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NASA NTRS2016

Pre-Mission Input Requirements to Enable Successful Sample Collection by A Remote Field/EVA Team

The FINESSE (Field Investigations to Enable Solar System Science and Exploration) team, part of the Solar System Exploration Virtual Institute (SSERVI), is a field-based research program aimed at generating strategic knowledge in preparation for human and robotic exploration of the Moon, near-Earth asteroids, Phobos and Deimos, and beyond. In contract to other technology-driven NASA analog studies, The FINESSE WCIS activity is science-focused and, moreover, is sampling-focused with the explicit intent to return the best samples for geochronology studies in the laboratory. We used the FINESSE field excursion to the West Clearwater Lake Impact structure (WCIS) as an opportunity to test factors related to sampling decisions. We examined the in situ sample characterization and real-time decision-making process of the astronauts, with a guiding hypothesis that pre-mission training that included detailed background information on the analytical fate of a sample would better enable future astronauts to select samples that would best meet science requirements. We conducted three tests of this hypothesis over several days in the field. Our investigation was designed to document processes, tools and procedures for crew sampling of planetary targets. This was not meant to be a blind, controlled test of crew efficacy, but rather an effort to explicitly recognize the relevant variables that enter into sampling protocol and to be able to develop recommendations for crew and backroom training in future endeavors.

FINESSE↗

NASA NTRS2014

Defining Reliability and Robustness from a Human Factors Perspective

A human factors team was tasked with assessing best practices for developing a crewed space vehicle that is both reliable and robust. The team identified two broad dimensions of human factors are relevant to system design. Namely, the attributes of the product, and the processes used to develop the product. The “product” includes hardware, software, documentation, training systems, and procedures throughout all phases of the system life, including construction, testing, operation and maintenance. Three product attributes relevant to robustness are the extent to which task demands are within human capabilities, the capacity of the system to cope with unanticipated human actions, and the ability of the system to make use of unique human capabilities during non-routine situations. The “process” dimension of human factors relates to the activities that start in the early stages of design, and continue throughout the life of the system. There are, of course, no guarantees that a formal consideration of human factors throughout the design process will identify all the relevant human issues. In the absence of such a consideration, however, problems are virtually assured.

Hobbs, Alan↗

NASA NTRS2024

m:N Working Group: Meeting Summary March 2024

From March 26th to 28th, 2024 the m:N UAS working group and its subgroups (Evaluation Methodologies, Exceptions/Interventions, and Initial Operating Capability for Airspace Integration) met at SAIC in Washington, D.C. for an in-person meeting. The subgroups meet virtually throughout the year, and twice a year participants from all the subgroups come together to further identify and discuss challenges and paths forward for incorporating UAS into the airspace. The m:N UAS working group is run by Jay Shively (Adaptive Aerospace) and Andy Thurling (DroneUp) and is comprised of members from government, industry, and academia in an effort to identify and reduce barriers to m:N operations. This includes identifying requirements, use cases, metrics, and the development of white papers to support organizations including the FAA, RTCA, and ASTM. A change from last year, the Large UAS and HAPS sub working groups have disbanded while the sUAS working group continues independently, currently working on a white paper titled Personnel Selection, Roles, and Training for sUAS. For 2024 the m:N sub working groups have been refocused to cover evaluation methodologies, interventions/exceptions, and initial operating capability for airspace integration; with the premise that the outcomes from these subgroups will be white papers. These white papers can inform one another to ultimately become a master whitepaper. Each subgroup lead is called out below: Evaluation Methodologies Subgroup Jay Shively, Adaptive Aerospace Interventions/Exceptions Subgroup Andy Thurling, DroneUp (Lead) Initial Operating Capability for Airspace Integration Subgroup Andy Lacher, NASA (Lead)

m:N operations↗

NASA NTRS2008

Venus Quadrangle Geological Mapping: Use of Geoscience Data Visualization Systems in Mapping and Training

We are currently investigating new technological developments in computer visualization and analysis in order to assess their importance and utility in planetary geological analysis and mapping [1,2]. Last year we reported on the range of technologies available and on our application of these to various problems in planetary mapping [3]. In this contribution we focus on the application of these techniques and tools to Venus geological mapping at the 1:5M quadrangle scale. In our current Venus mapping projects we have utilized and tested the various platforms to understand their capabilities and assess their usefulness in defining units, establishing stratigraphic relationships, mapping structures, reaching consensus on interpretations and producing map products. We are specifically assessing how computer visualization display qualities (e.g., level of immersion, stereoscopic vs. monoscopic viewing, field of view, large vs. small display size, etc.) influence performance on scientific analysis and geological mapping. We have been exploring four different environments: 1) conventional desktops (DT), 2) semi-immersive Fishtank VR (FT) (i.e., a conventional desktop with head-tracked stereo and 6DOF input), 3) tiled wall displays (TW), and 4) fully immersive virtual reality (IVR) (e.g., "Cave Automatic Virtual Environment," or Cave system). Formal studies demonstrate that fully immersive Cave environments are superior to desktop systems for many tasks [e.g., 4].

Head, James W.↗

NASA NTRS1998

Measures and Interpretations of Vigilance Performance: Evidence Against the Detection Criterion

Operators' performance in a vigilance task is often assumed to depend on their choice of a detection criterion. When the signal rate is low this criterion is set high, causing the hit and false alarm rates to be low. With increasing time on task the criterion presumably tends to increase even further, thereby further decreasing the hit and false alarm rates. Virtually all of the empirical evidence for this simple interpretation is based on estimates of the bias measure Beta from signal detection theory. In this article, I describe a new approach to studying decision making that does not require the technical assumptions of signal detection theory. The results of this new analysis suggest that the detection criterion is never biased toward either response, even when the signal rate is low and the time on task is long. Two modifications of the signal detection theory framework are considered to account for this seemingly paradoxical result. The first assumes that the signal rate affects the relative sizes of the variances of the information distributions; the second assumes that the signal rate affects the logic of the operator's stopping rule. Actual or potential applications of this research include the improved training and performance assessment of operators in areas such as product quality control, air traffic control, and medical and clinical diagnosis.

Balakrishnan, J. D.↗

NASA NTRS2014

Simulation Technology at NASA

NASA Ames Research Center is home to several high-fidelity research flight and air-traffic control simulation facilities which, together with an experienced workforce, produce high-quality research data and findings that have proven to be applicable in the real world. These assets include the Vertical Motion Simulator (VMS), Crew Vehicle Systems Research Facility (CVSRF), Future Flight Central (FFC) air traffic control tower simulator, and several air-traffic control (ATC) simulators. The VMS combines a high-fidelity simulation capability with an adaptable simulation environment, enabling customization for numerous human-in-the-loop research applications. The distinctive feature of the VMS is its unparalleled large amplitude, high-fidelity motion capability. In over 30 years of continuous operation, the VMS has contributed significantly to the body of knowledge in a range of disciplines directly benefiting several aerospace programs and flight safety, including the design and development of flight control systems for the Joint Strike Fighter, Space Shuttle Orbiter, and rotorcraft. It continues to be used for researching new vehicle configurations, vehicle control and safety, transfer-of-training, etc., by NASA, other government agencies, and Industry.The CVSRF includes two motion-based flight simulators: a Boeing 747-400 full flight simulator and the reconfigurable Advanced Concepts Flight Simulator (ACFS). These simulators are primarily used to research air-traffic management concepts and procedures, advanced navigation and avionics concepts, and cockpit human factors. FFC is a full-sized control tower simulator with a 360-degree external field-of-view display system and reconfigurable system architecture. FFC and the ATC simulators are used for testing air-traffic management automation and decision support tools and demonstrate their feasibility in a realistic environment prior to technology transfer for implementation in the National Airspace System (NAS).To support integrated simulations and flight-tests for NASA's Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) Project, NASA developed a distributed test environment incorporating Live, Virtual, Constructive, (LVC) concepts. Development of the software enabling the LVC is conducted primarily at the Distributed Simulation Research Lab (DSRL) at NASA Ames. The LVC components provide the core infrastructure supporting simulation of UAS operations by integrating live and virtual aircraft in a realistic air traffic environment. This provides the ability to conduct tests more efficiently by promoting the use of existing distributed assets. The LVC infrastructure was used in several human-in-the-loop simulations to evaluate acceptance of Detect and Avoid (DAA) advisories used by UAS pilots to maintain well clear of other virtual traffic and to negotiate maneuvers with air traffic control. It is currently being used to support testing of self-separation algorithms between unmanned and manned aircraft in live flight. Further simulations with more comprehensive air traffic scenarios mixing live and virtual aircraft is planned.In the current fiscal environment, maintaining and upgrading these high-fidelity simulation assets and retaining the skilled workforce necessary to meet future research needs is the primary non-technical challenge.

CVSRF↗

NASA NTRS2014

Using Tests Designed to Measure Individual Sensorimotor Subsystem Perfomance to Predict Locomotor Adaptability

Astronauts experience sensorimotor disturbances during the initial exposure to microgravity and during the readapation phase following a return to a gravitational environment. These alterations may lead to disruption in the ability to perform mission critical functions during and after these gravitational transitions. Astronauts show significant inter-subject variation in adaptive capability following gravitational transitions. The way each individual's brain synthesizes the available visual, vestibular and somatosensory information is likely the basis for much of the variation. Identifying the presence of biases in each person's use of information available from these sensorimotor subsystems and relating it to their ability to adapt to a novel locomotor task will allow us to customize a training program designed to enhance sensorimotor adaptability. Eight tests are being used to measure sensorimotor subsystem performance. Three of these use measures of body sway to characterize balance during varying sensorimotor challenges. The effect of vision is assessed by repeating conditions with eyes open and eyes closed. Standing on foam, or on a support surface that pitches to maintain a constant ankle angle provide somatosensory challenges. Information from the vestibular system is isolated when vision is removed and the support surface is compromised, and it is challenged when the tasks are done while the head is in motion. The integration and dominance of visual information is assessed in three additional tests. The Rod & Frame Test measures the degree to which a subject's perception of the visual vertical is affected by the orientation of a tilted frame in the periphery. Locomotor visual dependence is determined by assessing how much an oscillating virtual visual world affects a treadmill-walking subject. In the third of the visual manipulation tests, subjects walk an obstacle course while wearing up-down reversing prisms. The two remaining tests include direct measures of knee and ankle proprioception and a functional movement assessment that screens for movement restrictions and asymmetries. To assess each subject's locomotor adaptability subjects walk for twenty minutes on a treadmill that oscillates laterally at 0.3 Hz. Throughout the test metabolic cost provides a measure of exertion and step frequency provides a measure of stability. Additionally, at four points during the perturbation period, reaction time tests are used to probe changes in the amount of mental effort being used to perform the task. As with the adaptive capability observed in astronauts during gravitational transitions, our data shows significant variability between subjects. To aid in the analysis of the results, custom software tools have been developed to enhance in the visualization of the large number of output variables. Preliminary analyses of the data collected to date do not show a strong relationship between adaptability and any single predictor variable. Analysis continues to identify a multifactorial predictor outcome "signature" that do inform us of locomotor adaptability.

Peters, B. T.↗

NASA NTRS2016

Holodeck Testbed Project

The main objective of the Holodeck Testbed is to create a cost effective, realistic, and highly immersive environment that can be used to train astronauts, carry out engineering analysis, develop procedures, and support various operations tasks. Currently, the Holodeck testbed allows to step into a simulated ISS (International Space Station) and interact with objects; as well as, perform Extra Vehicular Activities (EVA) on the surface of the Moon or Mars. The Holodeck Testbed is using the products being developed in the Hybrid Reality Lab (HRL). The HRL is combining technologies related to merging physical models with photo-realistic visuals to create a realistic and highly immersive environment. The lab also investigates technologies and concepts that are needed to allow it to be integrated with other testbeds; such as, the gravity offload capability provided by the Active Response Gravity Offload System (ARGOS). My main two duties were to develop and animate models for use in the HRL environments and work on a new way to interface with computers using Brain Computer Interface (BCI) technology. On my first task, I was able to create precise computer virtual tool models (accurate down to the thousandths or hundredths of an inch). To make these tools even more realistic, I produced animations for these tools so they would have the same mechanical features as the tools in real life. The computer models were also used to create 3D printed replicas that will be outfitted with tracking sensors. The sensor will allow the 3D printed models to align precisely with the computer models in the physical world and provide people with haptic/tactile feedback while wearing a VR (Virtual Reality) headset and interacting with the tools. Getting close to the end of my internship the lab bought a professional grade 3D Scanner. With this, I was able to replicate more intricate tools at a much more time-effective rate. The second task was to investigate the use of BCI to control objects inside the hybrid reality ISS environment. This task looked at using an Electroencephalogram (EEG) headset to collect brain state data that could be mapped to commands that a computer could execute. On this Task, I had a setback with the hardware, which stopped working and was returned to the vendor for repair. However, I was still able to collect some data, was able to process it, and started to create correlation algorithms between the electrical patterns in the brain and the commands we wanted the computer to carry out. I also carried out a test to investigate the comfort of the headset if it is worn for a long time. The knowledge gained will benefit me in my future career. I learned how to use various modeling and programming tools that included Blender, Maya, Substance Painter, Artec Studio, Github, and Unreal Engine 4. I learned how to use a professional grade 3D scanner and 3D printer. On the BCI Project I learned about data mining and how to create correlation algorithms. I also supported various demos including a live demo of the hybrid reality lab capabilities at ComicPalooza. This internship has given me a good look into engineering at NASA. I developed a more thorough understanding of engineering and my overall confidence has grown. I have also realized that any problem can be fixed, if you try hard enough, and as an engineer it is your job to not only fix problems but to embrace coming up with solutions to those problems.

Arias, Adriel↗

NASA NTRS1992

Dark focus of accommodation as dependent and independent variables in visual display technology

When independent stimuli are available for accommodation, as in the dark or under low contrast conditions, the lens seeks its resting position. Individual differences in resting positions are reliable, under autonomic control, and can change with visual task demands. We hypothesized that motion sickness in a flight simulator might result in dark focus changes. Method: Subjects received training flights in three different Navy flight simulators. Two were helicopter simulators entailed CRT presentation using infinity optics, one involved a dome presentation of a computer graphic visual projection system. Results: In all three experiments there were significant differences between dark focus activity before and after simulator exposure when comparisons were made between sick and not-sick pilot subjects. In two of these experiments, the average shift in dark focus for the sick subjects was toward increased myopia when each subject was compared to his own baseline. In the third experiment, the group showed an average shift outward of small amount and the subjects who were sick showed significantly less outward movement than those who were symptom free. Conclusions: Although the relationship is not a simple one, dark focus changes in simulator sickness imply parasympathetic activity. Because changes can occur in relation to endogenous and exogenous events, such measurement may have useful applications as dependent measures in studies of visually coupled systems, virtual reality systems, and space adaptation syndrome.

Jones, Sherrie↗

NASA NTRS2015

A Model for Effective Professional Development of Formal Science Educators

The Lunar Workshops for Educators (LWE) series was developed by the Lunar Reconnaissance Orbiter (LRO) education team in 2010 to provide professional development on lunar science and exploration concepts for grades 6-9 science teachers. Over 300 educators have been trained to date. The LWE model incorporates best practices from pedagogical research of science education, thoughtful integration of scientists and engineer subject matter experts for both content presentations and informal networking with educators, access to NASA-unique facilities, hands-on and data-rich activities aligned with education standards, exposure to the practice of science, tools for addressing common misconceptions, follow-up with participants, and extensive evaluation. Evaluation of the LWE model via pre- and post-assessments, daily workshop surveys, and follow-up surveys at 6-month and 1-year intervals indicate that the LWE are extremely effective in increasing educators' content knowledge, confidence in incorporating content into the classroom, understanding of the practice of science, and ability to address common student misconceptions. In order to address the efficacy of the LWE model for other science content areas, the Dynamic Response of Environments at Asteroids, the Moon, and moons of Mars (DREAM2) education team, funded by NASA's Solar System Exploration Research Virtual Institute, developed and ran a pilot workshop called Dream2Explore at NASA's Goddard Space Flight Center in June, 2015. Dream2Explore utilized the LWE model, but incorporated content related to the science and exploration of asteroids and the moons of Mars. Evaluation results indicate that the LWE model was effectively used for educator professional development on non-lunar content. We will present more detail on the LWE model, evaluation results from the Dream2Explore pilot workshop, and suggestions for the application of the model with other science content for robust educator professional development.

Orbiter↗

NASA NTRS2015

Examining Volcanic Terrains Using In Situ Geochemical Technologies; Implications for Planetary Field Geology

Regardless of the target destination for the next manned planetary mission, the crew will require technology with which to select samples for return to Earth. The six Apollo lunar surface missions crews had only the tools to enable them to physically pick samples up off the surface or from a boulder and store those samples for return to the Lunar Module and eventually to Earth. Sample characterization was dependent upon visual inspection and relied upon their extensive geology training. In the four decades since Apollo however, great advances have been made in traditionally laboratory-based instrument technologies that enable miniaturization to a field-portable configuration. The implications of these advancements extend past traditional terrestrial field geology and into planetary surface exploration. With tools that will allow for real-time geochemical analysis, an astronaut can better develop a series of working hypotheses that are testable during surface science operations. One such technology is x-ray fluorescence (XRF). Traditionally used in a laboratory configuration, these instruments have now been developed and marketed commercially in a field-portable mode. We examine this technology in the context of geologic sample analysis and discuss current and future plans for instrument deployment. We also discuss the development of the Chromatic Mineral Identification and Surface Texture (CMIST) instrument at the NASA Goddard Space Flight Center (GSFC). Testing is taking place in conjunction with the RIS4E (Remote, In Situ, and Synchrotron Studies for Science and Exploration) SSERVI (Solar System Exploration and Research Virtual Institute) team activities, including field testing at Kilauea Volcano, HI..

Young, K. E.↗

NASA NTRS2005

Predictive Interfaces for Long-Distance Tele-Operations

We address the development of predictive tele-operator interfaces for humanoid robots with respect to two basic challenges. Firstly, we address automating the transition from fully tele-operated systems towards degrees of autonomy. Secondly, we develop compensation for the time-delay that exists when sending telemetry data from a remote operation point to robots located at low earth orbit and beyond. Humanoid robots have a great advantage over other robotic platforms for use in space-based construction and maintenance because they can use the same tools as astronauts do. The major disadvantage is that they are difficult to control due to the large number of degrees of freedom, which makes it difficult to synthesize autonomous behaviors using conventional means. We are working with the NASA Johnson Space Center's Robonaut which is an anthropomorphic robot with fully articulated hands, arms, and neck. We have trained hidden Markov models that make use of the command data, sensory streams, and other relevant data sources to predict a tele-operator's intent. This allows us to achieve subgoal level commanding without the use of predefined command dictionaries, and to create sub-goal autonomy via sequence generation from generative models. Our method works as a means to incrementally transition from manual tele-operation to semi-autonomous, supervised operation. The multi-agent laboratory experiments conducted by Ambrose et. al. have shown that it is feasible to directly tele-operate multiple Robonauts with humans to perform complex tasks such as truss assembly. However, once a time-delay is introduced into the system, the rate of tele\ioperation slows down to mimic a bump and wait type of activity. We would like to maintain the same interface to the operator despite time-delays. To this end, we are developing an interface which will allow for us to predict the intentions of the operator while interacting with a 3D virtual representation of the expected state of the robot. The predictive interface anticipates the intention of the operator, and then uses this prediction to initiate appropriate sub-goal autonomy tasks.

Wheeler, Kevin R.↗

NASA NTRS1992

Beyond the cockpit: The visual world as a flight instrument

The use of cockpit instruments to guide flight control is not always an option (e.g., low level rotorcraft flight). Under such circumstances the pilot must use out-the-window information for control and navigation. Thus it is important to determine the basis of visually guided flight for several reasons: (1) to guide the design and construction of the visual displays used in training simulators; (2) to allow modeling of visibility restrictions brought about by weather, cockpit constraints, or distortions introduced by sensor systems; and (3) to aid in the development of displays that augment the cockpit window scene and are compatible with the pilot's visual extraction of information from the visual scene. The authors are actively pursuing these questions. We have on-going studies using both low-cost, lower fidelity flight simulators, and state-of-the-art helicopter simulation research facilities. Research results will be presented on: (1) the important visual scene information used in altitude and speed control; (2) the utility of monocular, stereo, and hyperstereo cues for the control of flight; (3) perceptual effects due to the differences between normal unaided daylight vision, and that made available by various night vision devices (e.g., light intensifying goggles and infra-red sensor displays); and (4) the utility of advanced contact displays in which instrument information is made part of the visual scene, as on a 'scene linked' head-up display (e.g., displaying altimeter information on a virtual billboard located on the ground).

Johnson, W. W.↗

NASA NTRS2015

NASAs Solar System Exploration Research Virtual Institute- Expanded Goals and More Partners

The NASA Solar System Exploration Research Virtual Institute (SSERVI) has been pursuing international partnerships since its inception as the NASA Lunar Science Institute (NLSI), in order to both leverage the science being done by its domestic member institutions as well as to help lunar science and exploration become a greater global endeavor. The international partners of the Institute have pursued a broad program of lunar science stimulated by scientific partnerships enabled by the SSERVI community. Furthermore, regional partnerships have been formed such as the new pan-European lunar science consortium, which promises both new scientific approaches and mission concepts. International partner membership requires long-term commitment from both the partner and SSERVI, together with tangible and specific plans for scientific interaction that will produce results of mutual benefit to both the institute's U.S. Teams and the international partner. International partners are invited to participate in all aspects of the Institute's activities and programs, on a basis of no exchange of funds. Through these activities, SSERVI researchers and international partners participate in sharing ideas, information, and data arising from their respective research efforts, and contribute to the training of young scientists. This talk will present an overview of the Institute and the international nodes. We will also discuss the various processes to become a SSERVI partner as well as the opportunities available for collaborations with the SSERVI national teams.

SSERVI↗

NASA NTRS2014

Spinoff 2013

Topics covered include: Innovative Software Tools Measure Behavioral Alertness; Miniaturized, Portable Sensors Monitor Metabolic Health; Patient Simulators Train Emergency Caregivers; Solar Refrigerators Store Life-Saving Vaccines; Monitors Enable Medication Management in Patients' Homes; Handheld Diagnostic Device Delivers Quick Medical Readings; Experiments Result in Safer, Spin-Resistant Aircraft; Interfaces Visualize Data for Airline Safety, Efficiency; Data Mining Tools Make Flights Safer, More Efficient; NASA Standards Inform Comfortable Car Seats; Heat Shield Paves the Way for Commercial Space; Air Systems Provide Life Support to Miners; Coatings Preserve Metal, Stone, Tile, and Concrete; Robots Spur Software That Lends a Hand; Cloud-Based Data Sharing Connects Emergency Managers; Catalytic Converters Maintain Air Quality in Mines; NASA-Enhanced Water Bottles Filter Water on the Go; Brainwave Monitoring Software Improves Distracted Minds; Thermal Materials Protect Priceless, Personal Keepsakes; Home Air Purifiers Eradicate Harmful Pathogens; Thermal Materials Drive Professional Apparel Line; Radiant Barriers Save Energy in Buildings; Open Source Initiative Powers Real-Time Data Streams; Shuttle Engine Designs Revolutionize Solar Power; Procedure-Authoring Tool Improves Safety on Oil Rigs; Satellite Data Aid Monitoring of Nation's Forests; Mars Technologies Spawn Durable Wind Turbines; Programs Visualize Earth and Space for Interactive Education; Processor Units Reduce Satellite Construction Costs; Software Accelerates Computing Time for Complex Math; Simulation Tools Prevent Signal Interference on Spacecraft; Software Simplifies the Sharing of Numerical Models; Virtual Machine Language Controls Remote Devices; Micro-Accelerometers Monitor Equipment Health; Reactors Save Energy, Costs for Hydrogen Production; Cameras Monitor Spacecraft Integrity to Prevent Failures; Testing Devices Garner Data on Insulation Performance; Smart Sensors Gather Information for Machine Diagnostics; Oxygen Sensors Monitor Bioreactors and Ensure Health and Safety; Vision Algorithms Catch Defects in Screen Displays; and Deformable Mirrors Capture Exoplanet Data, Reflect Lasers.

Source record↗

NASA NTRS2024

Assessments of Physiology and Cognition in Hybrid-Reality Environments (APACHE) – A VR “Sandbox” for Planetary Spacewalk Research

Human Performance↗

NASA NTRSDate not supplied

Assessments of Physiology and Cognition in Hybrid-Reality Environments (APACHE)

NASA is planning to return to the Moon in the mid-2020s as a stepping stone to Mars missions in the 2030s. Spacewalks, or extravehicular activities (EVAs), performed on the Moon and Mars will differ in a variety of ways from those that have been performed in decades past. NASA has identified multiple risks to human health and performance associated with a crewed mission to Mars, especially those associated with exploration EVAs which are expected to be a primary mission activity. Crew may be expected to conduct up to 24 hours of EVA per person per week, where the likelihood of injury and/or mental mistakes are increased compared to ground-based training or current microgravity EVAs and the consequences of which can be catastrophic. Current test environments for exploration EVA research and technology development are large, costly facilities that are limited in their availability or capabilities. Spacesuit testing in a reduced gravity environment such as NASA’s Neutral Buoyancy Laboratory, while a good representation of the crew’s physical workload during exploration EVAs, typically has small datasets and is difficult to integrate physiological sensors or other types of crew performance measures. Meanwhile, scientific field-based testing such as NASA’s Desert Research and Technology Studies offers an operationally relevant environment for exploration EVAs, particularly for cognitive workload, but is also limited by small datasets, lack of a pressurized spacesuit, and obtrusive measures. The limitations of current analogs for exploration EVAs identify a need for a new test environment that can approximate both the physical and cognitive demands associated with exploration EVAs to enable rapid, controlled, and repeatable evaluations of human health and performance risks of exploration missions. In response, the Human Physiology, Performance, Protection, and Operations Laboratory (H-3PO) at NASA Johnson Space Center has developed a hybrid reality exploration EVA analog named the Assessments of Physiology And Cognition in Hybrid-reality Environments (APACHE) to address these limitations using a combination of virtual, physical, and hybrid reality techniques. The APACHE facility resides at NASA Johnson Space Center and serves as a large “sandbox” for EVA research and simulation. At its center is a roughly 15x20ft space surrounded by a 14” tall sandbox partially filled with lunar regolith simulant to emulate the physical feeling of walking on a planetary surface and to allow for simulated geology operations. Nearby, a curved passive treadmill (Skillmill Connect, Technogym, Fairfield, NJ) and an omnidirectional treadmill (Infinadeck, Infinadeck, Rocklin, CA) are included to enable exploration of these large virtual environments while also imposing the physical demands, representative timelines, and cognitive burdens required to navigate and traverse these distances during exploration EVA. A 6DOF motion platform is used to simulate rover operations and supports various human performance evaluations and associated risks. Lastly, APACHE can support two extravehicular (EV) crewmembers working in tandem. A computer workstation is located nearby and also supports an intravehicular (IV) crewmember as part of a full mission simulation. The IV crewmember has direct video and audio communication with the EV crew in VR to provide operational and procedural support. The software used in APACHE was created by the JSC Engineering Directorate, in partnership with Buendea, powered by a custom Unreal Engine 5 (UE5.3, Epic Games) project. APACHE currently utilizes the HTC Vive Pro Eye in a wireless configuration for VR simulations. There are two virtual environments that subjects can explore within APACHE, a Lunar and Martian surface. The virtual Lunar surface was created from LIDAR data of the Lunar South Pole to create roughly 16 sq km of explorable terrain. The virtual Martian surface contains roughly 400 sq km of explorable terrain derived from Mars Reconnaissance Orbiter LIDAR data of the Jezero Crater. The immersion and related cognitive burdens of conducting a planetary EVA is simulated through a series of EVA-relevant tasks performed in the VR environment, using these high-fidelity visual representations. Additionally, APACHE includes biosensor driven informatics, such as real-time heart rate monitoring and/or derived values from model simulations, for active monitoring by the EV crew and added cognitive demand. A “Wizard of Oz” control panel enables test operators to activate contingency events such as simulated spacesuit malfunctions, loss of communications, and/or limited visibility. Embedded performance measures such as accuracy, completeness, and execution time have been developed for various exploration tasks to objectively quantify crew performance during an EVA and compare impacts to performance when different environmental stressors, both physical and cognitive, are added to or removed from the simulation. Additionally, validated cognitive and operational performance measures such as the Digit Symbol Substitution Task have been recreated and embedded in VR for direct and relatively unobtrusive measurement of motor perception. The APACHE environment currently supports multiple research studies at NASA. Examples include the CHAPEA project, a series of simulated year-long missions on Mars by a 4-person crew; and the CO2 Contingency Walk Back Study, an investigation of elevated CO2 exposure on crew performance during a contingency EVA scenario. APACHE also provides a test environment to support the development of the Crew State and Risk Model, which is a collection of individualized, mathematical models of crew physical and cognitive state; and the Personalized EVA Informatics and Decision Support system, an operational tool for flight controllers, and eventually a self-reliant Martian crew, to make biomedically-informed decisions in real-time to optimize the EVA planning and execution with respect to crew health and performance. Some technical challenges associated with developing the APACHE environment, as well as current limitations, include VR limitless natural walking with a hybrid spacesuit simulator, optimizing performance for wireless PC VR streaming while maintaining a high degree of visual fidelity, and the integration of various physiological (metabolic masks) and psychometric (eye tracking) sensors with the VR headset.

Human Performance↗

NASA NTRS2018

Increasing Flight Software Reuse with OpenSatKit

In January 2015 the NASA Goddard Space Flight Center (GSFC) released the Core Flight System (cFS) as open source under the NASA Open Source Agreement (NOSA) license. The cFS is based on flight software (FSW) developed for 12 spacecraft spanning nearly two decades of effort and it can provide about a third of the FSW functionality for a low-earth orbiting scientific spacecraft. The cFS is a FSW framework that is portable, configurable, and extendable using a product line deployment model. However, the components are maintained separately so the user must configure, integrate, and deploy them as a cohesive functional system. This can be very challenging especially for organizations such as universities building cubesats that have minimal experience developing FSW. Supporting universities was one of the primary motivators for releasing the cFS under NOSA. This paper describes the OpenSatKit that was developed to address the cFS deployment challenges and to serve as a cFS training platform for new users. It provides a fully functional out-of-the box software system that includes NASA's cFS, Ball Aerospace's command and control system COSMOS, and a NASA dynamic simulator called 42. The kit is freely available since all of the components have been released as open source. The kit runs on a Linux platform, includes 8 cFS applications, several kit-specific applications, and built in demos illustrating how to use key application features. It also includes the software necessary to port the cFS to a Raspberry Pi and instructions for configuring COSMOS to communicate with the target. All of the demos and test scripts can be rerun unchanged with the cFS running on the Raspberry Pi. The cFS uses a 3-tiered layered architecture including a platform abstraction layer, a Core Flight Executive (cFE) middle layer, and an application layer. Similar to smart phones, the cFS application layer is the key architectural feature for users to extend the FSW functionality to meet their mission-specific requirements. The platform abstraction layer and the cFE layers go a step further than smart phones by providing a platform-agnostic Application Programmer Interface (API) that allows applications to run unchanged on different platforms. OpenSatKit can serve two significant architectural roles that will further help the adoption of the cFS and help create a community of users that can share assets. First, the kit is being enhanced to automate the integration of applications with the goal of creating a virtual cFS "App Store".. Second, a platform certification test suite can be developed that would allow users to verify the port of the cFS to a new platform. This paper will describe the current state of these efforts and future plans.

Computer Programming and Software↗