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At least 127 records · Page 7

Artificial Intelligence: Powering Human Exploration of the Moon and Mars

Artificial Intelligence (AI) is a growing field of computa- tional science techniques designed to mimic functions per- formed by people. Advancements in autonomy will depend on a portfolio of AI technologies. Automated planning and scheduling is a venerable field of study in AI, and is needed for a variety of mission planning functions. Plan execution technology is less well studied, but important for auton- omy and robotics. Specialized forms of automated reason- ing and machine learning are key technologies to enable fault management. Over the past decade, the NASA Au- tonomous Systems and Operations (ASO) project has devel- oped and demonstrated numerous autonomy enabling tech- nologies employing AI techniques. Our work has employed AI in three distinct ways to enable autonomous mission op- erations capabilities. Crew Autonomy gives astronauts tools to assist in the performance of each of these mission oper-ations functions. Vehicle System Management uses AI tech- niques to turn the astronaut's spacecraft into a robot, allow- ing it to operate when astronauts are not present, or to reduce astronaut workload. AI technology also enables Autonomous Robots as crew assistants or proxies when the crew are not present. When these capabilities are used to enable astro- nauts to operate autonomously, they must be integrated with user interfaces, introducing numerous human factors con- siderations; when these capabilities are used to enable vehi- cle system management, they must be integrated with flight software, and run on embedded processors under the control of real-time operating systems.We first describe human spaceflight mission operations capabilities. The remainder of the paper will describe the ASO project, and the development and demonstration per- formed by ASO since 2011. We will describe the AI tech- niques behind each of these demonstrations, which include a variety of symbolic automated reasoning and machine learn- ing based approaches. Finally, we conclude with an assess- ment of future development needs for AI to enable NASA's future Exploration missions.

Mission Operations↗

Spaceflight tracking and data network operational reliability assessment for Skylab

Data on the spaceflight communications equipment status during the Skylab mission were subjected to an operational reliability assessment. Reliability models were revised to reflect pertinent equipment changes accomplished prior to the beginning of the Skylab missions. Appropriate adjustments were made to fit the data to the models. The availabilities are based on the failure events resulting in the stations inability to support a function of functions and the MTBF's are based on all events including 'can support' and 'cannot support'. Data were received from eleven land-based stations and one ship.

Seneca, V. I.↗

MIT January Operational Internship Experience 2011

This slide presentation reviews the 2011 January Operational Internship experience (JOIE) program which allows students to study operational aspects of spaceflight, how design affects operations and systems engineering in practice for 3 weeks. Topics include: (1) Systems Engineering (2) NASA Organization (3) Workforce Core Values (4) Human Factors (5) Safety (6) Lean Engineering (7) NASA Now (8) Press, Media, and Outreach and (9) Future of Spaceflight.

DeLatte, Danielle↗

Recurring Causes of Human Spaceflight Mishaps During Flight Tests and Early Operations

An analysis of recurring causes underlying human spaceflight mishaps that occurred during flight tests and early operations was performed. Eight mishaps from the Apollo, Soyuz, Skylab, Space Shuttle, and Constellation Programs (i.e., the Ares-1X test flight) and early commercial suborbital operations were included in the study. Detailed event analyses were performed for the historical mishaps and aggregate data analyses conducted to identify recurring issues. The nine most frequent issues were inadequate technical controls or risk management practices, incomplete procedures, system design and development issues, inadequate inspection or secondary verification requirements, failures of organizations to learn from previous incidents, inadequate schedule controls, inadequate task analyses or design processes, flaws in the design of organizations, and issues with organizational safety cultures.

Human Spaceflight↗

Promoting Astronaut Autonomy in Human Spaceflight Missions

Mission operations will have to adapt for long duration, long distance human spaceflight missions. This change is driven mainly by the significantly different communication availability between Earth and space. As astronauts travel farther from Earth, the one-way communication latency increases; the amount of bandwidth will be limited; and there will be period of long and/or no communication. Currently, ground flight controllers collaborate and cooperate with astronauts in space to accomplish essential operational functions. Astronaut autonomy, i.e., the crew’s ability to work more independently from mission control, will be a key enabler in future exploration missions. Over the last several years, the NASA Ames Human-Computer Interaction (HCI) Group has investigated various ways to promote and support astronaut autonomy in human spaceflight missions. Software prototypes are researched, designed, implemented, and assessed for their ability to enable astronaut autonomy. From integrated Internet of Thing for Space, advanced procedures interfaces, comm-delayed chats, and self-scheduling tools, the HCI Group has explored different aspects of astronaut autonomy. Specifically, the self-scheduling tool Playbook has been evaluated in analog extreme environments and onboard the International Space Station, successfully paving the way for future autonomous astronauts.

crew autonomy↗

Recurring Causes of Human Spaceflight Mishaps during Flight Tests and Early Operations

n analysis of recurring causes underlying human spaceflight mishaps that occurred during flight tests and early operations was performed. Eight mishaps from the Apollo, Soyuz, Skylab, Space Shuttle, and Constellation Programs (i.e., the Ares-1X test flight) and commercial suborbital systems were included in the study. Detailed event analyses were performed for the historical mishaps and aggregate data analyses conducted to identify recurring issues. The nine most frequent issues were inadequate technical controls or risk management practices, incomplete procedures, system design and development issues, inadequate inspection or secondary verification requirements, failures of organizations to learn from previous incidents, inadequate schedule controls, inadequate task analyses or design processes, flaws in the design of organizations, and issues with organizational safety cultures.

Timothy S Barth↗

The Evolution of the Impact Evidence Library Methods – What We Learned

During fiscal years 2020-2022 NASA’s Human Research Program, Exploration Medical Capability Element has worked to source this evidence for the model. During the process several lessons learned have been identified and drive recommendations for future efforts. The ICL 1.0: Spaceflight Medical Operational expertise should be consulted regarding the addition of future conditions. A clinician experienced with the nuances of spaceflight is recommended to have a minimum of 20 hours per condition to adequately source the evidence. Condition definitions should be carefully crafted to maintain mutual exclusivity. Common side effects from medications, common and consequential incidental findings in laboratory studies, and consequential side effects of diagnostic and procedural capabilities should be considered for inclusion as unique conditions in future iterations of the ICL 1.0. Incidence: Spaceflight incidence, although based on small population sizes, is the gold standard. Terrestrial incidence should be applied cautiously. Probability of minor vs. severe cases of the condition: Data informing severity probability of the medical condition are nearly always terrestrial. Special attention should be paid to this metric as it drives outcomes in the model and terrestrial data often overestimate severity of expected cases in spaceflight. Condition duration: Three clinical phases currently exist in the model. They represent the time necessary for diagnosis, treatment/convalescence/recurrence, and the remaining duration of the mission after maximal recovery, respectively. Further subdivision of acute and convalescent treatment/recurrence is recommended. Probability of need for evacuation: Surrogates for “Return to Definitive Care” were chosen prior to data collection. In most cases these surrogates were “need for hospitalization” or “need for surgery.” For many conditions these may not be realistic drivers of “Return to Definitive Care” and should be re-examined. Probability of Crew Mortality: Terrestrial mortality data is difficult to apply to astronauts who, invariably, have less comorbidities than terrestrial subjects. It must be applied judiciously. The proportion of mission tasks impaired by the condition: “Task Impairment” was assigned to each condition prior to the condition duration data becoming available. Future efforts should assign Task Impairment as the final step in sourcing the evidence.

A.J. Kreykes↗

Exploration Technologies for Operations

Although the International Space Station (ISS) assembly has been completed, the Operations support teams continue to seek more efficient and effective ways to prepare for and conduct the ISS operations and future exploration missions beyond low earth orbit. This search for improvement has led to a significant collaboration between the NASA research and advanced software development community at NASA Ames Research Center and the Mission Operations community at NASA Johnson Space Center. Since 2001, NASA Ames Research Center has been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for several of the unmanned Mars missions operations. Since 2006, NASA Ames Research Center has also been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for manned operations support with the Mission Operations Directorate at NASA Johnson Space Center. This paper discusses the completion of the development and deployment of a variety of intelligent and human systems technologies adopted for manned mission operations. The technologies associated with the projects include advanced software systems for operations and human-centered computing. Human-centered computing looks to the processes and procedures that people do to perform any given job, then attempts to identify opportunities to improve these processes and procedures. In particular, for mission operations, improvements are quantified by specifically identifying how a tool can increase a persons efficiency, enhance a persons functional capability, andor improve the assurance of a persons decisions. The Ames development team has collaborated with the Mission Operations team to identify areas of efficiencies through technology infusion applications in support of the Plan, Train, and Fly activities of human-spaceflight mission operations. The specific applications discussed in this paper are in the areas of mission planning systems, mission operations design modeling and workflow automation, advanced systems monitoring, mission control technologies, search tools, training management tools, spacecraft solar array management, spacecraft power management, and spacecraft attitude planning. We discuss these specific projects between the Ames Research Center and the Johnson Space Centers Mission Operations Directorate, and how these technologies and projects are enhancing the mission operations support for the International Space Station. We also discuss the challenges, problems, and successes associated with long-distance and multi-year development projects between the research team at Ames and the Mission Operations customers at Johnson Space center. Finally, we discuss how these technology infusion applications and underlying technologies might be used in the future to support on-board operations of the crew and spacecraft systems as human exploration expands beyond low earth orbit to destinations in the solar system where communications delays will require more on-board autonomy and planning by the crew. Longer communications delays will require that the ground mission operations support will be primarily strategic in nature, while the tactical level of planning, systems monitoring and control, and failure analysisisolationrecovery will be the responsibility of both the spacecraft autonomous systems and the crew. Our expectation is that the technologies

mission operations↗

Assessment of Proficiency During Simulated Rover Operations Following Long-Duration Spaceflight

Following long-duration space travel, pressurized rovers will enhance crew mobility to explore Mars and other planetary surfaces. Adaptive changes in sensorimotor function may limit the crew s proficiency when performing some rover operations shortly after transition to the new gravitoinertial environment. The primary goal of this investigation is to quantify postflight decrements in operational proficiency in a motion-based rover simulation after International Space Station (ISS) expeditions. Given that postflight performance will also be influenced by the level of preflight proficiency attained, a ground-based normative study was conducted to characterize the acquisition of skills over multiple sessions.

Wood, S. J.↗

Assessment of Proficiency During Simulated Rover Operations Following Long-Duration Spaceflight

Following long-duration space travel, pressurized rovers will enhance crew mobility to explore Mars and other planetary surfaces. Adaptive changes in sensorimotor function may limit the crew's proficiency when performing some rover operations shortly after transition to the new gravitoinertial environment. The primary goal of this investigation is to quantify postflight decrements in operational proficiency in a motion-based rover simulation after International Space Station (ISS) expeditions.

Beltran, E. J.↗

Human-Automation Allocations for Current Robotic Space Operations

Within the Human Research Program, one risk delineates the uncertainty surrounding crew working with automation and robotics in spaceflight. The Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) is concerned with the detrimental effects on crew performance due to ineffective user interfaces, system designs and/or functional task allocation, potentially compromising mission success and safety. Risk arises because we have limited experience with complex automation and robotics. One key gap within HARI, is the gap related to functional allocation. The gap states: We need to evaluate, develop, and validate methods and guidelines for identifying human-automation/robot task information needs, function allocation, and team composition for future long duration, long distance space missions. Allocations determine the human-system performance as it identifies the functions and performance levels required by the automation/robotic system, and in turn, what work the crew is expected to perform and the necessary human performance requirements. Allocations must take into account each of the human, automation, and robotic systems capabilities and limitations. Some functions may be intuitively assigned to the human versus the robot, but to optimize efficiency and effectiveness, purposeful role assignments will be required. The role of automation and robotics will significantly change in future exploration missions, particularly as crew becomes more autonomous from ground controllers. Thus, we must understand the suitability of existing function allocation methods within NASA as well as the existing allocations established by the few robotic systems that are operational in spaceflight. In order to evaluate future methods of robotic allocations, we must first benchmark the allocations and allocation methods that have been used. We will present 1) documentation of human-automation-robotic allocations in existing, operational spaceflight systems; and 2) To gather existing lessons learned and best practices in these role assignments, from spaceflight operational experience of crew and ground teams that may be used to guide development for future systems. NASA and other space agencies have operational spaceflight experience with two key Human-Automation-Robotic (HAR) systems: heavy lift robotic arms and planetary robotic explorers. Additionally, NASA has invested in high-fidelity rover systems that can carry crew, building beyond Apollo's lunar rover. The heavy lift robotic arms reviewed are: Space Station Remote Manipulator System (SSRMS), Japanese Remote Manipulator System (JEMRMS), and the European Robotic Arm (ERA, designed but not deployed in space). The robotic rover systems reviewed are: Mars Exploration Rovers, Mars Science Laboratory rover, and the high-fidelity K10 rovers. Much of the design and operational feedback for these systems have been communicated to flight controllers and robotic design teams. As part of the mitigating the HARI risk for future human spaceflight operations, we must document function allocations between robots and humans that have worked well in practice.

robotic allocation↗

A Flexible Control Center Architecture for Support of Diverse Spaceflight Missions

The Ames Multi-Mission Operations Center (MMOC) enables and supports flight and science operations for Ames' spaceflight missions. The MMOC is composed of the facilities, networks, information technology equipment, software, and system administration services needed by flight projects to effectively and efficiently perform all mission functions, including planning, scheduling, command, telemetry processing, and science analysis. The MMOC's ready-to-use services reduce start-up time, shorten procurement and provisioning and allow mission planning efforts to focus more on science and less on infrastructure. The architecture of the MMOC was designed from the start for flexibility, so that it can readily support multiple missions of greatly varying size and complexity while simultaneously keeping costs low.

Differding, Joan C.↗

Characterizing Fractures Across the Astronaut Corps: Preliminary Findings from Population-Level Analysis

Despite evidence of bone loss during spaceflight and operational countermeasures to mitigate this loss, the subsequent risk of fracture among astronauts is not known. The physiologic process of diminished bone density and bone recovery during or following spaceflight is multifactorial. Such factors as age, sex, fracture history, and others may combine to increase fracture risk among astronauts. As part of the 2016 Bone Research and Clinical Advisory Panel (RCAP), the authors analyzed data collected on 338 NASA astronauts to describe the demographics, bone-relevant characteristics, and fracture history of the astronaut population. The majority of the population are male (n=286, 84.6%), have flown at least one mission (n=306, 90.5%), and were between the ages of 30 and 49 at first mission (n=296, 96.7% of those with at least one mission). Of the 338 astronauts, 241 (71.3%) experienced a fracture over the course of their lifetime. One hundred and five (43.5%) of these 241 astronauts only experienced a fracture prior to being selected into the Astronaut Corps, whereas 53 (22.0%) only experienced a fracture after selection as an astronaut. An additional 80 astronauts (33.2%) had both pre- and post-selection fractures. The remaining 3 astronauts had a fracture of unknown date, which could not be categorized as pre- or post-selection. Among the 133 astronauts with at least one post-selection fracture, males comprised 90.2% (n=120) compared to 84.5% of the entire Corps, and females accounted for 9.8% (n=13) compared to 15.4% of the Corps. Ninety-seven of the 133 astronauts with post-selection fractures (72.9%) had one fracture event, 22 (16.5%) had two fractures, and 14 (10.5%) had three or more fractures. Some astronauts with multiple fractures suffered these in a single event, such as an automobile accident. The 133 astronauts with a post-selection fracture accounted for a total of 188 fracture events. One hundred and four (78.2%) of astronauts with post-selection fractures experienced those fractures following their first mission (mean 12.7 +/- 11.1 years following first mission; range 14.0 days - 50.6 years). Additional analyses are ongoing and include examination of fracture history, skeletal site, mechanism, and type of fracture, age at time of fracture, time from spaceflight to fracture, as well as multivariable analysis comparing fracture events to non-events. The results of such analyses may reveal trends in risk factors for fracture among the astronaut corps that have yet to be systematically described through a corps-wide approach.

Rossi, Meredith M.↗

Turbulence Modeling near Gas-Liquid Interfaces for Cryogenic Fluid Management

In cryogenic fluid management (CFM), gas-liquid interface turbulence transport (ITT) heavily influences crucial design parameters of spaceflight missions. ITT and phase change processes require length-scales and time-scales that are around 4-8 orders of magnitude smaller than the scales of CFM operations in spaceflights. A sharp interface method based parsimonious yet elegant turbulence modeling approach was developed from experimental observations and high-fidelity numerical studies. The technique was validated using flight-scale CFM tests.

cryogenic fluid management↗

Development of a Rover Simulation to Assess Operational Proficiency Following Long Duration Spaceflights

Following long-duration space transits, adaptive changes in sensorimotor and cognitive function may impair the crew s ability to safely control pressurized rovers designed to explore the new environment. We describe a rover simulation developed to quantify post-flight decrements in operational proficiency following International Space Station expeditions. The rover simulation consists of a serial presentation of discrete tasks to be completed as quickly and accurately as possible. Each task consists of 1) perspective taking using a map that defines a docking target, 2) navigation toward the target around a Martian outpost, and 3) docking a side hatch of the rover to a visually guided target. The simulator utilizes a Stewart-type motion base (CKAS, Australia), single seat cabin with triple scene projection covering approximately 150 horizontal by 40 vertical, and joystick controller. The software was implemented using Unity3 with next-gen PhysX engine to tightly synchronize simulation and motion platform commands. Separate C# applications allow investigators to customize session sequences with different lighting and gravitational conditions, and then execute tasks to be performed as well as record performance data. Preliminary tests resulted in low incidence of motion sickness (<15% unable to complete first session), with only negligible after effects and symptoms after familiarization sessions. Functionally relevant testing early post-flight will develop evidence regarding the limitations to early surface operations and what countermeasures are needed. This approach can be easily adapted to other vehicle designs to provide a platform to safely assess how sensorimotor and cognitive function impact manual control performance.

DeDios, Y. E.↗

NSCOR for Evaluating Risk Factors and Biomarkers for Adaptation and Resilience to Spaceflight: Emotional Valence and Social Processes in ICC/ICE Environments

Space exploration class missions, such as a mission to Mars, will require optimization of human performance, adaptability, and resilience. This NASA Specialized Center of Research (NSCOR) utilizes the NIMH Research Domain Criteria (RDoC) framework to identify biological and behavioral markers of individual social adaptation and emotional resilience (as well as vulnerability) to spaceflight-relevant stressors such as living in extended isolation. The overarching goal of this NSCOR is to obtain novel information to help identify biomarkers of individuals who are resilient and/or adaptable to the stressors of isolated, confined, and controlled (ICC) and isolated, confined, and extreme (ICE) environments.A total of N=90 healthy adult astronaut surrogates are being studied in three spaceflight-analog environments: (1) n=40 healthy adults in the Isolation and Confinement Analog Research Unit (ICARUS), an ICC at the University of Pennsylvania, during 7-day missions, for a target total of 280 subject days; (2) n=32 healthy adult astronaut surrogates studied in NASA’s Human Exploration Research Analog (HERA), an ICC at Johnson Space Center during 45-day missions, for a target total of 2,112 subject days; and (3) n=18 healthy adults in the Alfred-Wegener-Institute’s Neumayer Station III, an ICE in Antarctica, during 14-month missions, for a target total of 7,560 subject days. Dr. Nindl’s Laboratory at the University of Pittsburgh is analyzing a priori selected protein biomarkers in blood, saliva, and urine. Complementary rodent models of exposure to early life stressors, confinement, and isolation are being evaluated at Dr. Hensch’s Laboratory to further validate the neurobehavioral and biological findings from the human studies.Given the inconsistency and varied definition of resilience/adaptation in the scientific literature, the NSCOR team developed a composite resilience/adaptation measure that reflects the most relevant outcomes to resilience/adaptation across psychosocial and neurobehavioral functions, as well as neurocognitive and spaceflight-relevant operational performance. To achieve this, group consensus was attained from subject matter experts to produce a rank-order of importance for each input variable. The final resilience/adaptation score included 36 variables that were collected across spaceflight analogs. As of 10/1/2021, the NSCOR project acquired data on n=27 subjects at ICARUS, n=16 at HERA, and n=18 at Neumayer. The COVID-19 pandemic delayed data acquisition at ICARUS and HERA.Among subjects studied to date, 99% of neural and neurobehavioral data (e.g., neuroimaging for structure and function, behavioral measures) as well as blood, saliva, and urine for biochemical assays have been acquired. For rodent models, Dr. Hensch’s laboratory has established biochemical and behavioral parameters reflecting confinement stress in social networks of mice for comparison to stress responses in the human spaceflight analog environments.Group social behaviors were measured with a Social Network Analysis (SNA) approach to define objective parameters associated with sociability and its plasticity by sex. This analytic approach may help identify a network of individuals who are more effective teammates or more likely to generate new social relationships. Data acquisition, biomarker assessment, and data quality control will continue through September 2022.

D F Dinges↗