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NASA NTRS2001

Enabling Advanced Automation in Spacecraft Operations with the Spacecraft Emergency Response System

True autonomy is the Holy Grail of spacecraft mission operations. The goal of launching a satellite and letting it manage itself throughout its useful life is a worthy one. With true autonomy, the cost of mission operations would be reduced to a negligible amount. Under full autonomy, any problems (no matter the severity or type) that may arise with the spacecraft would be handled without any human intervention via some combination of smart sensors, on-board intelligence, and/or smart automated ground system. Until the day that complete autonomy is practical and affordable to deploy, incremental steps of deploying ever-increasing levels of automation (computerization of once manual tasks) on the ground and on the spacecraft are gradually decreasing the cost of mission operations. For example, NASA's Goddard Space Flight Center (NASA-GSFC) has been flying spacecraft with low cost operations for several years. NASA-GSFC's SMEX (Small Explorer) and MIDEX (Middle Explorer) missions have effectively deployed significant amounts of automation to enable the missions to fly predominately in 'light-out' mode. Under light-out operations the ground system is run without human intervention. Various tools perform many of the tasks previously performed by the human operators. One of the major issues in reducing human staff in favor of automation is the perceived increased in risk of losing data, or even losing a spacecraft, because of anomalous conditions that may occur when there is no one in the control center. When things go wrong, missions deploying advanced automation need to be sure that anomalous conditions are detected and that key personal are notified in a timely manner so that on-call team members can react to those conditions. To ensure the health and safety of its lights-out missions, NASA-GSFC's Advanced Automation and Autonomy branch (Code 588) developed the Spacecraft Emergency Response System (SERS). The SERS is a Web-based collaborative environment that enables secure distributed fault and resource management. The SERS incorporates the use of intelligent agents, threaded discussions, workflow, database connectivity, and links to a variety of communications devices (e.g., two-way paging, PDA's, and Internet phones) via commercial gateways. When the SERS detects a problem, it notifies on-call team members, who then can remotely take any necessary actions to resolve the anomalies.The SERS goes well beyond a simple '911' system that sends out an error code to everyone with a pager. Instead, SERS' software agents send detailed data (i.e., notifications) to the most appropriate team members based on the type and severity of the anomaly and the skills of the on-call team members. The SERS also allows the team members to respond to the notifications from their wireless devices. This unique capability ensures rapid response since the team members no longer have to go to a PC or the control center for every anomalous event. Most importantly, the SERS enables safe experimentation with various techniques for increasing levels of automation, leading to robust autonomy. For the MIDEX missions at NASA GSFC, the SERS is used to provide 'human-in-the-loop' automation. During lights-out operations, as greater control is given to the MIDEX automated systems, the SERS can be configured to page remote personnel and keep them informed regarding actions taking place in the control center. Remote off-duty operators can even be given the option of enabling or inhibiting a specific automated response in near real time via their two-way pagers. The SERS facilitates insertion of new technology to increase automation, while maintaining the safety and security of mission resources. This paper will focus on SERS' overall functionality and how SERS has been designed to handle the monitoring and emergency response for missions with varying levels of automation. The paper will also convey some of the key lessons learned from SERS' deployment across of variety of missions, highlighting this incremental approach to achieving 'robust autonomy'.

Breed, Julie↗
NASA NTRS2017

Medical Systems Engineering to Support Mars Mission Crew Autonomy

Human spaceflight missions to Mars face exceptionally challenging resource limitations that far exceed those faced before. Increasing transit times, decreasing opportunity for resupply, communications challenges, and extended time to evacuate a crew to definitive medical care dictate a level of crew autonomy in medical care that is beyond the current medical model. To approach this challenge, a medical systems engineering approach is proposed that relies on a clearly articulated Concept of Operations and risk analysis tools that are in development at NASA. This paper proposes an operational clinical model with key terminology and concepts translated to a controls theory paradigm to frame a common language between clinical and engineering teams. This common language will be used for design and validation of an exploration medical system that is fully integrated into a Mars transit vehicle. This approach merges medical simulation, human factors evaluation techniques, and human-in-the-loop testing in ground based analogs to tie medical hardware and software subsystem performance and overall medical system functionality to metrics of operational medical autonomy. Merging increases in operational clinical autonomy with a more restricted vehicle system resource scenario in interplanetary spaceflight will require an unprecedented level of medical and engineering integration. Full integration of medical capabilities into a Mars vehicle system may require a new approach to integrating medical system design and operations into the vehicle Program structure. Prior to the standing-up of a Mars Mission Program, proof of concept is proposed through the Human Research Program.

Antonsen, Erik↗
NASA NTRSDate not supplied

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗
NASA NTRS2013

Development and Execution of Autonomous Procedures Onboard the International Space Station to Support the Next Phase of Human Space Exploration

Now that major assembly of the International Space Station (ISS) is complete, NASA's focus has turned to using this high fidelity in-space research testbed to not only advance fundamental science research, but also demonstrate and mature technologies and develop operational concepts that will enable future human exploration missions beyond low Earth orbit. The ISS as a Testbed for Analog Research (ISTAR) project was established to reduce risks for manned missions to exploration destinations by utilizing ISS as a high fidelity micro-g laboratory to demonstrate technologies, operations concepts, and techniques associated with crew autonomous operations. One of these focus areas is the development and execution of ISS Testbed for Analog Research (ISTAR) autonomous flight crew procedures intended to increase crew autonomy that will be required for long duration human exploration missions. Due to increasing communications delays and reduced logistics resupply, autonomous procedures are expected to help reduce crew reliance on the ground flight control team, increase crew performance, and enable the crew to become more subject-matter experts on both the exploration space vehicle systems and the scientific investigation operations that will be conducted on a long duration human space exploration mission. These tests make use of previous or ongoing projects tested in ground analogs such as Research and Technology Studies (RATS) and NASA Extreme Environment Mission Operations (NEEMO). Since the latter half of 2012, selected non-critical ISS systems crew procedures have been used to develop techniques for building ISTAR autonomous procedures, and ISS flight crews have successfully executed them without flight controller involvement. Although the main focus has been preparing for exploration, the ISS has been a beneficiary of this synergistic effort and is considering modifying additional standard ISS procedures that may increase crew efficiency, reduce operational costs, and raise the amount of crew time available for scientific research. The next phase of autonomous procedure development is expected to include payload science and human research investigations. Additionally, ISS International Partners have expressed interest in participating in this effort. The recently approved one-year crew expedition starting in 2015, consisting of one Russian and one U.S. Operating Segment (USOS) crewmember, will be used not only for long duration human research investigations but also for the testing of exploration operations concepts, including crew autonomy.

beyond low earth orbit (BLEO)↗
NASA NTRSDate not supplied

Innovations in Distributed Spacecraft Autonomy

The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in distributed space systems through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. This talk describes recent successes of the DSA experiment onboard the Starling 1.0 mission.

Caleb Adams↗
NASA NTRSDate not supplied

Designing Autonomy into Interfaces for Long-Duration Missions

As NASA develops technologies for long-duration crewed missions, we must understand how communication between ground control teams and astronauts differs from the current dynamic to adapt new concepts for long-duration mission operations. Today, ground control teams support astronauts with immediate availability to answer questions, resolve issues, and manage activities. In the near future, however, extended communication delays during long-duration missions will require astronauts to become more autonomous. As many of the responsibilities shift from the ground control teams to the astronauts on-board, the concept of operations must also change from how it functions today. With increased astronaut autonomy, software tools must be developed that enable efficient completion of mission tasks without increased mental workload. Designing software tools to facilitate crew autonomy requires development teams to know which data will enhance quick decision making while providing necessary context for situational awareness of systems being managed on-board. NASA's Autonomous Systems and Operations (ASO) team is presently developing a software interface tool, EXPRESS (EXpedite the PRocessing of Experiments for Space Station) 2.5 to enable a long-duration crew to schedule activities for and operate autonomous systems. This paper describes details of the integrated human factors approach that drove the design of the elements of the software tool, including self-managed scheduling, constraint-driven planning, autonomous system fault recovery, and recommended troubleshooting actions. Additionally, this paper will chronicle ASO modifications of the user interface after the team's first flight demonstration, how it was based on lessons learned during software development, as well as from crew feedback in order to develop the current version which will be demonstrated on ISS in 2021. In the upcoming ISS demonstration, the astronaut crew will be given scenarios for scheduling and operating autonomous system activities, including off-nominal scenarios and autonomous system recoveries. The demonstration of the EXPRESS 2.5 tool is a step towards improved levels of autonomy as our new journeys take us farther into space.

autonomy↗
NASA NTRS2021

ATTRACTOR: Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability

Autonomous systems (AS) are crucial to realizing the vision of new, complex transportation modes, such as advanced air mobility (AAM) and urban air mobility (UAM). A chief barrier to induction of AS into aviation is insufficient understanding of AS reliability in time-critical and safety-critical environments—an obstacle to certification. ATTRACTOR is aimed at building a basis for certification of classes of autonomous cyber-physical-human systems (CPHS) via establishing metrics and models of trustworthiness and trust in multi-agent team interactions, analyzable trajectories, explainability of computational algorithms (explainable artificial intelligence, or XAI), and persistent modeling and simulation, in the context of missions planning and operation. By “building a basis for certification,” we mean acquiring an understanding of when a system is trustworthy and developing computable means to estimate trustworthiness and trust in order to eventually inform functional requirements that contribute to certification. The outcomes are applicable not just to aviation but to all domains that rely on autonomous systems.

Autonomy↗
NASA NTRSDate not supplied

Human Capabilities Assessments for Autonomous Missions: A Multi-Team Research Effort to Reduce Risk in the Human-System Integration Architecture for Future Deep-Space Missions

In future exploration missions beyond low earth-orbit, crew will have to execute complex operations and respond to off-nominal events, without real-time support from Mission Control. It is anticipated that increased reliance on automated systems, including human-centric vehicle and information architecture, will need to be designed to support the crew; increased risk to performance, health, and safety may occur if these are not implemented appropriately. The Human Factors and Behavioral Performance Element (HFBP) in the NASA Human Research Program supports research to characterize and mitigate such human health and performance risks, including the Risk of Adverse Outcome Due to Inadequate Human Systems Integration Architecture (HSIA). The HSIA risk addresses the integration of onboard capability and the crew roles and responsibilities necessary to enable the crew to respond effectively and efficiently in the increasingly autonomous mission operations environment. In 2017, HFBP released the “Human Capabilities Assessments for Autonomous Missions” (HCAAM) research topic to address HSIA related questions. HCAAM is a major NASA research effort that has assembled a multidisciplinary team from seven institutions to work closely with design and engineering efforts on research towards developing and refining human performance standards, guidelines and automation tools. The scientific focus is on quantitative assessment of human capabilities relevant to future deep-space missions during which earth/spacecraft communication is so delayed and intermittent that the crew must be able to function autonomously. The integrated strategy of the HCAAM project characterizes human capabilities and limitations related to potential performance decrements during long duration exploration mission spaceflight as relevant to both routine and complex task performance; defines system characteristics that reduce the likelihood or impact of potential decrements in human performance capabilities; performs integrated assessment of intelligent system responses within the context of an operational environment with relevant NASA tools, systems, and data structures in order to determine positive or negative interactions and validate recommended approaches; and proposes specific updates to existing standards and guidelines for inclusion in NASA handbooks for the design of future spacecraft intelligent systems that provide crew performance assessment/feedback, and to also serve as decision-support aids for the onboard crew (i.e., NASA-STD-3001, and NASA/SP-Human Integration Design Handbook (HIDH)). The scientific research vectors being addressed by the seven HCAAM teams include: - crew task performance (accuracy, efficiency) (crew + automation) - crew performance (accuracy, efficiency) - crew Situation Awareness - procedure design and multi-modal enhancement - concurrent tasking (mixed manual + some level of autonomy) - task handover - crew self-planning and time-lining - task design - trust in automation, real-time calibration - human multi-sensory feedback and guidance - human trust in on-board software-based intelligent assistants - virtual assistants The presentation will highlight plans and progress made in each of these research areas as well as the methods by which surrogate astronaut crews in the NASA JSC HERA spaceflight analog facility will function as human test subjects for all of the HCAAM research projects.

HCAAM VNSCOR↗
NASA NTRS2018

Development of a Ground Test and Analysis Protocol for NASA's NextSTEP Phase 2 Habitation Concepts

The NASA Next Space Technologies for Exploration Partnerships (NextSTEP) program is a public-private partnership model that seeks commercial development of deep space exploration capabilities to support human spaceflight missions around and beyond cislunar space. NASA first issued the Phase 1 NextSTEP Broad Agency Announcement to U.S. industries in 2014, which called for innovative cislunar habitation concepts that leveraged commercialization plans for low-Earth orbit. These habitats will be part of the Deep Space Gateway (DSG), the cislunar space station planned by NASA for construction in the 2020s. In 2016, Phase 2 of the NextSTEP program selected five commercial partners to develop ground prototypes. A team of NASA research engineers and subject matter experts (SMEs) have been tasked with developing the ground-test protocol that will serve as the primary means by which these Phase 2 prototypes will be evaluated. Since 2008, this core test team has successfully conducted multiple spaceflight analog mission evaluations utilizing a consistent set of operational tools, methods, and metrics to enable the iterative development, testing, analysis, and validation of evolving exploration architectures, operations concepts, and vehicle designs. The purpose of implementing a similar evaluation process for the Phase 2 Habitation Concepts is to consistently evaluate different commercial partner ground prototypes to provide data-driven, actionable recommendations for Phase 3. This paper describes the process by which the ground test protocol was developed and the objectives, methods, and metrics by which the NextSTEP Phase 2 Habitation Concepts will be rigorously and systematically evaluated. The protocol has been developed using both a top-down and bottom-up approach. Top-down development began with the Human Exploration and Operations Mission Directorate (HEOMD) exploration objectives and ISS Exploration Capability Study Team (IECST) candidate flight objectives. Strategic questions and associated rationales, derived from these candidate architectural objectives, provide the framework by which the ground-test protocol will address the DSG stack elements and configurations, systems and subsystems, and habitation, science, and EVA functions. From these strategic questions, high-level functional requirements for the DSG were drafted and associated ground-test objectives and analysis protocols were established. Bottom-up development incorporated objectives from NASA SMEs in autonomy, avionics and software, communication, environmental control and life support systems, exercise, extravehicular activity, exploration medical operations, guidance navigation and control, human factors and behavioral performance, human factors and habitability, logistics, Mission Control Center operations, power, radiation, robotics, safety and mission assurance, science, simulation, structures, thermal, trash management, and vehicle health. Top-down and bottom-up objectives were integrated to form overall functional requirements - ground-test objectives and analysis mapping. From this mapping, ground-test objectives were organized into those that will be evaluated through inspection, demonstration, analysis, subsystem standalone testing, and human-in-the-loop (HITL) testing. For the HITL tests, mission-like timelines, procedures, and flight rules have been developed to directly meet ground test objectives and evaluate specific functional requirements. Data collected from these assessments will be analyzed to determine the acceptability of habitation element configurations and the combinations of capabilities that will result in the best habitation platform to be recommended by the test team for Phase 3.

Gernhardt, Michael L.↗
NASA NTRS2012

Advancing Robotic Control for Space Exploration Using Robonaut 2

Robonaut 2, or R2, arrived on the International Space Station (ISS) in February 2011 and is currently being tested in preparation for its role initially as an Intra-Vehicular Activity (IVA) tool and eventually as a robot that performs Extra-Vehicular Activities (EVA). Robonaut 2, is a state of the art dexterous anthropomorphic robotic torso designed for assisting astronauts. R2 features increased force sensing, greater range of motion, higher bandwidth, and improved dexterity over its predecessor. Robonaut 2 is unique in its ability to safely allow humans in its workspace and to perform significant tasks in a workspace designed for humans. The current operational paradigm involves either the crew or the ground control team running semi-autonomous scripts on the robot as both the astronaut and the ground team monitor R2 and the data it produces. While this is appropriate for the check-out phase of operations, the future plans for R2 will stress the current operational framework. The approach described here will outline a suite of operational modes that will be developed for Robonaut 2. These operational modes include teleoperation, shared control, directed autonomy, and supervised autonomy, and they cover a spectrum of human involvement in controlling R2.

Badger, Julia↗
NASA NTRS1987

Development of a semi-autonomous service robot with telerobotic capabilities

The importance to the United States of semi-autonomous systems for application to a large number of manufacturing and service processes is very clear. Two principal reasons emerge as the primary driving forces for development of such systems: enhanced national productivity and operation in environments whch are hazardous to humans. Completely autonomous systems may not currently be economically feasible. However, autonomous systems that operate in a limited operation domain or that are supervised by humans are within the technology capability of this decade and will likely provide reasonable return on investment. The two research and development efforts of autonomy and telerobotics are distinctly different, yet interconnected. The first addresses the communication of an intelligent electronic system with a robot while the second requires human communication and ergonomic consideration. Discussed here are work in robotic control, human/robot team implementation, expert system robot operation, and sensor development by the American Welding Institute, MTS Systems Corporation, and the Colorado School of Mines--Center for Welding Research.

Jones, J. E.↗
NASA NTRS2017

Human-Robot Teaming: From Space Robotics to Self-Driving Cars

In this talk, I describe how NASA Ames has been developing and testing robots for space exploration. In our research, we have focused on studying how human-robot teams can increase the performance, reduce the cost, and increase the success of space missions. A key tenet of our work is that humans and robots should support one another in order to compensate for limitations of manual control and autonomy. This principle has broad applicability beyond space exploration. Thus, I will conclude by discussing how we have worked with Nissan to apply our methods to self-driving cars, enabling humans to support autonomous vehicles operating in unpredictable and difficult situations.

robotics↗
NASA NTRSDate not supplied

ATTRACTOR: Toward Trustworthy and Trusted Autonomous Systems

The question of what it means and what it takes for an autonomous system to consider another autonomous system justifiably trustworthy must be addressed by all who seek to integrate intelligent machine agents into real-world operations. A satisfactory answer to this question is an essential component in accepting autonomous machine decision-making in safety-critical and time-critical environments, such as aviation. Historically, simulation platforms for test and evaluation of complex systems have proven to be effective in assessing performance and contributing to decisions on the fitness of systems to operate in current general and commercial aviation airspace. Moreover, simulations have informed the definition of safety-critical constraints. However, as machine systems progressively take on responsibilities for decision-making traditionally supplied by humans, simulations require enhancement. Mixed reality simulation that integrates real-world platforms and data or high-fidelity simulation data in a sim-to-flight paradigm provides insight into agent interaction and the rationale behind autonomous agent decision-making as well as the capacity for seamless integrated implementation, testing, and operation of systems. Strong simulation capabilities are especially important in the presence of algorithms that hold great promise in decision-making yet increase the uncertainty in the system. Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) is a subproject of NASA’s Convergent Aeronautics Solutions (CAS) Project. ATTRACTOR’s objective is to build a basis for understanding trust and trustworthiness in multi-agent autonomous teams, and thus to inform future certification of safety-critical and time-critical autonomous systems in aviation. Because the concepts of trust and trustworthiness must be addressed in a context, ATTRACTOR has chosen Search and Rescue (SAR) in dynamic and unstructured environments, with emphasis on search, as its design reference mission (DRM). During dynamic planning and execution of trajectory-based operations, autonomous agents determine their trajectories given an assigned mission or missions and call for assistance from an appropriate teammate when needed. This experience along with the attendant human-machine and machine-machine interactions, serve as a platform for developing approaches to identifying and measuring trustworthiness and increasing trust. In this paper, we give an overview of some of ATTRACTOR’s research and development activities, findings, and ongoing work.

ATTRACTOR↗
NASA NTRS2022

Automation & Autonomy Standards and Guidelines for Space Vehicles

The NASA Office of the Chief Health and Medical Officer (OCHMO) requested HRP conduct a survey of industry and government standards and guidelines for the interaction of automation/autonomy with humans. Guidance for verification testing of human-automation designs was also requested. A rapid response was requested so that the deliverables could be provided as part of a future NASA solicitation for automated systems for HLS. The project began with a broad review and analysis of prior NASA work in this area, as well as external standards related to human interaction with automation/autonomy. The team reviewed approximately 200 documents, and interviewed multiple industry and government subject matter experts (SMEs). “Gold standard” documents were selected for focus and key categories were identified. A cross-walk of standards was created, and common standards and guidelines were selected and rephrased (where necessary) to be information-rich, concise, and usable. Verification guidelines and examples were also developed. The final report includes an introduction to automation and autonomy, selected standards and guidelines, verification method guidance, and research gaps. In addition to the report, the team delivered a list of candidate standards for autonomous vehicles, as well as a list of candidate standards for a future NASA-STD-3001 update on automation/autonomy. The presentation will describe the rapid response project approach and methods, examples of standards and guidelines identified and delivered to OCHMO, and research needed to develop additional automation/autonomy design guidance where gaps currently exist.

automation↗
NASA NTRS2017

CARACaS multi-agent maritime autonomy for unmanned surface vehicles in the Swarm II harbor patrol demonstration

This paper describes new autonomy technology that enabled a team of unmanned surface vehicles (USVs) to execute cooperative behaviors in the USV Swarm II harbor patrol demonstration and provides a description of autonomy performance in the event. The new developments extend the NASA Jet Propulsion Laboratory’s CARACaS (Control Architecture for Robotic Agent Command and Sensing) autonomy architecture, which pro- vides foundational software infrastructure, core executive functions, and several default robotic technology mod- ules. In Swarm II, CARACaS demonstrated higher levels of autonomy and more complex cooperation than previous on-water exercises, using full-sized vehicles and real-world sensing and communication. The core au- tonomous behaviors to support the harbor patrol scenario included Patrol, Track, Inspect, and Trail, providing the capability of finding all vessels entering the patrol area, keeping track of them, inspecting them to infer intent, and trailing suspect vessels. Significantly, CARACaS assumed responsibility for not only executing tasks safely and efficiently but also recognizing what tasks needed to be accomplished, given the current state of the world. Since the heterogeneous USV teams shared world model that evolved, such as due to (dis)appearance of vessels in the area or a change in health or availability of a USV, CARACaS replanned to generate and reallocate the new task list. Thus, human intervention was never required in the loop to task USVs during mission execution, though a supervisory role was supported in the autonomy system for mission monitoring and exception handling. Finally, CARACaS also ensured the USVs avoided hazards and obeyed the applicable rules of the road, using its local motion planning modules.

Sandoval, Michael↗
NASA NTRSDate not supplied

A Thinking System and Thinking Autonomy

There are many definitions of what a “Thinking System” (TS) is. The literature primarily addresses what is called “Systems Thinking.” Dr. Marie Morganelli from Southern New Hampshire University states that “Systems thinking is a holistic way to investigate factors and interactions that could contribute to a possible outcome. A mindset more than a prescribed practice, systems thinking provides an understanding of how individuals can work together in different types of teams and through that understanding, create the best possible processes to accomplish just about anything.” So, a TS is a system that is capable of “systems thinking,” as it should be able to “ … create [utilize] the best possible processes [and intelligence] to accomplish just about anything.” To achieve this capability, human-like thinking is required. A truly autonomous system must be one that is capable of human-like thinking. This paper will address “Thinking Autonomy” (TA) enabled by a “Thinking System.” It will describe an architecture with the elements required to achieve the “thinking” behavior: understanding, intellect, reason, decision, will. The paper will further describe the contents and functionality of these elements and how to implement them, including software capabilities needed. Finally, the paper will provide details of a software platform that enables TA, the NASA Platform for Autonomous Systems (NPAS), and describe implementations of thinking systems. Thinking systems will enable a fundamental change how AI and autonomy are implemented. It will change from a “brute force” approach that results in one-time implementations that are minimally intelligent or autonomous to a “thinking” approach where implementations evolve continuously and enable powerful intelligence and autonomy on systems of high complexity as well as on systems-of-systems.

Thinking systems↗
NASA NTRS2023

Artificial Thought is Required for Sustained Autonomy

Current literature primarily addresses what is referred to as “Systems Thinking.” Dr. Marie Morganelli from Southern New Hampshire University states that “Systems thinking is a holistic way to investigate factors and interactions that could contribute to a possible outcome [1]. A mindset more than a prescribed practice, systems thinking provides an understanding of how individuals can work together in different types of teams and through that understanding, create the best possible processes to accomplish just about any-thing.” So, a “Thinking System” is a system that is capable of “systems thinking,” as it should be able to “ …create [utilize] the best possible processes, and possess the [intelligence] to accomplish just about anything.” To achieve this capability, hu-man-like thinking is required. A truly autonomous system must be one that is capable of human-like thinking. Sustained autonomy requires “Thinking Autonomy” (TA) that is enabled by a “Thinking System.”

Autonomous systems↗
NASA NTRS2021

Novel Ways to use the International Spacer Station as an Exploration Analog: International Progress in Planning "ISS4Mars"

In October 2020, International Space Station (ISS) Partner Agencies held a set of international workshops to solicit and develop creative and forward-looking ideas for using the ISS as an analog for preparation for Mars missions during its 3rd decade of operations. The workshops brought together participants from nine international space agencies or organizations, with stakeholders consisting of research managers, discipline experts, technology developers, flight physicians, flight operators, and astronauts. Breakout meetings and brainstorming sessions were conducted focusing on the following topics: Critical hazards and countermeasures for the transit to Mars; gravity transitions and early surface operations; environmental control and life support systems; food systems; human microbiome, microbial monitoring, and planetary protection; medical operations for Mars missions; isolation and confinement; autonomous systems and crew-centered autonomy; and communications delay effects on operations. In many cases the scenarios and approaches identified were compelling but challenging to implement under the current utilization structure used to manage the ISS for experiments. Following the series of workshops, a team of utilization leaders across the ISS partnership worked to compile the workshop recommendations and extract a set of use-cases with their prerequisites and constraints. The work considered the following aspects: what can be effectively done on ISS; which new technologies, approaches and scenarios are feasible; what alternatives could be considered; and what steps should be taken to enable integrated testing and future use of ISS as an analog for Mars missions. The final report will be published so that the use cases can be considered in each agency’s strategic planning processes. This paper will cover the process of international assessment in detail and how this process has influenced and broadened the vision of ISS utilization beyond single experiments to integrated studies and testing for future Mars missions. This approach to international collaboration informs both the next decade of international exploration research on the ISS and advancement of its utilization as an analog for deep space missions. For many of the participating partners, it also helps to frame the strategy for human research in Artemis as we begin planning for human missions to the moon. We conclude with a summary of the progress on the actions in the report and the additional implementation discussions that have occurred across the partnership.

Julie A Robinson↗