Results for “Human in the Loop” — Page 12

NASA NTRS2017

Airspace Technology Demonstration 2 (ATD-2) Integrated Surface and Airspace Simulation - Experiment Plan

This presentation describes the overview of the ATD-2 project and the integrated simulation of surface and airspace to evaluate the procedures of IADS system and evaluate surface metering capabilities via a high-fidelity human-in-the-loop simulation. Two HITL facilities, Future Flight Central (FFC) and Airspace Operations Laboratory (AOL), are integrated for simulating surface operations of the Charlotte-Douglas International Airport (CLT) and airspace in CLT TRACON and Washington Center.

ATD-2↗

NASA NTRS2012

Orion ECLSS/Suit System - Ambient Pressure Integrated Suit Test

The Ambient Pressure Integrated Suit Test (APIST) phase of the integrated system testing of the Orion Vehicle Atmosphere Revitalization System (ARS) technology was conducted for the Multipurpose Crew Vehicle (MPCV) Program within the National Aeronautics and Space Administration (NASA) Exploration Systems Mission Directorate. Crew and Thermal Systems Division performed this test in the eleven-foot human-rated vacuum chamber at the NASA Johnson Space Center. This testing is the first phase of suit loop testing to demonstrate the viability of the Environmental Control and Life Support System (ECLSS) being developed for Orion. APIST is the first in a series, which will consist of testing development hardware including the Carbon dioxide and Moisture Removal Amine Swing-bed (CAMRAS) and the air revitalization loop fan with human test subjects in pressure suits at varying suit pressures. Follow-on testing, to be conducted in 2013, will utilize the CAMRAS and a development regulator with human test subjects in pressure suits at varying cabin and suit pressures. This paper will discuss the results and findings of APIST and will also discuss future testing.

Barido, Richard A.↗

NASA NTRSDate not supplied

Usability Evaluation of Fleet Management Interface for High Density Vertiplex Environments

To meet the rising demand for an Advanced Air Mobility (AAM) (i.e. urban and rural unmanned aircraft systems) ecosystem, the NASA Aeronautics Research Mission Directorate (ARMD) is hosting a series of simulations and flight tests under the High Density Vertiplex sub-project (HDV) to prototype and study the effectiveness AAM capabilities under various operational contexts. HDV aims to develop an integrated automation architecture to support terminal area flight operations. The HDV simulations and flight tests address safety, integration, and operational challenges, while integrated systems and software demonstrate design readiness, robustness, and interoperability. During the initial HDV simulation in 2021, a prototype traffic management tool developed by NASA called the Fleet Management Interface (FMI) was tested. FMI was designed to introduce an advanced level of human-automation interaction to aid both Ground Control Station Operators (GCSOs) and Fleet Managers (FMs) in remotely managing flights under their ownership. In a human-in-the-loop simulation, a usability study was conducted with the FMI to identify optimal approaches for displaying information to human operators using subjective measures of usability, workload, situation awareness, risk, and trust, along with qualitative feedback. This study consisted of task analysis in which GCSO and FM subjects used an Urban Air Mobility (UAM) environment to develop and execute a plan for two different traffic scenarios of remotely controlled vehicles. In each scenario, a remotely controlled vehicle completed a takeoff, active flight, and landing sequence while simulated traffic flew in the background at a rate of 20 operations per hour. In the first scenario, the controlled vehicle flew a nominal route with takeoff and landing at the same vertiport. In the second scenario, the controlled vehicle started on the nominal route, then diverted to an unplanned location mid-flight. Results showed that self- reported performance, usability, trust, and situation awareness ratings of FMI were moderately to strongly high. There were small differences between scenarios, with Scenario 2 being perceived as more unstable, complex, variable, risky, and potentially harmful than Scenario 1. Furthermore, participants described improvements that could be made to create a better user experience. For example, users suggested customizable interfaces to accommodate information display preferences, and the ability to review routes before assigning them. The results from this study will inform future development of the FMI with the end goal of creating a reference automation tool for airspace management procedures in AAM. The FMI could serve to reduce dependency on traditional air navigation services through increased automation in high density vertiplex environments.

Fleet manager↗

NASA NTRS2013

Analysis of Traffic Conflicts in a Mixed-Airspace Evaluation of Airborne Separation Assurance

A pair of human-in-the-loop simulation evaluations of a distributed air/ground separation assurance system have been conducted to investigate the function allocation between humans and automation systems as well as ground-based and airborne agents in the Next Generation Air Transportation System and beyond. This paper focuses on an analysis of certain critical conflicts observed between self-separating aircraft and ground-managed traffic in the same airspace. The principal cause of each conflict is identified and potential mitigations are discussed, such as: the sharing of trajectory intent information between the ground and the air; more cautious trajectory planning by the self-separating aircraft; and more equitable rules-of-the-road between the self-separating aircraft and ground-managed aircraft. This analysis will inform the ongoing design of an airborne separation assurance automation tool.

Lewis, Timothy A.↗

NASA NTRS2026

Overview of Past and Future EVA Suit Testing and Training in Chamber B at NASA JSC

The Crew and Thermal System Division’s Chamber B has received an increase in demand for next generation suit testing. Chamber B is the National Aeronautics and Space Administration (NASA) Johnson Space Center’s only human-rated thermal vacuum (TVAC) chamber. Historically it was used in Gemini, Apollo, Skylab, Shuttle, and the International Space Station (ISS) suit tests. Recently, the chamber has been returned to service with new capabilities for suit testing. In 2023, The Exploration Extravehicular Mobility Unit (xEMU) underwent a 5-day, extensive thermal vacuum test that included both a full-bodied Exploration Pressure Garment Suit (xPGS) as well as a high fidelity Short xEMU. SpaceX has also used the chamber for human-in-the-loop (HITL) qualification and acceptance testing on their flight Polaris Dawn suits for the first-ever commercial extravehicular activity (EVA). Current chamber Manlock B2 upgrades include the support of two test subjects at the same time with updated chamber interface and support systems for the next generation of suits. This paper will discuss the history of spacesuit testing in the chamber, the recent testing for commercial and NASA suits, and upgrades to accommodate new test requirements.

Human-in-the-loop↗

NASA NTRS2026

Overview of Past and Future EVA Suit Testing and Training in Chamber B at NASA JSC

The Crew and Thermal System Division’s Chamber B has received an increase in demand for next generation suit testing. Chamber B is the National Aeronautics and Space Administration (NASA) Johnson Space Center’s only human-rated thermal vacuum (TVAC) chamber. Historically it was used in Gemini, Apollo, Skylab, Shuttle, and the International Space Station (ISS) suit tests. Recently, the chamber has been returned to service with new capabilities for suit testing. In 2023, The Exploration Extravehicular Mobility Unit (xEMU) underwent a 5-day, extensive thermal vacuum test that included both a full-bodied Exploration Pressure Garment Suit (xPGS) as well as a high fidelity Short xEMU. SpaceX has also used the chamber for human-in-the-loop (HITL) qualification and acceptance testing on their flight Polaris Dawn suits for the first-ever commercial extravehicular activity (EVA). Current chamber Manlock B2 upgrades include the support of two test subjects at the same time with updated chamber interface and support systems for the next generation of suits. This paper will discuss the history of spacesuit testing in the chamber, the recent testing for commercial and NASA suits, and upgrades to accommodate new test requirements.

Polaris Dawn↗

NASA NTRS2011

Allocation of Functions in a Far-Term Air Traffic Control Environment

A human-in-the-loop exploration of a ground-based automated separation assurance concept was conducted that involved the allocation of certain functions between humans and automation. This exploration included operations that were sustained for prolonged periods of time with high levels of traffic in the presence of convective weather and scheduling constraints. An investigation into the acceptability of the defined roles and performance of tasks was conducted where it was found that the participants rated the concept and allocation of functions with a high level of acceptability. However, issues were encountered with the automation related to the detection of and response to tactical conflicts. Lower ratings were given on account of these concerns, and it was found that a key contributor to the underlying problems was transitioning aircraft and the uncertainty of their trajectories. Stemming from those results, participants responded that they would rather have direct control over aircraft transitions as well as more control over the tactical conflict resolution automation. In contrast, participants responded that they would rather have the automation place aircraft back on trajectory, and perform weather avoidance and scheduling tasks.

Homola, Jeffrey↗

NASA NTRS2023

Using Virtual Reality to Envision Deployment of Spacesuit-Compatible Augmented Reality Displays for Lunar Surface Operations

The National Aeronautics and Space Administration (NASA) will soon land crew on the lunar surface to establish a sustainable presence and develop operational concepts for future long-duration missions. New technologies will be necessary to extend planning and execution capabilities for lunar surface activities. The Joint Augmented Reality Visual Informatics System (Joint AR) at NASA Johnson Space Center (JSC) is one such technology. Joint AR is a suit-mounted augmented reality (AR) display and compute system which facilitates unprecedented information exchange and data visualization capabilities between mission support operators and suited crew. This paper describes challenges associated with developing an AR technology for an envisioned work domain by applying a sociotechnical lens to the iterative testing and development of novel AR technology through virtual reality (VR). A foundational VR testbed was established, providing a high-fidelity approximation of the lunar surface and enabling testing of envisioned AR system features in parallel with real world product development. Using this environment, a series of human-in-the-loop experiments were conducted using VR to deploy a notional AR system supporting use cases envisioned for lunar exploration extravehicular activity (xEVA). Our findings indicate VR is a powerful and immersive tool for testing capabilities which extend beyond the limitations of current AR technology. Our VR testbed enables early testing of proposed system features, advancing identification of high-value features and driving present-day development of Joint AR. Future work directions are discussed, including lessons learned and a roadmap for an iterative research and development approach applying VR (among other testbeds) to accelerate Joint AR system maturation.

Augmented reality↗

NASA NTRSDate not supplied

HAT m:N Activity Overview

Since 2020, researchers from the Human Autonomy Teaming (HAT) Laboratory at NASA Ames Research Center have conducted human-in-the-loop (HITL) simulation research to study a new control paradigm for operations involving multiple remotely piloted aircraft systems (RPAS). Colloquially referred to as "m:N," this paradigm is characterized by multiple operators collaboratively controlling multiple vehicles between them. The m:N name expresses a ratio whereby m is the number of operators and N is the number of vehicles shared between them. In this presentation, HAT Lab researchers provide a high-level overview of the m:N studies that have been performed to-date. These include a study of the m:N concept of operations (CONOPS) and the attending roles and responsibilities ("ConOps/R&R Sim"), a study focused on contingency management involving dynamic, inter-operator transfers of vehicles ("Handoff Sim"), and a study examining the effects of pilot-ATC communication systems on workload ("UAM Comms Sim"). A selection of key results are provided. The presentation concludes with a brief discussion of planned research into m:N operations.

m:N↗

NASA NTRS2013

Pilot and Controller Evaluations of Separation Function Allocation in Air Traffic Management

Two human-in-the-loop simulation experiments were conducted in coordinated fashion to investigate the allocation of separation assurance functions between ground and air and between humans and automation. The experiments modeled a mixed-operations concept in which aircraft receiving ground-based separation services shared the airspace with aircraft providing their own separation service (i.e., self-separation). Ground-based separation was provided by air traffic controllers without automation tools, with tools, or by ground-based automation with controllers in a managing role. Airborne self-separation was provided by airline pilots using self-separation automation enabled by airborne surveillance technology. The two experiments, one pilot-focused and the other controller-focused, addressed selected key issues of mixed operations, assuming the starting point of current-day operations and modeling an emergence of NextGen technologies and procedures. In the controller-focused experiment, the impact of mixed operations on controller performance was assessed at four stages of NextGen implementation. In the pilot-focused experiment, the limits to which pilots with automation tools could take full responsibility for separation from ground-controlled aircraft were tested. Results indicate that the presence of self-separating aircraft had little impact on the controllers' ability to provide separation services for ground-controlled aircraft. Overall performance was best in the most automated environment in which all aircraft were data communications equipped, ground-based separation was highly automated, and self-separating aircraft had access to trajectory intent information for all aircraft. In this environment, safe, efficient, and highly acceptable operations could be achieved for twice today's peak airspace throughput. In less automated environments, reduced trajectory intent exchange and manual air traffic control limited the safely achievable airspace throughput and negatively impacted the maneuver efficiency of self-separating aircraft through high-density airspace. In a test of scripted conflicts with ground-managed aircraft, flight crews of self-separating aircraft prevented separation loss in all conflicts with detection time greater than one minute. In debrief, pilots indicated a preference for at least five minute's alerting notice and trajectory intent information on all aircraft. When intent information on ground-managed aircraft was available, self-separating aircraft benefited from fewer conflict alerts and fewer required deviations from trajectory-based operations.

Wing, David↗

NASA NTRS2015

T-38 Primary Flight Display Prototyping and HIVE Support Abstract & Summary

This fall I worked in EV3 within NASA's Johnson Space Center in The HIVE (Human Integrated Vehicles & Environments). The HIVE is responsible for human in the loop testing, getting new technologies in front of astronauts, operators, and users early in the development cycle to make the interfaces more human friendly. Some projects the HIVE is working on includes user interfaces for future spacecraft, wearables to alert astronauts about important information, and test beds to simulate mock missions. During my internship I created a prototype for T-38 aircraft displays using LabVIEW, learned how to use microcontrollers, and helped out with other small tasks in the HIVE. The purpose of developing a prototype for T-38 Displays in LabVIEW is to analyze functions of the display such as navigation in a cost and time effective manner. The LabVIEW prototypes allow Ellington Field AOD to easily make adjustments to the display before hardcoding the final product. LabVIEW was used to create a user interface for simulation almost identical to the real aircraft display. Goals to begin the T-38 PFD (Primary Flight Display) prototype included creating a T-38 PFD hardware display in a software environment, designing navigation for the menu's, incorporating vertical and horizontal navigation bars, and to add a heading bug for compass controls connected to the HSI (Horizontal Situation Indicator). To get started with the project, measurements of the entire display were taken. This enabled an accurate model of the hardware display to be created. Navigation of menu's required some exploration of different buttons on the display. The T-38 simulator and aircraft were used for examining the display. After one piece of the prototype was finished, another trip of to the simulator took place. This was done until all goals for the prototype were complete. Some possible integration ideas for displays in the near future are autopilot selection, touch screen displays, and crew member preferences. Complete navigation, control, and function customization will be achievable once a display is fully developed. Other than the T-38 prototyping, I spent time learning how to design small circuits and write code for them to function. This was done by adding electronic circuit components to breadboard and microcontroller then writing code to speak to those components through the microcontroller. I went through an Arduino starter kit to build circuits and code software that allowed the hardware to act. This work was planned to assist in a lighting project this fall but another solution was discovered for the lighting project. Other tasks that I assisted with, included hands on work such as mock-up construction/removal, logic analyzer repairs, and soldering with circuits. The unique opportunity to be involved work with NASA has significantly changed my educational and career goals. This opportunity has only opened the door to my career with engineering. I have learned over the span of this internship that I am fascinated by the type of work that NASA does. My desire to work in the aerospace industry has increased immensely. I hope to return to NASA to be more involved in the advancement of science, engineering, and spaceflight. My interests for my future education and career lie in NASA’s work - pioneering the future in space exploration, scientific discovery and aeronautics research.

Boniface, Andrew↗

NASA NTRS2014

Human-Automation Cooperation for Separation Assurance in Future NextGen Environments

A 2012 Human-In-The-Loop air traffic control simulation investigated a gradual paradigm-shift in the allocation of functions between operators and automation. Air traffic controllers staffed five adjacent high-altitude en route sectors, and during the course of a two-week experiment, worked traffic under different function-allocation approaches aligned with four increasingly mature NextGen operational environments. These NextGen time-frames ranged from near current-day operations to nearly fully-automated control, in which the ground systems automation was responsible for detecting conflicts, issuing strategic and tactical resolutions, and alerting the controller to exceptional circumstances. Results indicate that overall performance was best in the most automated NextGen environment. Safe operations were achieved in this environment for twice todays peak airspace capacity, while being rated by the controllers as highly acceptable. However, results show that sector operations were not always safe; separation violations did in fact occur. This paper will describe in detail the simulation conducted, as well discuss important results and their implications.

air traffic control↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

NASA NTRS2018

Do You See What I See? Interactive Visualization of Mission Design and Navigation

Mission Design and Navigation (MDNav) is an intensive process requiring advanced computational resources, expert human intuition, and many successive human-in-the-loop iterations to converge on acceptable trajectory designs or navigation solutions. The current bottleneck in MDNav is not the underlying computational algorithms but the human cognitive capacity to prune through a multitude of simulated results to select high-value candidates. One approach to alleviate this burden is through the judicious application of visualizations that allow humans to interactively ﬁlter data in multiple dimensions to reveal salient patterns and highlight divergences. When designed eﬃciently, such interactive visualizations should aid human operators to get familiar with data faster, visually observe correlations, and communicate ﬁndings more eﬀortlessly. In this work, we present three visualization case studies that have the potential to increase human operator eﬃciency in MDNav. While identifying the most critical “pain points” that operators face, and also working on potential solutions, we followed a human-centered design approach. We started with a series of interviews with potential users, and then rapidly created prototypes for alternative solutions, validated outcomes with feedback from users through out development of these proof of concept visualizations. With this survey of our current eﬀorts, we demonstrate the transformative capability of interactive data visualizations for improving mission development and operations, enabling operators to grow intuition, and communicating key concepts across diverse mission teams.

Arora, Nitin↗

NASA NTRS2006

Logistics Lessons Learned in NASA Space Flight

The Vision for Space Exploration sets out a number of goals, involving both strategic and tactical objectives. These include returning the Space Shuttle to flight, completing the International Space Station, and conducting human expeditions to the Moon by 2020. Each of these goals has profound logistics implications. In the consideration of these objectives,a need for a study on NASA logistics lessons learned was recognized. The study endeavors to identify both needs for space exploration and challenges in the development of past logistics architectures, as well as in the design of space systems. This study may also be appropriately applied as guidance in the development of an integrated logistics architecture for future human missions to the Moon and Mars. This report first summarizes current logistics practices for the Space Shuttle Program (SSP) and the International Space Station (ISS) and examines the practices of manifesting, stowage, inventory tracking, waste disposal, and return logistics. The key findings of this examination are that while the current practices do have many positive aspects, there are also several shortcomings. These shortcomings include a high-level of excess complexity, redundancy of information/lack of a common database, and a large human-in-the-loop component. Later sections of this report describe the methodology and results of our work to systematically gather logistics lessons learned from past and current human spaceflight programs as well as validating these lessons through a survey of the opinions of current space logisticians. To consider the perspectives on logistics lessons, we searched several sources within NASA, including organizations with direct and indirect connections with the system flow in mission planning. We utilized crew debriefs, the John Commonsense lessons repository for the JSC Mission Operations Directorate, and the Skylab Lessons Learned. Additionally, we searched the public version of the Lessons Learned Information System (LLIS) and verified that we received the same result using the internal version of LLIS for our logistics lesson searches. In conducting the research, information from multiple databases was consolidated into a single spreadsheet of 300 lessons learned. Keywords were applied for the purpose of sorting and evaluation. Once the lessons had been compiled, an analysis of the resulting data was performed, first sorting it by keyword, then finding duplication and root cause, and finally sorting by root cause. The data was then distilled into the top 7 lessons learned across programs, centers, and activities.

Evans, William A.↗

NASA NTRSDate not supplied

Modeling Spacesuit-Human Interaction for Injury Risk Identification

Performing functional tasks while inside of the space suit introduces additional ergonomic challenges which can lead to musculoskeletal stresses and injuries in astronauts. Computational modeling of the suit-body interaction can be used alongside human-in-the-loop testing to understand and mitigate these risks and potentially improve the work performance. In this work, a static rigid-body model of the human body was integrated with the space suit and the process is described. This model enables prediction of the resulting joint torques and musculoskeletal loading from a simulated extravehicular activity (EVA) task. For representative EVA tasks, joint torque and body angles were used as parameters to predict the muscle strength required to achieve the task, as well as the percentage of the general and astronaut-like population that could achieve that strength demand. Population strength capability can be used as an indicator of the difficulty of a task and the level of injury risk for the given task types and crew anthropometry. The sensitivity of the model to inputs such as body joint location within the space suit and individual anthropometry will also be evaluated. Future work will use a database of3D human body scans and the movements of the body inside the suit during different EVA tasks to identify potential soft tissue contact points. The specific locations and magnitudes of contacts between the body and suit are expected to identify risk of repetitive tissue contact stresses. Overall, this model will provide a new tool to structurally identify the injury risks of EVA tasks and evaluate alternate strategies to reduce injury risk.

Garima Gupta↗

NASA NTRSDate not supplied

Desert Research and Technology Studies (D-RATS) 2022 Quicklook Report

This report summarizes the Desert Research and Technology Studies (D-RATS) 2022 analog tests. BACKGROUND - Artemis Challenges – NASA’s concept of operations (ConOps) for the Artemis mission architecture brings new challenges for human exploration of the lunar surface, including: (1) Low-angle, natural lighting at lunar poles; and (2) Exploration sites that challenge communication with Earth. - International Partner Involvement – NASA is working with the Japan Aerospace Exploration Agency (JAXA) to scope mission & functional requirements for an Artemis Pressurized Rover (PR), which JAXA may provide. - Charter – HQ Exploration Systems Development Mission Directorate (ESDMD) Moon to Mars Architecture Development Office (M2MADO) Strategy and Architectures (SA) chartered the Human-in-the-Loop (HITL) test team to investigate Artemis architectural questions related to pressurized rover ConOps. - Rationale – to inform the NASA/JAXA pressurized rover study-agreement. PLAN - Objectives – Analog tests conducted in October 2022 by the D-RATS team addressed three high-level objectives: 1. Investigate pressurized rover (PR) ConOps and capabilities for Artemis exploration 2. Integrate with JAXA engineers & astronauts and incorporate JAXA PR design elements into testing. 3. Re-establish analog field-testing skills & capabilities with rovers to investigate Artemis architecture ConOps. - Secondary Objectives – Work with other groups to leverage D-RATS field test for additional objectives. 4. Work with the Public Affairs Office (PAO) to perform D-RATS public outreach activities. 5. Coordinate with the Human Physiology Performance Protection & Operations (H-3PO) team to facilitate in-field evaluation of human health and performance (HHP) objectives. 6. Share D-RATS field-site and assets with Lunar LTE Studies (Lunar LiTES) team, to aid their study of the use of 4G/LTE communication protocols and devices for astronauts and robotic nodes on the lunar surface. - Team – Fully integrated test team comprised of members from 5 NASA centers, JAXA, and the United States Geological Survey (USGS) - Location – Black Point Lava Flow, ~40 miles north of Flagstaff, AZ HIGH-LEVEL OBJECTIVES ACCOMPLISHED - Investigated Pressurized Rover ConOps & Capabilities for Artemis Exploration (Objective 1) - Completed testing with 4 crew pairs, each spending 3 days and 2 nights in the rover conducting Artemis PR dayin-the-life activities (2 JAXA astronauts, 2 JAXA engineers, 1 NASA astronaut, 3 NASA engineers). - Collected detailed objective & subjective data supporting 10 strategic questions related to Artemis PR operations. - Field geologists present in field observed rover operations & EVAs. - Science team in Houston MCC communicated directly with crew. - Demonstrated crew-led and MCC-led PR teleoperation use cases during EVAs. - Integrated with JAXA Engineers & Astronauts and Incorporated JAXA PR Design Elements into Testing (Objective 2) - NASA & JAXA engineers, flight controllers, scientists, roboticists, and astronauts directly participated in and/or observed testing both in field and in MCC-Houston. - Incorporated JAXA PR design elements into both integrated and standalone testing at JSC and in the field. - Re-established Analog Field-Testing Skills & Capabilities with Rovers to Investigate Artemis Architecture ConOps (Objective 3) - Multiple teams successfully worked to establish and manage field-test base camp, monitor and maintain the rover, and plan and execute 2 weeks of consecutive field-testing with little to no breaks between crews. TEST OUTCOMES - Results will inform Artemis architecture ConOps & capabilities related to pressurized rover operations (see sections 2 for more details) - Summary and team detailed reports will be posted on the D-RATS 2022 wiki

Analog↗