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NASA's plans for life sciences research facilities on a Space Station

A Life Sciences Research Facility on a Space Station will contribute to the health and well-being of humans in space, as well as address many fundamental questions in gravitational and developmental biology. Scientific interests include bone and muscle attrition, fluid and electrolyte shifts, cardiovascular deconditioning, metabolism, neurophysiology, reproduction, behavior, drugs and immunology, radiation biology, and closed life-support system development. The life sciences module will include a laboratory and a vivarium. Trade-offs currently being evaluated include (1) the need for and size of a 1-g control centrifuge; (2) specimen quantities and species for research; (3) degree of on-board analysis versus sample return and ground analysis; (4) type and extent of equipment automation; (5) facility return versus on-orbit refurbishment; (6) facility modularity, isolation, and system independence; and (7) selection of experiments, design, autonomy, sharing, compatibility, and integration.

Arno, R.↗

Implementing Artificial Thinking Autonomy with Model-Based System Engineering

Complex autonomous systems capable of successfully operating independently under ‘known unknowns’ and harsh conditions require paradigm innovation in modern development strategies. In the field of autonomy, developing a system-of-systems which can ostensibly think for itself in the face of ‘unknown unknowns’ is still a field of ongoing research. Maturing the systems architecting and modeling methodologies for developing henceforth named Thinking Autonomous Systems, which are verified with digital mission simulation, can potentially usher in the next generation of artificial intelligence for space exploration. The concept presented in this paper incorporates multiple Model-Based Systems Engineering and simulation methodologies combined as a new paradigm to design a novel, biomimetic thinking autonomy strategy. Anachronistic concepts from classical Kantian philosophy will be leveraged to inspire architectural designs that could be used for complex distributed systems in deep space. To accomplish this, digital transformation of a document-based implementation plan for Thinking Autonomous Systems, generated by experienced NASA software engineers, is implemented for NASA’s Platform for Autonomous Systems by creating descriptive and executable software models in SysML to prototype real-time operating capabilities. This conceptual implementation has been developed by incorporating model-based digital simulations to theorize how a cyberphysical thinking system would achieve specific strategies without crew reliance, while simultaneously being resilient to all operating conditions and remaining functional when devoid of ground communication. Additionally, ensuring that an autonomous system framework is an ethical Artificial Intelligence requires careful consideration of system behavior and accountability, human factors for teaming with a thinking autonomous system, and comparison to other modern approaches used for implementing true autonomy. This paper presents the first steps in formalizing the metacognition required for instantiating a truly Thinking Autonomous System; the approach described symphonizes autonomy characteristics from classical philosophical into a unified software architecture describing human thought. In the future, the foundational models described in this paper can be further leveraged to help advance research into thinking autonomy requirements for future deep space missions as well as for current near-term applications, i.e., living aboard crewed spacecraft like a NASA Gateway cislunar habitat.

Artificial Thought↗

A Self-Tuning Kalman Filter for Autonomous Spacecraft Navigation

Most navigation systems currently operated by NASA are ground-based, and require extensive support to produce accurate results. Recently developed systems that use Kalman Filter and Global Positioning System (GPS) data for orbit determination greatly reduce dependency on ground support, and have potential to provide significant economies for NASA spacecraft navigation. Current techniques of Kalman filtering, however, still rely on manual tuning from analysts, and cannot help in optimizing autonomy without compromising accuracy and performance. This paper presents an approach to produce a high accuracy autonomous navigation system fully integrated with the flight system. The resulting system performs real-time state estimation by using an Extended Kalman Filter (EKF) implemented with high-fidelity state dynamics model, as does the GPS Enhanced Orbit Determination Experiment (GEODE) system developed by the NASA Goddard Space Flight Center. Augmented to the EKF is a sophisticated neural-fuzzy system, which combines the explicit knowledge representation of fuzzy logic with the learning power of neural networks. The fuzzy-neural system performs most of the self-tuning capability and helps the navigation system recover from estimation errors. The core requirement is a method of state estimation that handles uncertainties robustly, capable of identifying estimation problems, flexible enough to make decisions and adjustments to recover from these problems, and compact enough to run on flight hardware. The resulting system can be extended to support geosynchronous spacecraft and high-eccentricity orbits. Mathematical methodology, systems and operations concepts, and implementation of a system prototype are presented in this paper. Results from the use of the prototype to evaluate optimal control algorithms implemented are discussed. Test data and major control issues (e.g., how to define specific roles for fuzzy logic to support the self-learning capability) are also discussed. In addition, architecture of a complete end-to-end candidate flight system that provides navigation with highly autonomous control using data from GPS is presented.

Truong, Son H.↗

High Speed Mobility Through On-Demand Aviation

Game changing advances come about by the introduction of new technologies at a time when societal needs create the opportunity for new market solutions. A unique opportunity exists for NASA to bring about such a mobility revolution in General Aviation, extendable to other aviation markets, to maintain leadership in aviation by the United States. This report outlines the research carried out so far under NASA's leadership towards developing a new mobility choice, called Zip Aviation1,2,3. The feasibility, technology and system gaps that need to be addressed, and pathways for successful implementation have been investigated to guide future investment. The past decade indicates exciting trends in transportation technologies, which are quickly evolving. Automobiles are embracing automation to ease driver tasks as well as to completely control the vehicle with added safety (Figure 1). Electric propulsion is providing zero tail-pipe emission vehicles with dramatically lower energy and maintenance costs. These technologies have not yet been applied to aviation, yet offer compelling potential benefits across all aviation markets, and in particular to General Aviation (GA) as an early adopter market. The benefits of such an adoption are applicable in the following areas: 􀁸 Safety: The GA market experiences accident rates that are substantially higher than automobiles or commercial airlines, with 7.5 fatal accidents per 100 million vehicle miles compared to 1.3 for automobiles and.068 for airlines. Approximately 80% of these accidents are caused by some form of pilot error, with another 13% caused by single point propulsion system failure. 􀁸 Emissions: Environmental constraints are pushing for the elimination of 100Low Lead (LL) fuel used in most GA aircraft, with aviation fuel the #1 source of lead emissions into the environment. Aircraft also have no emission control systems (i.e. no catalytic converters etc.), so they are gross hydrocarbon polluters compared to automobiles. 􀁸 Community Noise: Hub and smaller GA airports are facing increasing noise restrictions, and while commercial airliners have dramatically decreased their community noise footprint over the past 30 years, GA aircraft noise has essentially remained same, and moreover, is located in closer proximity to neighborhoods and businesses. 􀁸 Operating Costs: GA operating costs have risen dramatically due to average fuel costs of over $6 per gallon, which has constrained the market over the past decade and resulted in more than 50% lower sales and 35% less yearly operations. Infusion of autonomy and electric propulsion technologies can accomplish not only a transformation of the GA market, but also provide a technology enablement bridge for both larger aircraft and the emerging civil Unmanned Aerial Systems (UAS) markets. The NASA Advanced General Aviation Transport Experiments (AGATE) project successfully used a similar approach to enable the introduction of primary composite structures and flat panel displays in the 1990s, establishing both the technology and certification standardization to permit quick adoption through partnerships with industry, academia, and the Federal Aviation Administration (FAA). Regional and airliner markets are experiencing constant pressure to achieve decreasing levels of community emissions and noise, while lowering operating costs and improving safety. But to what degree can these new technology frontiers impact aircraft safety, the environment, operations, cost, and performance? Are the benefits transformational enough to fundamentally alter aircraft competiveness and productivity to permit much greater aviation use for high speed and On-Demand Mobility (ODM)? These questions were asked in a Zip aviation system study named after the Zip Car, an emerging car-sharing business model. Zip Aviation investigates the potential to enable new emergent markets for aviation that offer "more flexibility than the existing transportation solutions." These studies indicate that autonomy and electric propulsion technology infusions offer a unique opportunity to provide breakthrough capabilities for new high speed, on-demand travel alternatives that can leapfrog the need for future expensive ground-based infrastructure investment. At the same time, such investments offer a method of laying the foundation for these technologies to be incubated for commercial aviation at lower cost, and with lower initial certification thresholds due to the relatively poor capabilities of GA aircraft to permit early adoption and private market capitalization by rapid technology accelerations, as depicted in Figure 2.

Moore, Mark D.↗

A Prognostics Framework Development for Swarm Satellite Formations

Prognostics is the science of predicting the failure(s) of a component or a system and understanding how the performance will change in the event of a failure or degradation mechanism. With accurate predictions of possible failures, autonomous mitigative actions can be taken to correct/repair any issues or alert human operators of a failure threshold exceedance requiring condition-based maintenance. Although there is extensive research on failure predictions for a component or a system, there are significantly more opportunities to foray into failure predictions and prognostics for a system of systems such as an airspace consisting of multiple aircraft, a fleet of unmanned aerial vehicles, and a swarm of intelligent satellite systems. Failure prediction and mitigation are particularly important in autonomous systems such as satellite swarm systems that need effective resource management and minimal human interactions. Based on NASA's decadal survey, there is a clear need to prioritize the development of satellite swarm technology for studies of space physics and Earth science. The science community will propose future missions that return in-situ measurements from a 3-D (three-dimensional) volume of space, with relative spacecraft motion and inter-satellite baselines controlled according to the mission objectives. For such multi-spacecraft missions, it is required that ground operations resources do not scale with the number of satellites, thus compromising the swarm or leading to inefficiencies in resource allocation. Swarms of tens or hundreds of small satellites will require autonomy in attitude control, navigation and failure. Although significant research has been conducted in the areas of autonomous formation flying algorithms, less attention has been given to the development of resilient systems robust to failures.The focus of this research paper is the integration of model-based prognostics into the swarm dynamics control and decision-making algorithms. We simulate swarm management strategies for a subsystem failure to demonstrate the importance of failure predictions by comparing two cases: (i) no health information is provided to the system and utilized in the decision-making process and (2) system health information is obtained using prognostics and employed by the control system. One example scenario presented is for the GPS (Global Positioning System) system of an individual satellite to perform off-nominally due to increasing estimated error. In this scenario, the keep-out zone for that satellite would become more conservative, thereby decreasing the risk of collision. This is achieved via tuning the individual artificial repulsive functions assigned to each satellite.This paper is structured as follows. First we provide an overview of current swarm technology development, where we specifically use the term swarm to define multiple satellites flying in formation in similar orbits, with cross-link communication and station-keeping capabilities. Second, we give an introduction to the Swarm Orbital Dynamics Advisor (SODA), a tool that accepts high-level configuration commands and provides the orbital maneuvers required to achieve the prescribed formation configuration. Third, we provide the details of the model-based prognostics algorithm implementation in SODA. Finally, we present different case studies for potential component/subsystem failures and the swarm responses based with and without failure prediction information.

prognostics↗

The Path to Crew Autonomy - Situational Awareness in Scheduling and Rescheduling Tasks for Novice Schedulers

To increase crew autonomy for long duration exploration-class missions (LDEM), certain mission support tasks need to be completed by crew. Currently, crew activities are scheduled over the course of several weeks by ground-based experts with years of experience-based training. These experts display extensive amounts of situational awareness (SA) throughout task execution by maintaining a mental model of additional factors during scheduling such as constraints (e.g. physical space/layout), abilities and skills of the crew, and crew preferences allowing them to anticipate and mitigate potential issues. Thus, situational awareness is a key component for crews to manage their own schedules. In this paper, we examined situational awareness in novice schedulers in both a scheduling and rescheduling task. Our findings indicate that there is no significant difference between scheduling and rescheduling tasks for the development of SA in novice schedulers. Additionally, our experiment shows that novice schedulers are less able to develop sufficient SA for constraints that are dependent on one or more activities. Thus, we propose that software aids may be useful to support novice schedulers and increase SA in scheduling/rescheduling tasks. This work is vital to ensure the successful transfer of mission support tasks to the crew for future LDEM.

situation awareness↗

Operator Informational Needs for Multiple Autonomous Small Vehicles

With the anticipated explosion of small unmanned aerial vehicles, it is highly likely that operators will be controlling fleets of autonomous vehicles. To fulfill the promise of autonomy, vehicle operators will not be concerned with manual control of the vehicle; instead, they will deal with the overall mission. Furthermore, the one operator to many vehicles is becoming a constant meme with various industries including package delivery, search and rescue, and utility companies. In order for an operator to concurrently control several vehicles, his station must look and behave very differently than the current ground control station instantiations. Furthermore, the vehicle will have to be much more autonomous, especially during non-normal operations, in order to accommodate the knowledge deficit or the information overload of the operator in charge of several vehicles. The expected usage increase of small drones requires presenting the operational information generated by a fleet of heterogeneous autonomous agents to an operator. NASA Langley Research Center's Autonomy Incubator has brought together researchers in various disciplines including controls, trajectory planning, systems engineering, and human factors to develop an integrated system to study autonomy issues. The initial human factors effort is focusing on mission displays that would give an operator the overall status of all autonomous agents involved in the current mission. This paper will discuss the specifics of the mission displays for operators controlling several vehicles.

Trujillo, Anna C.↗

Demonstration of Two Extended Visual Line of Sight Methods for Urban UAV Operations

This report describes two extended visual line of sight (EVLOS) methods developed and utilized during two flight campaigns over the campus of NASA Langley Research Center (LaRC): a chase vehicle method and a radio controlled (RC) pilot handoff method. These campaigns were performed to (a) evaluate small unmanned aerial system (sUAS) flight beyond the visual line of sight (BVLOS) of the ground control station operator and (b) test technologies under development to enable a transition from EVLOS to BVLOS operations. While an autonomous waypoint-based operational approach enabled minimal pilot intervention in both methods, range containment was enforced (a) manually via continual pilot visual monitoring and (b) autonomously via on-board contingency landing autonomy triggerable at the boundary of stay-in geofences. In the thirty-nine flights which utilized the chase vehicle, the pilot followed the sUAS flying a 1.2 km path at 40m altitude over urban streets. In the fifteen flights which utilized pilot handoff, a pilot at one end of a 1.5 km path initiated the flight at 120m altitude over buildings and trees, and at the midway point of the path transferred radio control to a pilot at the other end. In comparison, the chase vehicle method requires less ground crew and simpler avionics, while the pilot handoff method avoids schedule risk arising from street traffic congestion but better replicates actual direct routing for BVLOS flights. Collision risk with another aircraft was introduced in both campaigns and mitigated with the same manual and autonomous methods. Results from these campaigns serve as a basis for planned BVLOS operations at NASA LaRC.

Nicholas Rymer↗

Autonomous and Autonomic Systems: A Paradigm for Future Space Exploration Missions

NASA increasingly will rely on autonomous systems concepts, not only in the mission control centers on the ground, but also on spacecraft and on rovers and other assets on extraterrestrial bodies. Automomy enables not only reduced operations costs, But also adaptable goal-driven functionality of mission systems. Space missions lacking autonomy will be unable to achieve the full range of advanced mission objectives, given that human control under dynamic environmental conditions will not be feasible due, in part, to the unavoidably high signal propagation latency and constrained data rates of mission communications links. While autonomy cost-effectively supports accomplishment of mission goals, autonomicity supports survivability of remote mission assets, especially when human tending is not feasible. Autonomic system properties (which ensure self-configuring, self-optimizing self-healing, and self-protecting behavior) conceptually may enable space missions of a higher order into any previously flown. Analysis of two NASA agent-based systems previously prototyped, and of a proposed future mission involving numerous cooperating spacecraft, illustrates how autonomous and autonomic system concepts may be brought to bear on future space missions.

Truszkowski, Walter F.↗

Robonaut 2 and Watson: Cognitive Dexterity for Future Exploration

Future exploration missions will dictate a level of autonomy never before experienced in human spaceflight. Mission plans involving the uncrewed phases of complex human spacecraft in deep space will require a coordinated autonomous capability to be able to maintain the spacecraft when ground control is not available. One promising direction involves embedding intelligence into the system design both through the employment of state-of-the-art system engineering principles as well as through the creation of a cognitive network between a smart spacecraft or habitat and embodiments of cognitive agents. The work described here details efforts to integrate IBM's Watson and other cognitive computing services into NASA Johnson Space Center (JSC)'s Robonaut 2 (R2) anthropomorphic robot. This paper also discusses future directions this work will take. A cognitive spacecraft management system that is able to seamlessly collect data from subsystems, determine corrective actions, and provide commands to enable those actions is the end goal. These commands could be to embedded spacecraft systems or to a set of robotic assets that are tied into the cognitive system. An exciting collaboration with Woodside provides a promising Earth-bound testing analog, as controlling and maintaining not normally manned off-shore platforms have similar constraints to the space missions described.

Badger, Julia M.↗

The environmental control and life support system advanced automation project. Phase 1: Application evaluation

The Environmental Control and Life Support System (ECLSS) is a Freedom Station distributed system with inherent applicability to advanced automation primarily due to the comparatively large reaction times of its subsystem processes. This allows longer contemplation times in which to form a more intelligent control strategy and to detect or prevent faults. The objective of the ECLSS Advanced Automation Project is to reduce the flight and ground manpower needed to support the initial and evolutionary ECLS system. The approach is to search out and make apparent those processes in the baseline system which are in need of more automatic control and fault detection strategies, to influence the ECLSS design by suggesting software hooks and hardware scars which will allow easy adaptation to advanced algorithms, and to develop complex software prototypes which fit into the ECLSS software architecture and will be shown in an ECLSS hardware testbed to increase the autonomy of the system. Covered here are the preliminary investigation and evaluation process, aimed at searching the ECLSS for candidate functions for automation and providing a software hooks and hardware scars analysis. This analysis shows changes needed in the baselined system for easy accommodation of knowledge-based or other complex implementations which, when integrated in flight or ground sustaining engineering architectures, will produce a more autonomous and fault tolerant Environmental Control and Life Support System.

Dewberry, Brandon S.↗

Designing and Building a Crew-Centric Mobile Scheduling and Planning Tool for Exploring Crew Autonomy Concepts Onboard the International Space Station

During 2015, as part of our ongoing research on crew autonomy, our team adapted and extended the plan viewing tool, Playbook, into a mobile tool for exploring crew autonomy onboard the International Space Station (ISS). This work enables crewmembers to intuitively re-plan and schedule on their own with limited input from mission control. Designed for ease of use, re-planning is composed of simple drag and drop interactions and learning the tool requires little to no training. Playbook was successfully uplinked onto ISS as a technology demonstration and completed its onboard ground and crew checkouts in August and September 2015, respectively. We will discuss and describe how Playbook was able to integrate with actual ISS operational plans and operational procedures without disrupting real mission operations. This work will also outline the design and technical constraints required to build a collaborative tool that allows multiple users to simultaneously self-schedule and synchronize during communication dropouts in the restricted networking and computing environment onboard ISS. Finally, we will explore the aspects of crew autonomy that this technology enables as well as discuss our next steps and possible extensions.

ISS↗

NASA Tech Briefs, July 2013

Dielectrophoresis-Based Particle Sensor Using Nanoelectrode Arrays; Multi-Dimensional Damage Detection for Surfaces and Structures; ULTRA: Underwater Localization for Transit and Reconnaissance Autonomy; Autonomous Cryogenic Leak Detector for Improving Launch Site Operations; Submillimeter Planetary Atmospheric Chemistry Exploration Sounder; Method for Reduction of Silver Biocide Plating on Metal Surfaces; Silicon Micromachined Microlens Array for THz Antennas; Forward-Looking IED Detector Ground Penetrating Radar; Fully Printed, Flexible, Phased Array Antenna for Lunar Surface Communication, Battery Charge Equalizer with Transformer Array; An Efficient, Highly Flexible Multi-Channel Digital Downconverter Architecture; Dimmable Electronic Ballast for a Gas Discharge Lamp; Conductive Carbon Nanotube Inks for Use with Desktop Inkjet Printing Technology; Enhanced Schapery Theory Software Development for Modeling Failure of Fiber-Reinforced Laminates; High-Performance, Low-Temperature-Operating, Long-Lifetime Aerospace Lubricants; Carbon Nanotube Microarrays Grown on Nanoflake Substrates; Differential Muon Tomography to Continuously Monitor Changes in the Composition of Subsurface Fluids; Microgravity Drill and Anchor System; 20 Granular Media-Based Tunable Passive Vibration Suppressor; 21 Miga Aero Actuator and 2D Machined Mechanical Binary Latch; Micro-XRF for In Situ Geological Exploration of Other Planets; Hydrogen-Enhanced Lunar Oxygen Extraction and Storage Using Only Solar Power; Uplift of Ionospheric Oxygen Ions During Extreme Magnetic Storms; Miniaturized, High-Speed, Modulated X-Ray Source; Hollow-Fiber Spacesuit Water Membrane Evaporator 25 High-Power Single-Mode 2.65-micrometers InGaAsSb/AlInGaAsSb Diode Lasers; Optical Device for Converting a Laser Beam Into Two Co-aligned but Oppositely Directed Beams; A Hybrid Fiber/Solid-State Regenerative Amplifier with Tunable Pulse Widths for Satellite Laser Ranging; X-Ray Diffractive Optics; SynGenics Optimization System (SynOptSys); 29 CFD Script for Rapid TPS Damage Assessment; radEq Add-On Module for CFD Solver Loci-CHEM; Science Opportunity Analyzer (SOA) Version 8; 30 Autonomous Byte Stream Randomizer; Distributed Engine Control Empirical/Analytical Verification Tools; Dynamic Server-Based KML Code Generator Method for Level-of-Detail Traversal of Geospatial Data; Automated Planning of Science Products Based on Nadir Overflights and Alerts for Onboard and Ground Processing; Linked Autonomous Interplanetary Satellite Orbit Navigation; Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing; Scheduling Operations for Massive Heterogeneous Clusters; Deepak Condenser Model (DeCoM); Flight Software Math Library; Recirculating 1-K-Pot for Pulse-Tube Cryostats; 35 Method for Processing Lunar Regolith Using Microwaves; Wells for In Situ Extraction of Volatiles from Regolith (WIEVR); and Estimating the Backup Reaction Wheel Orientation Using Reaction Wheel Spin Rates Flight Telemetry from a Spacecraft.

Source record↗

State of the Profession Considerations: NASA Langley Research Center Capabilities / Technologies for Autonomous In-Space Assembly and Modular Persistent Assets

Successfully implementing OSAM into next generation revolutionary observatories requires integrating expertise and technologies in modular space structures, assembly operations, autonomy, and modeling/simulation. LaRC OSAM technologies/capabilities have been presented to inform the Planetary Science and Astrobiology Decadal Survey community of the robust and mature existing capability to support an OSAM based architecture for their next observatory. LaRC Structures and Assembly capabilities enable; a modular telescope architecture, high-performance structural modules, and robotic assembly techniques. LaRC Autonomy capabilities ensure that the robotic assembly will be accomplished in a safe and robust manner and only require humans in a supervisory role. The LaRC toolbox of Modeling and Simulation capabilities that is calibrated using module-level ground testing, will ensure that the performance of the fully assembled observatory, a very large zero-g system that will never be assembled/tested in a gravity environment, meets all performance requirements when it enters into service. Integrating all three LaRC capabilities and including embedded metrology, will enable servicing, repair, instrument upgrades (and/or replacement) while ensuring a very long lifetime for the observatory and providing a return-on-investment that is substantially greater than the initial cost. Further confidence will be achieved as OSAM technologies are validated in a new LaRC OSAM laboratory that allows large-scale collaborative testing of modular hardware, simulation software and algorithms, and autonomous agents.

Large space structures↗

Scientific Physical and Operations Characterization (SPOC): Studying Scientists in the Wild to Inform Human Planetary Exploration Operations

The objective of the Scientific Physical and Operational Characterization (SPOC) project is to build an evidence-based description of terrestrial field science to inform the operational, physical, and tool requirements for planetary exploration extravehicular activities (xEVAs). EVAs of the future, including Artemis 2024 and beyond, intend to promote scientific productivity (e.g., LEAG science goals)[1]; however, no clear, objective pathway currently exists to enable this goal, particularly with respect to the desired increase in autonomy imparted to future astronauts. The SPOC project applies expertise in the fields of cognitive systems engineering [2-5], biomechanics, wearable sensors [6-8] and hardware/software to more targetly address these issues. In doing so, a terrestrial fieldwork ground-truth can be established that will benefit human and robotic exploration of other planetary surfaces.

M J Miller↗

Extended Duration: The SIRIUS 21 Crew Perspective

The SIRIUS (Scientific International Research In a Unique terrestrial Station) missions represent a collaborative effort between NASA and Russia’s Institute for Biomedical Problems (IBMP) to conduct a series of long duration isolation and confinement spaceflight analog missions. Three missions of 17-day, 4-month, and 8-month duration (SIRIUS 17, 19, and 21) have been completed at IBMP’s Ground-Based Experimental Complex / Nazemnyy eksperimental'nyy kompleks (NEK) in Moscow, Russia. The international SIRIUS 21 crew comprising representatives from the United States, United Arab Emirates and Russia recently completed the 8-month analog lunar mission. The extended duration mission included simulated lunar transit, orbital, and surface operations with corresponding deep space communication delay, during which the crew participated in nearly 70 studies, eight of which were sponsored by NASA’s Human Research Program. The studies examined the effect of isolation and confinement on the behavioral health of research subjects, and investigated medical countermeasures, team performance, crew dynamics, crew autonomy, food system risks, consequences of confinement and associated physiological stressors. SIRIUS 21 crewmembers also participated in operational tasks such as Rover and CubeSat assembly, simulated lunar sample assessment, VR activities, robotic arm training, environmental systems monitoring, exercise, greenhouse maintenance and 3D printing. Communication with Mission Control was limited to 30-minute periods every two hours. Since access to the internet and email was restricted, simulated ground support provided the Crew’s primary source of daily news and mission information. This panel discussion will include presentations from the US SIRIUS 21 crewmembers – William Brown and Ashley Kowalski – about their experience participating in the mission and science. A facilitated question and answer session will follow with attendees encouraged to ask questions and join in discussion with the SIRIUS 21 crewmembers about their experiences. William Brown came to SIRIUS 21 with experience spread across multiple industries, including the military, defense contracting, healthcare consulting, software engineering, and logistics. He has lived in the Middle East, Central Asia, and Russia. A former Boren Scholar, Brown is fluent in Russian. He holds a Master of International Business degree from the University of South Carolina’s Darla Moore School of Business. Prior to that, he earned a bachelor’s degree in Russian language, literature, and culture from the University of South Carolina. There, he also completed additional undergraduate coursework in computer science. Ashley Kowalski is a Project Leader in The Aerospace Corporation’s International Partnerships Department, where she works with, represents, and provides technical support to the the U.S. Space Force Space Systems Command International Affairs (SSC/IA) office. Through her numerous national and international assignments (Russia, China, and Germany), she has worked on topics related to international space systems, national security space systems, civil systems (including human spaceflight and civil launch projects), space policy, satellite industry analysis, and satellite manufacturing start-ups. She is proficient in Russian and German, and fluent in Polish. Kowalski received her Bachelor of Science and Master of Science degrees in mechanical and aerospace engineering from George Washington University in 2011 and 2012, respectively.

S. E. Whiting↗

Adjustable Autonomy and Human-Agent Teamwork in Practice: An Interim Report on Space Applications

We give a preliminary perspective on the basic principles and pitfalls of adjustable autonomy and human-centered teamwork. We then summarize the interim results of our study on the problem of work practice modeling and human-agent collaboration in space applications, the development of a broad model of human-agent teamwork grounded in practice, and the integration of the Brahms, KAoS, and NOMADS agent frameworks. We hope our work will benefit those who plan and participate in work activities in a wide variety of space applications, as well as those who are interested in design and execution tools for teams of robots that can function as effective assistants to humans.

Bradshaw, Jeffrey M.↗

Search and Rescue under the Forest Canopy using Multiple UAS

We consider the problem of multi-robot search and rescue under the forest canopy. Forest is a particularly challenging environment for collaborative mapping and exploration, mainly due to the existence of severe perceptual aliasing, which hinders reliable mutual localization and map fusion. Our proposed system features unmanned aerial vehicles (UAVs) with onboard sensing and autonomy. Each UAV runs a lightweight filtering algorithm for local state estimation, and a dynamic-aware frontier selection algorithm for fast exploration. The essential and computationally intensive task of collaborative simultaneous localization and mapping (CSLAM) is performed at a central ground station. To handle perceptual aliasing, we make use of stable landmarks extracted from trees, which significantly improve precision and recall during place recognition. Furthermore, to recover from incorrect pairwise data associations during loop closure, we propose a novel procedure for global data association based on recently developed techniques on cycle consistent multiway matching. Our algorithm returns a global data association that is guaranteed to be cycle consistent, and is shown to significantly improve precision compared to the input pairwise associations. The overall multi-UAV system is extensively validated during real-world collaborative exploration missions in a forest at NASA Langley Research Center.

Multi-robot systems↗