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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

The Value of a Spaceflight Clinical Decision Support System for Earth-Independent Medical Operations

As NASA prepares for crewed lunar missions over the next several years, plans are also underway to journey farther into deep space. Deep space exploration will require a paradigm shift in astronaut medical support toward progressively earth-independent medical operations (EIMO). The Exploration Medical Capability (ExMC) element of NASA’s Human Research Program (HRP) is investigating the feasibility and value of advanced capabilities to promote and enhance EIMO. Currently, astronauts rely on real-time communication with ground-based medical providers. However, as the distance from Earth increases, so do communication delays and disruptions. Moreover, resupply and evacuation will become increasingly complex, if not impossible, on deep space missions. In contrast to today’s missions in low earth orbit (LEO), where most medical expertise and decision-making are ground-based, an exploration crew will need to autonomously detect, diagnose, treat, and prevent medical events. Due to the sheer amount of pre-mission training required to execute a human spaceflight mission, there is often little time to devote exclusively to medical training. One potential solution is to augment the long duration exploration crew’s knowledge, skills, and abilities with a clinical decision support system (CDSS). An analysis of preliminary data indicates the potential benefits of a CDSS to mission outcomes when augmenting cognitive and procedural performance of an autonomous crew performing medical operations, and we provide an illustrative scenario of how such a CDSS might function.

Brian K. Russell↗
NASA NTRS2015

AMO EXPRESS: A Command and Control Experiment for Crew Autonomy Onboard the International Space Station

NASA is investigating a range of future human spaceflight missions, including both Mars-distance and Near Earth Object (NEO) targets. Of significant importance for these missions is the balance between crew autonomy and vehicle automation. As distance from Earth results in increasing communication delays, future crews need both the capability and authority to independently make decisions. However, small crews cannot take on all functions performed by ground today, and so vehicles must be more automated to reduce the crew workload for such missions. NASA's Advanced Exploration Systems Program funded Autonomous Mission Operations (AMO) project conducted an autonomous command and control experiment on-board the International Space Station that demonstrated single action intelligent procedures for crew command and control. The target problem was to enable crew initialization of a facility class rack with power and thermal interfaces, and involving core and payload command and telemetry processing, without support from ground controllers. This autonomous operations capability is enabling in scenarios such as initialization of a medical facility to respond to a crew medical emergency, and representative of other spacecraft autonomy challenges. The experiment was conducted using the Expedite the Processing of Experiments for Space Station (EXPRESS) rack 7, which was located in the Port 2 location within the U.S Laboratory onboard the International Space Station (ISS). Activation and deactivation of this facility is time consuming and operationally intensive, requiring coordination of three flight control positions, 47 nominal steps, 57 commands, 276 telemetry checks, and coordination of multiple ISS systems (both core and payload). Utilization of Draper Laboratory's Timeliner software, deployed on-board the ISS within the Command and Control (C&C) computers and the Payload computers, allowed development of the automated procedures specific to ISS without having to certify and employ novel software for procedure development and execution. The procedures contained the ground procedure logic and actions as possible to include fault detection and recovery capabilities. The autonomous operations concept includes a reduction of the amount of data a crew operator is required to verify during activation or de-activation, as well as integration of procedure execution status and relevant data in a single integrated display. During execution, the auto-procedures (via Timerliner) provide a step-by-step messaging paradigm and a high-level status upon termination. This messaging and high-level status is the only data generated for operator display. To enhance situational awareness of the operator, the Web-based Procedure Display (WebPD) provides a novel approach to the issues of procedure display and execution tracking. WebPD is a web based application that serves as the user interface for electronic procedure execution. It incorporates several aspects of the HTML5 standard. Procedures are written in a dialect of XML called Procedure Representation Language (PRL). WebPD tracks execution status in the procedure or procedures being displayed. WebPD aggregates and simplifies the auto-sequence execution status information, and formatted to be easily followed and understood by an operator who is not dedicated to actively monitoring the task. WebPD also provides an integrated data and control interface to pause or halt the execution in order to provide a check point of operation and to examine progress before starting the next sequence of activities. For this demonstration, the procedure was initiated and monitored from the ground. As the Timeliner sequences executed, their high-level execution status was written to PLMDM memory. This memory is read and downlinked via Ku-Band at a 1 Hz rate. The data containing the high-level execution status is de-commutated on the ground, and rebroadcast for WebPD consumption. A future demonstration will be performed onboard, with ISS astronauts initiating the operations instead of ground controllers. The AMO EXPRESS experiment demonstrated activation and de-activation of EXPRESS rack 7, providing the capability of future single button activations and deactivations of facility class racks. The experiment achieved numerous technical and operations 'firsts' for the ISS

Stetson, Howard K.↗
NASA NTRS1992

Manifold traversing as a model for learning control of autonomous robots

This paper describes a recipe for the construction of control systems that support complex machines such as multi-limbed/multi-fingered robots. The robot has to execute a task under varying environmental conditions and it has to react reasonably when previously unknown conditions are encountered. Its behavior should be learned and/or trained as opposed to being programmed. The paper describes one possible method for organizing the data that the robot has learned by various means. This framework can accept useful operator input even if it does not fully specify what to do, and can combine knowledge from autonomous, operator assisted and programmed experiences.

Szakaly, Zoltan F.↗
NASA NTRSDate not supplied

Towards Persistent Space Observations through Autonomous Multi-Agent Formations

Sensing platforms must advance in scale and sophistication in order to support increasingly ambitious missions across Earth and space science; intelligence, surveillance, and reconnaissance (ISR); and planetary exploration. Distributed, persistent observation platforms have the potential to play a pivotal role in next generation missions through improved area coverage, enhanced situational awareness, and faster identification of trends and changes. The Multi-Agent Clusters for Persistent Observations from Space (MACPOS) project at NASA Langley Research Center is developing key technologies for the autonomous, heterogeneous formations that will comprise such platforms. Research thrusts include dynamic formation negotiation for self-assembling clusters of agents, distributed motion planning, and coordinated trajectory execution. Adaptive leader-follower formation negotiation allows agents to cluster and break off as necessary to adapt to both nominal and new mission objectives. Coordinated motion planning and execution maintain the formation while ensuring safe separation distances among agents and obstacles in the environment. These capabilities align MACPOS with NASA’s initiative for space and surface in-situ assembly through fundamental technology development for autonomous multi-agent systems. This paper presents an overview and early progress for the MACPOS project. We describe the system architecture for both individual agents and the overall fleet. Design considerations are given for the planning, control, and metrology subsystems. Finally, we discuss planned project milestones and the expected course of development.

Matthew P Vaughan↗
NASA NTRS1990

System control of an autonomous planetary mobile spacecraft

The goal is to suggest the scheduling and control functions necessary for accomplishing mission objectives of a fairly autonomous interplanetary mobile spacecraft, while maximizing reliability. Goals are to provide an extensible, reliable system conservative in its use of on-board resources, while getting full value from subsystem autonomy, and avoiding the lure of ground micromanagement. A functional layout consisting of four basic elements is proposed: GROUND and SYSTEM EXECUTIVE system functions and RESOURCE CONTROL and ACTIVITY MANAGER subsystem functions. The system executive includes six subfunctions: SYSTEM MANAGER, SYSTEM FAULT PROTECTION, PLANNER, SCHEDULE ADAPTER, EVENT MONITOR and RESOURCE MONITOR. The full configuration is needed for autonomous operation on Moon or Mars, whereas a reduced version without the planning, schedule adaption and event monitoring functions could be appropriate for lower-autonomy use on the Moon. An implementation concept is suggested which is conservative in use of system resources and consists of modules combined with a network communications fabric. A language concept termed a scheduling calculus for rapidly performing essential on-board schedule adaption functions is introduced.

Dias, William C.↗
DOE OSTI2025

Design, Preparation, and Execution of the 100-AV Field Test for the CIRCLES Consortium: Methodology and Implementation of the Largest Mobile Traffic Control Experiment to Date

This article presents the comprehensive design, setup, execution, and evaluation of the MegaVanderTest (MVT) experiment conducted by the Congestion Impacts Reduction via CAV-in-the-Loop Lagrangian Energy Smoothing (CIRCLES) Consortium, which aimed to mitigate traffic congestion using partially autonomous vehicles (AVs) (see “Summary”). The experiment involved 100 vehicles on Nashville’s Interstate 24 (I-24) highway, utilizing various control algorithms to smooth stop-and-go traffic waves. The execution of the MVT experiment required a coordinated effort from multiple teams. This article details the meticulous planning process, the coordinated efforts of multiple teams, and the innovative use of a dynamic agent-based simulation framework for traffic evaluation. Here, the contributions of this work include demonstrating and providing a detailed roadmap for large-scale live traffic experiments, illustrating the lessons learned from the MVT experiment, and introducing the other articles in this issue and their complementary relationship in the MVT experiment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

AI-Ready Semantic Infrastructure for CEBAF: From CED to PALS Knowledge Graphs

JLab and PNNL are jointly developing an AI-ready data ecosystem that exposes the Continuous Electron Beam Acceleration Facility’s (CEBAF’s) operational configuration, lattice description, and control-system channels to agentic optimization frameworks through a standards-based semantic layer. The effort integrates the existing facility-specific CEBAF Element Database (CED) with extensions of the emerging facility-agnostic Particle Accelerator Lattice Standard (PALS) to produce a knowledge graph (KG) containing coherent, machine-interpretable views of devices, signals, and regions. With this KG, CEBAF’s setpoints, readbacks, and device hierarchies become queryable using a uniform declarative graph query language (e.g., Neo4j Cypher), providing intents and inspectable semantics suitable for agentic control. The resulting graph-backed interfaces will allow autonomous agents to retrieve authoritative machine configurations, reason over device- and signal-level relationships, and execute tuning and diagnostic workflows without bespoke CEBAF-specific logic, thereby delivering a scalable pathway from operational data to trustworthy agentic accelerator tuning frameworks.

Zhang, He [Thomas Jefferson National Accelerator F↗
NASA NTRS2012

Virtual Machine Language 2.1

VML (Virtual Machine Language) is an advanced computing environment that allows spacecraft to operate using mechanisms ranging from simple, time-oriented sequencing to advanced, multicomponent reactive systems. VML has developed in four evolutionary stages. VML 0 is a core execution capability providing multi-threaded command execution, integer data types, and rudimentary branching. VML 1 added named parameterized procedures, extensive polymorphism, data typing, branching, looping issuance of commands using run-time parameters, and named global variables. VML 2 added for loops, data verification, telemetry reaction, and an open flight adaptation architecture. VML 2.1 contains major advances in control flow capabilities for executable state machines. On the resource requirements front, VML 2.1 features a reduced memory footprint in order to fit more capability into modestly sized flight processors, and endian-neutral data access for compatibility with Intel little-endian processors. Sequence packaging has been improved with object-oriented programming constructs and the use of implicit (rather than explicit) time tags on statements. Sequence event detection has been significantly enhanced with multi-variable waiting, which allows a sequence to detect and react to conditions defined by complex expressions with multiple global variables. This multi-variable waiting serves as the basis for implementing parallel rule checking, which in turn, makes possible executable state machines. The new state machine feature in VML 2.1 allows the creation of sophisticated autonomous reactive systems without the need to develop expensive flight software. Users specify named states and transitions, along with the truth conditions required, before taking transitions. Transitions with the same signal name allow separate state machines to coordinate actions: the conditions distributed across all state machines necessary to arm a particular signal are evaluated, and once found true, that signal is raised. The selected signal then causes all identically named transitions in all present state machines to be taken simultaneously. VML 2.1 has relevance to all potential space missions, both manned and unmanned. It was under consideration for use on Orion.

Riedel, Joseph E.↗
NASA NTRS2018

Increasing Human Spaceflight Capabilities: Demonstration of Crew Autonomy Through Self-Scheduling Onboard International Space Station

For the first time in a spaceflight operational environment, our team enabled an ISS (International Space Station) crewmember to plan, reschedule, and execute their activities in real-time while abiding by flight and scheduling constraints. The Crew Autonomous Scheduling Test (CAST) investigated the novel concept of operations: allowing crew to manage their own timeline.

crew autonomy↗
NASA NTRSDate not supplied

Using Artificial Intelligence and Machine Learning to Enhance Mission Design and Operations of the Habitable Worlds Observatory (HWO)

One key aspect in the development of HWO is the early deployment of artificial intelligence (AI) and machine learning (ML) to enhance mission science and operations. Our subtask group is part of the HWO AI/ML working group and focuses on AI and ML for mission operations. Our task group seeks to educate other HWO working groups about AI and ML capabilities for mission operations, investigate how to bridge technology gaps, and enable new capabilities particularly in the areas of observational scheduling, instrument health monitoring, and downlink operations. We focus on mission tasking / scheduling both for mission analysis in development and operations. AI and ML for mission scheduling includes: tools to support proposal calls and review, ensuring fairness in calls for proposals, community peer reviews and ease workloads, as well as in-flight and ground software development (e.g., using natural language processing (NLP) to support process automation from requirements). AI and ML for the mission’s development and operations include 1) anomaly detection and prediction (from onboard and ground based tools) to monitor the spacecraft’s health, 2) ground-based automated scheduling for mission operations including long-term and short-term planning and maintenance, and 3) flight system flexible execution (as flight proven for Spitzer and JWST) to enable robust execution despite execution variations, and 4) data analysis for prioritization (e.g., real-time data evaluation leading to autonomous actions and adjustments, high-priority identification, onboard data compression, etc.). Incorporation of ML and AI will enable HWO to address the major science questions related to exoplanet characterization, general astrophysics, and solar system exploration and also extend the boundaries of space mission technologies.

Mark Moussa↗
NASA NTRS2015

Software Testbed for Developing and Evaluating Integrated Autonomous Subsystems

To implement fault tolerant autonomy in future space systems, it will be necessary to integrate planning, adaptive control, and state estimation subsystems. However, integrating these subsystems is difficult, time-consuming, and error-prone. This paper describes Intelliface/ADAPT, a software testbed that helps researchers develop and test alternative strategies for integrating planning, execution, and diagnosis subsystems more quickly and easily. The testbed's architecture, graphical data displays, and implementations of the integrated subsystems support easy plug and play of alternate components to support research and development in fault-tolerant control of autonomous vehicles and operations support systems. Intelliface/ADAPT controls NASA's Advanced Diagnostics and Prognostics Testbed (ADAPT), which comprises batteries, electrical loads (fans, pumps, and lights), relays, circuit breakers, invertors, and sensors. During plan execution, an experimentor can inject faults into the ADAPT testbed by tripping circuit breakers, changing fan speed settings, and closing valves to restrict fluid flow. The diagnostic subsystem, based on NASA's Hybrid Diagnosis Engine (HyDE), detects and isolates these faults to determine the new state of the plant, ADAPT. Intelliface/ADAPT then updates its model of the ADAPT system's resources and determines whether the current plan can be executed using the reduced resources. If not, the planning subsystem generates a new plan that reschedules tasks, reconfigures ADAPT, and reassigns the use of ADAPT resources as needed to work around the fault. The resource model, planning domain model, and planning goals are expressed using NASA's Action Notation Modeling Language (ANML). Parts of the ANML model are generated automatically, and other parts are constructed by hand using the Planning Model Integrated Development Environment, a visual Eclipse-based IDE that accelerates ANML model development. Because native ANML planners are currently under development and not yet sufficiently capable, the ANML model is translated into the New Domain Definition Language (NDDL) and sent to NASA's EUROPA planning system for plan generation. The adaptive controller executes the new plan, using augmented, hierarchical finite state machines to select and sequence actions based on the state of the ADAPT system. Real-time sensor data, commands, and plans are displayed in information-dense arrays of timelines and graphs that zoom and scroll in unison. A dynamic schematic display uses color to show the real-time fault state and utilization of the system components and resources. An execution manager coordinates the activities of the other subsystems. The subsystems are integrated using the Internet Communications Engine (ICE). an object-oriented toolkit for building distributed applications.

Testbed↗
NASA NTRS2016

Development of Navigation Doppler Lidar for Future Landing Mission

A coherent Navigation Doppler Lidar (NDL) sensor has been developed under the Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) project to support future NASA missions to planetary bodies. This lidar sensor provides accurate surface-relative altitude and vector velocity data during the descent phase that can be used by an autonomous Guidance, Navigation, and Control (GN&C) system to precisely navigate the vehicle from a few kilometers above the ground to a designated location and execute a controlled soft touchdown. The operation and performance of the NDL was demonstrated through closed-loop flights onboard the rocket-propelled Morpheus vehicle in 2014. In Morpheus flights, conducted at the NASA Kennedy Space Center, the NDL data was used by an autonomous GN&C system to navigate and land the vehicle precisely at the selected location surrounded by hazardous rocks and craters. Since then, development efforts for the NDL have shifted toward enhancing performance, optimizing design, and addressing spaceflight size and mass constraints and environmental and reliability requirements. The next generation NDL, with expanded operational envelope and significantly reduced size, will be demonstrated in 2017 through a new flight test campaign onboard a commercial rocketpropelled test vehicle.

Amzajerdian, Farzin↗
NASA NTRSDate not supplied

Testing a Run-Time Assurance Framework Coupled with Integrated Risk Mitigation Capabilities for Autonomous Urban UAS Flights

The In-Time Aviation Safety Management System (IASMS) Concept of Operations (ConOps) envisions new capabilities to monitor, assess, and mitigate flight safety risks. Systems will be tailored to mission type, vehicle/equipage type, operational environment, and safety risk tolerance. Within an IASMS framework, several capabilities may be implemented spanning three operational phases (pre-flight, in-flight, and post-flight/off-line); and consisting of lower level functions and information services which may reside onboard the aircraft, on third-party server(s), and/or on ground/operator station(s). Each capability will be designed to produce and disseminate safety-relevant information; perform detection, diagnosis, and prediction of unsafe situations; and/or execute mitigation actions when hazardous events warrant such changes. This paper focuses on recent testing of airborne capabilities that demonstrate inflight aspects of the overarching concept for autonomous unmanned aircraft systems (UAS) operations in urban environments. A flight test architecture is described that applies run-time assurance principles (e.g., executes independent of the unassured autopilot), real-time risk assessment, and a technique to execute contingencies if necessary either automatically or via pilot intervention. Several tests using small UAS were conducted to verify the assured in-flight risk mitigation capability. The paper draws significantly from a larger NASA technical report and recent prior conference papers, providing additional details. Data is analyzed for two representative flights to illustrate the performance for various sequential and simultaneous hazards used during testing. During each automated flight, several hazards are encountered at various points along the flight path. At each point, the hazard is mitigated by the system, with the vehicle then continuing to subsequent points. The paper concludes with lessons-learned regarding relevant aspects of the overarching IASMS concept and how it may be updated and further advanced in the future.

population activity↗
NASA NTRS2010

360-Degree Visual Detection and Target Tracking on an Autonomous Surface Vehicle

This paper describes perception and planning systems of an autonomous sea surface vehicle (ASV) whose goal is to detect and track other vessels at medium to long ranges and execute responses to determine whether the vessel is adversarial. The Jet Propulsion Laboratory (JPL) has developed a tightly integrated system called CARACaS (Control Architecture for Robotic Agent Command and Sensing) that blends the sensing, planning, and behavior autonomy necessary for such missions. Two patrol scenarios are addressed here: one in which the ASV patrols a large harbor region and checks for vessels near a fixed asset on each pass and one in which the ASV circles a fixed asset and intercepts approaching vessels. This paper focuses on the ASV's central perception and situation awareness system, dubbed Surface Autonomous Visual Analysis and Tracking (SAVAnT), which receives images from an omnidirectional camera head, identifies objects of interest in these images, and probabilistically tracks the objects' presence over time, even as they may exist outside of the vehicle's sensor range. The integrated CARACaS/SAVAnT system has been implemented on U.S. Navy experimental ASVs and tested in on-water field demonstrations.

ASV (AUTONOMOUS SEA SURFACE VEHICLE)↗
NASA NTRS2013

Autonomous Aerobraking Development Software: Phase 2 Summary

NASA has used aerobraking at Mars and Venus to reduce the fuel required to deliver a spacecraft into a desired orbit compared to an all-propulsive solution. Although aerobraking reduces the propellant, it does so at the expense of mission duration, large staff, and DSN coverage. These factors make aerobraking a significant cost element in the mission design. By moving on-board the current ground-based tasks of ephemeris determination, atmospheric density estimation, and maneuver sizing and execution, a flight project would realize significant cost savings. The NASA Engineering and Safety Center (NESC) sponsored Phase 1 and 2 of the Autonomous Aerobraking Development Software (AADS) study, which demonstrated the initial feasibility of moving these current ground-based functions to the spacecraft. This paper highlights key state-of-the-art advancements made in the Phase 2 effort to verify that the AADS algorithms are accurate, robust and ready to be considered for application on future missions that utilize aerobraking. The advancements discussed herein include both model updates and simulation and benchmark testing. Rigorous testing using observed flight atmospheres, operational environments and statistical analysis characterized the AADS operability in a perturbed environment.

Cianciolo, Alicia D.↗
NASA NTRS2012

Autonomous RPOD Technology Challenges for the Coming Decade

Rendezvous Proximity Operations and Docking (RPOD) technologies are important to a wide range of future space endeavors. This paper will review some of the recent and ongoing activities related to autonomous RPOD capabilities and summarize the current state of the art. Gaps are identified where future investments are necessary to successfully execute some of the missions likely to be conducted within the next ten years. A proposed RPOD technology roadmap that meets the broad needs of NASA's future missions will be outlined, and ongoing activities at OSFC in support of a future satellite servicing mission are presented. The case presented shows that an evolutionary, stair-step technology development program. including a robust campaign of coordinated ground tests and space-based system-level technology demonstration missions, will ultimately yield a multi-use main-stream autonomous RPOD capability suite with cross-cutting benefits across a wide range of future applications.

Naasz, Bo J.↗
NASA NTRS2020

Solar Cruiser Technology Maturation Plans

The NASA Marshall Space Flight Center (MSFC) developed the Solar Cruiser mission concept to mature solar sail technology for use in future Heliophysics missions, as well as missions of interest across a broad user community (e.g., space weather and Earth polar observatories). Solar Cruiser will serve as a pathfinder for missions that observe the solar environment from unique vantage points such as a high inclination solar mission opening a fundamentally new range of observational capabilities for the Heliophysics Program and for space weather monitoring. Sustained observations away from the Sun-Earth line (SEL) present unique opportunities for answering the outstanding science questions of Heliophysics, improving space-weather monitoring and prediction, and revealing new information about our Sun and solar system. Propellantless solar sails can be used to create artificial equilibria and maintain indefinite station-keeping at locations sunward of L1 along the SEL, or at any desired offset from the SEL leading or trailing the Earth in its orbit. They can change the heliocentric inclination of a spacecraft from the ecliptic to as high as solar polar, stopping and remaining at any intermediate inclination orbit in between. Sails can be used to hover over the Earth’s poles, using solar photon pressure to offset the Earth’s gravitational attraction, creating functional equivalents of geostationary earth orbits. The Solar Cruiser mission would fly a small spacecraft with a large (>1,600 square meter) solar sail containing embedded reflectivity control devices (RCDs) and photovoltaic cells. The mission concept includes successful deployment of the solar sail, validation of all sail subsystems, controlled station-keeping inside of the Sun-Earth L1 point, attitude control of the sail with the RCDs (including spinning and de-spinning), demonstration of pointing performance for science imaging, and an increase in heliocentric inclination (out of the ecliptic). To demonstrate the requisite sail technology, the Solar Cruiser project will design, fabricate, deploy, and fly the Solar Sail Propulsion Element (SSPE). The SSPE incorporates the following three systems: • The Solar Sail System (SSS) provides the large propulsive surface required for acceleration and smaller reflectivity-changing surfaces for roll control. • The Active Mass Translator System (AMT) provides SSPE motion with respect to the sailcraft bus for pitch and yaw control. • The Solar Sail Attitude Determination and Control System (SSADCS) consists of embedded software to 1) provide autonomous sailcraft attitude estimation, attitude pointing control, and reaction wheel momentum management following sail deployment and 2) execute the uplinked inertial attitude pointing commands to maintain the desired sailcraft trajectory. The plans for maturing each of these technology systems to TRL 5 and beyond are described herein.

Solar Sail↗
NASA NTRSDate not supplied

What is the Role of Usability and Trust in Autonomy?

Usability encompasses learnability, efficiency, memorability, effectiveness, and satisfaction. NASA’s standards for usability acceptance criteria focus on interfaces that help operators achieve their tasks efficiently, effectively, and with satisfaction. However, discussions on usability, especially regarding future highly automated and autonomous systems, rarely include trust. As NASA plans for long-duration exploration missions, it envisions astronauts operating more independently from Mission Control on Earth. This independence will drive the development of these highly automated and autonomous systems that astronauts will use daily. To prepare for this future, our team has developed a scheduling and execution software tool that facilitates self-scheduling, allowing astronauts to independently manage their own schedule without Mission Control’s involvement. Over many years, we have developed, matured, and evaluated our software tool in extreme environments, prioritizing user-centered design and high usability. These evaluations have included multiple campaigns in NASA analogs, including NEEMO, BASALT, and HERA, as well as technology demonstrations onboard the International Space Station. Our recent research on software interfaces for future astronaut autonomy revealed a strong correlation between usability and trust measures. In a controlled lab experiment, we asked novice users to perform a complex scheduling task, during which the software immediately validated the schedule’s constraints and checked for violations. We collected usability (User Experience Questionnaire, UEQ) and trust (Trust in Automated Systems scale, TAS) measures; significant, strong, and moderate correlations emerged between several of the UEQ metrics and TAS. These results support the argument for investing in usability early to enable and sustain trust in highly automated and autonomous systems.

usability↗