentry vehicle to mitigate risk. This paper provides an overview, including the architecture and flight concept of operations, for the proposed HULA flight experiment.

Dinonno, J. M.↗

NASA NTRS1990

Sparse distributed memory overview

The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massively parallel computing architecture, called sparse distributed memory, that will support the storage and retrieval of sensory and motor patterns characteristic of autonomous systems. The immediate objectives of the project are centered in studies of the memory itself and in the use of the memory to solve problems in speech, vision, and robotics. Investigation of methods for encoding sensory data is an important part of the research. Examples of NASA missions that may benefit from this work are Space Station, planetary rovers, and solar exploration. Sparse distributed memory offers promising technology for systems that must learn through experience and be capable of adapting to new circumstances, and for operating any large complex system requiring automatic monitoring and control. Sparse distributed memory is a massively parallel architecture motivated by efforts to understand how the human brain works. Sparse distributed memory is an associative memory, able to retrieve information from cues that only partially match patterns stored in the memory. It is able to store long temporal sequences derived from the behavior of a complex system, such as progressive records of the system's sensory data and correlated records of the system's motor controls.

Raugh, Mike↗

NASA NTRS1994

The sympathetic nervous system and the physiologic consequences of spaceflight: a hypothesis

Many of the physiologic consequences of weightlessness and the cardiovascular abnormalities on return from space could be due, at least in part, to alterations in the regulation of the autonomic nervous system. In this article, the authors review the rationale and evidence for an autonomic mediation of diverse changes that occur with spaceflight, including the anemia and hypovolemia of weightlessness and the tachycardia and orthostatic intolerance on return from space. This hypothesis is supported by studies of two groups of persons known to have low catecholamine levels: persons subjected to prolonged bedrest and persons with syndromes characterized by low circulating catecholamines (Bradbury-Eggleston syndrome and dopamine beta-hydroxylase deficiency). Both groups exhibit the symptoms mentioned. The increasing evidence that autonomic mechanisms underlie many of the physiologic consequences of weightlessness suggests that new pharmacologic approaches (such as administration of beta-blockers and/or sympathomimetic amines) based on these findings may attenuate these unwanted effects.

short duration↗

NASA NTRS1998

Operations and Autonomy of the Mars Pathfinder Microrover

The Microrover Flight Experiment (MFEX) is a NSAS OACT (Office of Advanced Concepts and Technology) flight experiment which, integrated with the Mars Pathfinder (MPF) lander and spacecraft system, landed on Mars on July 4, 1997.

navigation surface operations scenario commmand se↗

NASA NTRS2015

Diagnostic Reasoning using Prognostic Information for Unmanned Aerial Systems

With increasing popularity of unmanned aircraft, continuous monitoring of their systems, software, and health status is becoming more and more important to ensure safe, correct, and efficient operation and fulfillment of missions. The paper presents integration of prognosis models and prognostic information with the R2U2 (REALIZABLE, RESPONSIVE, and UNOBTRUSIVE Unit) monitoring and diagnosis framework. This integration makes available statistically reliable health information predictions of the future at a much earlier time to enable autonomous decision making. The prognostic information can be used in the R2U2 model to improve diagnostic accuracy and enable decisions to be made at the present time to deal with events in the future. This will be an advancement over the current state of the art, where temporal logic observers can only do such valuation at the end of the time interval. Usefulness and effectiveness of this integrated diagnostics and prognostics framework was demonstrated using simulation experiments with the NASA Dragon Eye electric unmanned aircraft.

Diagnostics↗

NASA NTRSDate not supplied

Supervised Autonomous Assembly to Create and Evolve Persistent Assets

Supervised autonomous assembly (SAA) will create a paradigm shift in the planning and design of future persistent assets (PAs), both in near zero-g environments and on planetary surfaces. SAA refers to an autonomy approach that has the benefits of autonomous assembly as well as the benefits provided by a supervisor (operator) who is available to resolve unexpected situations. SAA provides both increased design freedom as well as reduced programmatic risk. SAA enables evolution of future PAs over decades as in-space operations transition from single purpose missions to creation of PAs, such as laboratories and experimental stations which more closely resembling terrestrial laboratories that can easily adapt and evolve to new missions leveraging repeated visits to the PA. The ability to evolve enables PAs to rapidly respond to changing objectives resulting from new questions as our understanding improves. A recently initiated National Aeronautics and Space Administration (NASA) project in the Space Technology Mission Directorate (STMD) Game Changing Development (GCD) Program called the Precision Assembled Space Structure (PASS), leverages the advantages of SAA to develop technologies that enable efficient creation and evolution of hexagonal topologies; both planar (example: fuel depots) and curved (examples: telescopes and shelters). PASS will be used to provide context for the philosophy and concepts discussed as well as the decision and selections made. PASS objectives are: a) Develop confidence in SAA and on-orbit servicing, assembly and manufacturing (OSAM) technologies by executing a test campaign that uses a path-to-flight autonomous precision assembly process directly applicable to future space telescopes. b) Test autonomous technologies including automated path planning and error recovery, to emphasize a robust approach that relies on generic robots and special purpose tools. c) Validate critical component models using a digital twin that includes the assembled primary mirror support structure and assembly process. A digital twin is a high-fidelity simulation of the asset capable of predicting the on-orbit performance. The paper concludes after identifying the critical need for a modest assembly flight experiment to validate and develop confidence in the SAA paradigm, thus accelerating adoption of the benefits described. SAA is a game changing paradigm that enhances the ability of an organization to infuse new technology through rapid evolution of PAs while leveraging OSAM technologies.

Structural Modeling↗

DOE OSTI2025

Autonomous organic synthesis for redox flow batteries via flexible batch Bayesian optimization

Traditional trial-and-error methods for materials discovery are inefficient to meet the urgent demands posed by the rapid progression of climate change. This urgency has driven the increasing interest in integrating robotics and machine learning into materials research to accelerate experimental learning. However, idealized decision-making frameworks to achieve maximum sampling efficiency are not always compatible with high-throughput experimental workflows inside a laboratory. For multi-step chemical processes, differences in hardware capacities can complicate the digital framework by introducing constraints on the maximum number of samples in each step of the experiment, hence causing varying batch sizes in variable selection within the same batch. Therefore, designing flexible sampling algorithms is necessary to accommodate the multi-step synthesis with practical constraints unique to each high-throughput workflow. In this work, we designed and employed three strategies on a high-throughput robotic platform to optimize the sulfonation reaction of redox-active molecules used in flow batteries. Our strategies adapt to the multi-step experimental workflow, where their formulation and heating steps are separate, causing varying batch size requirements. By strategically sampling using clustering and mixed-variable batch Bayesian optimization, we were able to iteratively identify optimal conditions that maximize the yields. Our work presents a flexible approach that allows tailoring the machine learning decision-making to suit the practical constraints in individual high-throughput experimental platforms, followed by performing resource-efficient yield optimization using available open-source Python libraries.

Tamura, Clara [Univ. of Washington, Seattle, WA (U↗

NASA NTRS1992

Autonomous berthing/unberthing of a Work Attachment Mechanism/Work Attachment Fixture (WAM/WAF)

Discussed here is the autonomous berthing of a Work Attachment Mechanism/Work Attachment Fixture (WAM/WAF) developed by NASA for berthing and docking applications in space. The WAM/WAF system enables fast and reliable berthing (unberthing) of space hardware. A successful operation of the WAM/WAF requires that the WAM motor velocity be precisely controlled. The operating principle and the design of the WAM/WAF is described as well as the development of a control system used to regulate the WAM motor velocity. The results of an experiment in which the WAM/WAF is used to handle an orbital replacement unit are given.

Nguyen, Charles C.↗

NASA NTRS2020

Preparing for Human Missions to Mars: The role of ISS and Artemis as Analogs for Research and Technology Testing

The hazards of spaceflight to the human system are present in in varying degrees on different spaceflight platforms: altered gravity, isolation and confinement, distance from Earth, radiation, and hostile closed environments. A strategic view of the fidelity of hazards experienced on different platforms can shape the testing plans for human research and technology demonstration related to crew health and performance. Working across the international partnership, the International Space Station (ISS) is planning periods of modified operations to improve the fidelity of Mars simulations. To understand transit durations as an independent variable, a series of 1-year, 6-month and 30-45 day missions are being planned on ISS. Standard measurements across ISS missions of different durations, lunar missions and ground analogs offers the opportunity to distinguish different hazards and their effects in the context of the relevance to future mission concepts. The ISS partnership is planning for additional test cases that are aligned with Mars mission plans. (1) Evaluating crew performance capabilities when transitioning to gravity after long durations in microgravity representative of a Mars transit. (2) Simulating crew medical care under Mars-like autonomous operations. (3) Identification and testing of operations under communications delay and autonomy expected for Mars missions and the linked effects on behavioral health and performance of the crew. Artemis missions serve as a valuable analogs for Mars surface operations, with partial gravity and deep space radiation hazards, but with crewmembers that are probably more physically capable than their counterparts would be after a Mars transit. Getting unobtrusive data from early Artemis missions, and knowledge gained from operational experience as Artemis operations develop can improve engineering design, medical requirements and countermeasures, and ultimately ensure mission success on Mars. Linking Mars architectures with the plans and capabilities for ISS and Artemis allows us to plan to most operationally relevant tests of crew health and performance on current spaceflight missions to inform planning for future missions to Mars. By using human spaceflight platforms as well as ground simulation in an integrated way, the international community can improve exploration readiness, develop countermeasures and reduce risks of future human space missions.

International Space Station↗

DOE OSTI2024

3D high-fidelity automated neutronics guided optimization of fusion blanket designs

The compact Fusion Pilot Plant (FPP) is defined in the recent National Academies of Sciences, Engineering, and Medicine report as the next step of fusion energy demonstration with a $50$ MWe peak net electricity production, $Q_e$ greater than $1$, and at least $3$ hours of continuous operation. This fusion pilot plant will be a test bed enabling materials, designs, and fuel management assessment, and it will represent an engineering challenge because of its high-fusion power and compact design targets. Previous reactor data is limited to experiments operating in different design space ranges. Therefore, design iterations and assessments should rely on high-fidelity first-principle theoretical and computational models. The high-fidelity integrated modeling of the plasma is a fundamental part of fusion energy research. However, the whole device modeling is often neglected, utilizing low-fidelity, system-level analysis. Recently, the need for high-fidelity multi-physics modeling was recognized, resulting in a selection of integrated tools. Further, autonomous design optimization requires a streamlined framework that perturbs the design point, reruns the analysis, and examines the outputs. However, high-fidelity analysis requires complex geometry specification that is difficult to perturb. This work presents the parametric CAD generation tool TRACER and a new neutronic workflow. TRACER allows the perturbation of the geometry representation, creating geometry files ready for further analysis. The streamlined neutronic workflow allows efficient and accurate calculations. The two new tools coupled together were used to perform a 3D high-fidelity multi-objective, multi-input optimization of an "ARC Class" compact tokamak design. The workflow was driven by an optimization driver for full automation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗