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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

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↗
NASA NTRS2020

Demonstrating Assurance of Model-Based Fault Diagnosis Systems on an Operational Mission

Developers of robotic scientific and commercial spacecraft are trending towards use of onboard autonomous capabilities for responding quickly to dynamic environments and rapidly changing situations. These capabilities need to know the state of the spacecraft’s health. Model-based fault diagnosis (MBFD) is an approach to estimating health by continuously verifying accurate behavior and diagnosing off-nominal behavior. Proper functioning of MBFD depends on 1) the quality of the diagnostic system model that is analyzed and compared to commands and onboard measurements to estimate a system’s health state, and 2) the correct functionality of the diagnosis engine interrogating the model and comparing its analyses to observed system behavior. Our goal is to develop Verification and Validation (V&V) techniques for MBFD to provide future missions sufficient confidence in its functionality and performance to deploy it on the systems they develop. Our work has been focused on infusing the techniques we developed earlier to an operational mission. First, we are constructing diagnostic models of a spacecraft attitude control system and updating our diagnostic engine so they can be demonstrated aboard the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, an operational spacecraft for which experiments in autonomy are being planned and executed, using the V&V techniques we have previously developed to assure they are both correct and complete. Since it is nearing the end of its life, ASTERIA provides a unique opportunity to demonstrate MBFD since the monitored components are expected to fail. Our demonstration will give system developers additional confidence to make timely, informed MBFD deployment decisions. Second, we will be completing performance assessments of the diagnostic engine/diagnostic model ensemble both on the flight system and ground-based testbeds to gain confidence in MBFD’s ability to run successfully in a spacecraft’s resource-constrained environment without adversely affecting other on-board activities. Finally, we are capturing our experience in preparing this demonstration in a set of checklists and guidance documents. Current practice includes high-level institutional guidance documents and standards, but at a high level of abstraction that does not necessarily address specific MBFD concerns. The purpose of the new checklists is to provide future mission developers clear, unambiguous, procedure-oriented guidance on assuring MBFD. This paper describes our work in these areas. For the first area, we describe the diagnostic models and updated diagnostic engine that will be used for the on-board demonstration. We describe how the V&V techniques we developed earlier are used to assure model and engine correctness and completeness. For the second area, we identify the performance measurement and assessment techniques used to characterize the diagnostic engine and diagnostic models, and discuss the effect of measured performance on overall mission operation. Finally, we present the checklist and guidance documents and describe how they meet the goals of providing system developers with clear, unambiguous, procedure-oriented guidance on MBFD assurance. We show how the techniques we have developed map into those artifacts.

Nikora, Allen↗
NASA NTRS2016

Workshop on Assurance for Autonomous Systems for Aviation

This report describes the workshop on Assurance for Autonomous Systems for Aviation that was held in January 2016 in conjunction with the SciTech 2016 conference held in San Diego, CA. The workshop explored issues related to assurance for autonomous systems and also the idea of trust in these systems. Specifically, we focused on discussing current practices for assurance of autonomy, identifying barriers specific to autonomy as related to assurance as well as operational scenarios demonstrating the need to address the barriers. Furthermore, attention was given to identifying verification techniques that may be applicable to autonomy, as well as discussing new research directions needed to address barriers, thereby involving potential shifts in current practices.

assurance↗
NASA NTRSDate not supplied

A Remote, Human-in-the-Loop Evaluation of a Multiple-Drone Delivery Operation

Over time, advances in unmanned aircraft systems (UAS) have enabled a shift in the operational paradigm from one operator managing one aircraft to that of multiple operators working together to manage multiple aircraft. This shift has highlighted the need for effective human-autonomy teaming methods to maintain manageable workload levels for operators as well as high standards of system performance and safety. This paper presents a study aimed at evaluating whether automation can help operators manage workload during small UAS (sUAS) package delivery scenarios featuring contingency situations. These contingency situations, resulting from unplanned UAS Volume Reservations (UVRs), required flight path reroutes for multiple aircraft simultaneously. The study manipulated the number of aircraft affected by the UVRs and the level of automation support. The presence of terrain conflicts was also controlled within each scenario. Due to the COVID-19 pandemic, subjects were not able to gain direct access to the Ground Control System (GCS). Therefore, the study was conducted using a subject-surrogate paradigm that required subjects to relay commands through a verbal protocol from remote locations outside of the lab to a researcher surrogate who had direct control of the GCS interfaces at the lab location. Results show that the automated support condition was associated with faster reroute response times, more efficient reroute maneuvers, and significantly lower levels of perceived workload than the manual reroute condition. However, the automation support level did not significantly impact pilots’ ability to avoid the UVR successfully; pilots were overwhelmingly capable of avoiding the UVR in all conditions. The presence of terrain conflicts primarily impacted pilot performance by leading to multiple uploads per vehicle, which was not typically required when pilots only needed to maneuver laterally. Although subjects did not have direct control over the GCS, subjective ratings indicate that the displays under test provided them with sufficient information to manage their aircraft and promptly respond to the unplanned UVRs. Overall, the objective and subjective data strongly suggest that the verbal protocol and subject-surrogate paradigm were effective methods for collecting data remotely amid the COVID-19 pandemic.

multi-UAS↗
NASA NTRS1996

Low-Cost Mission Operations

This paper discusses the transition between traditional planetary missions (requiring constant operational control and limited in size only by booster capability) and the cheaper missions of the New Millennium spacecraft, which will be smaller and will have a great deal of autonomy.

New Millennium spacecraft operations spacecraft au↗
NASA NTRSDate not supplied

An Overview of Advanced Air Mobility Research at NASA

Advanced Air Mobility (AAM) will enable new types of aircraft to operate more cleanly, efficiently, and quietly, complemented by higher levels of autonomy and automation, and supported by air traffic management systems and infrastructure. The operations that these aircraft and systems are intended to conduct are designed to support missions that cover a varied set of use cases. The National Aeronautics and Space Administration (NASA) has been helping to lead the way in its AAM research through a broad portfolio of efforts that leverages multiple internal activities and external collaborations with industry and government. As the AAM concept has continued to advance, it has also become clear that there are very likely great benefits in its application to disaster response and the challenges posed by such complex events. In this application, NASA is leveraging its foundational work performed in partnership with the Japan Aerospace Exploration Agency (JAXA) on integrated unmanned and manned aircraft operations in disaster response situations. The joint NASA and JAXA work, along with the ongoing AAM efforts, have contributed to the formulation of a new project that will expand the scope of technology integration with an initial focus on wildland firefighting.

advanced air mobility↗
DOE OSTI2025

GIScience in the era of Artificial Intelligence: a research agenda towards Autonomous GIS

The advent of generative AI exemplified by large language models (LLMs) opens new ways to represent and compute geographic information and transcends the process of geographic knowledge production, driving geographic information systems (GIS) towards autonomous GIS. Leveraging LLMs as the decision core, autonomous GIS can independently generate and execute geoprocessing workflows to perform spatial analysis. In this vision paper, we further elaborate on the concept of autonomous GIS and present a conceptual framework that defines its five autonomous goals, five levels of autonomy, five core functions, and three operational scales. We demonstrate how autonomous GIS could perform geospatial data retrieval, spatial analysis, and map making with four proof-of-concept GIS agents. We conclude by identifying critical challenges and future research directions, including fine-tuning and self-growing decision-cores, autonomous modelling, and examining the societal and practical implications of autonomous GIS. By establishing the groundwork for a paradigm shift in GIScience, this paper envisions a future where GIS moves beyond traditional workflows to autonomously reason, derive, innovate, and advance geospatial solutions to pressing global challenges. Meanwhile, we emphasize that as we design and deploy increasingly intelligent geospatial systems, we carry a responsibility to ensure they are developed in socially responsible ways, serve the public good, and support the continued value of human geographic insight in an AI-augmented future.

Autonomous GI↗
NASA NTRS1986

Operations and support for the next-generation space transportation system

The role of operations and support in the design of future space transportation systems (STSs) is studied. There is a need to reduce launch and operation costs for future space systems. Methods for reducing the cost of ground operations and supports for a STS are described. Technological advances such as expert systems, robotics, and sensors, and reduction in management of operations are discussed. Changes in the management of flight operations and control, from a manpower intensive monitoring to a strong vehicle autonomy, are examined. The development of equipment and procedures to improve space operations and reduce costs is analyzed. The use of a clean sheet approach for building a STS is proposed.

Sawaya, G. J.↗
NASA NTRS1985

Overview of the NASA automation and robotics research program

NASA studies over the last eight years have identified five opportunities for the application of automation and robotics technology: (1) satellite servicing; (2) system monitoring, control, sequencing and diagnosis; (3) space manufacturing; (4) space structure assembly; and (5) planetary rovers. The development of these opportunities entails two technology R&D thrusts: telerobotics and system autonomy; both encompass such concerns as operator interface, task planning and reasoning, control execution, sensing, and systems integration.

Holcomb, Lee↗
NASA NTRS1989

A prototype autonomous agent for crew and equipment retrieval in space

The ground-based demonstration of Extra Vehicular Activity (EVA) Retriever, a voice-supervised, intelligent, free-flying robot, is designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The EVA Retriever software is required to autonomously plan and execute a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles. The software architecture incorporates a hierarchical decomposition of the control system that is horizontally partitioned into five major functional subsystems: perception, world model, reasoning, sensing, and acting. The design provides for supervised autonomy as the primary mode of operation with teleoperation as the backup mode. It is intended to be an evolutionary system improving in capability over time and as it earns crew trust through reliable operation.

Erickson, J. D.↗
NASA NTRS1993

Air Force construction automation/robotics

The Air Force has several missions which generate unique requirements that are being met through the development of construction robotic technology. One especially important mission will be the conduct of Department of Defense (DOD) space activities. Space operations and other missions place construction/repair equipment operators in dangerous environments and potentially harmful situations. Additionally, force reductions require that human resources be leveraged to the maximum extent possible, and more stringent construction repair requirements push for increased automation. To solve these problems, the U.S. Air Force is undertaking a research and development effort at Tyndall AFB, FL, to develop robotic construction/repair equipment. This development effort involves the following technologies: teleoperation, telerobotics, construction operations (excavation, grading, leveling, tool change), robotic vehicle communications, vehicle navigation, mission/vehicle task control architecture, and associated computing environment. The ultimate goal is the fielding of a robotic repair capability operating at the level of supervised autonomy. This paper will discuss current and planned efforts in space construction/repair, explosive ordnance disposal, hazardous waste cleanup, and fire fighting.

Nease, A. D.↗
NASA NTRS1992

Technology test results from an intelligent, free-flying robot for crew and equipment retrieval in space

The ground-based demonstrations of Extra Vehicular Activity (EVA) Retriever, a voice-supervised, intelligent, free-flying robot, are designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The EVA Retriever software is required to autonomously plan and execute a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles with subsequent object handover. The software architecture incorporates a heirarchical decomposition of the control system that is horizontally partitioned into five major functional subsystems: sensing, perception, world model, reasoning, and acting. The design provides for supervised autonomy as the primary mode of operation. It is intended to be an evolutionary system improving in capability over time and as it earns crew trust through reliable and safe operation. This paper gives an overview of the hardware, a focus on software, and a summary of results achieved recently from both computer simulations and air bearing floor demonstrations. Limitations of the technology used are evaluated. Plans for the next phase, during which moving targets and obstacles drive realtime behavior requirements, are discussed.

Erickson, J.↗
NASA NTRS1994

Air Force construction automation/robotics

The Air Force has several unique requirements that are being met through the development of construction robotic technology. The missions associated with these requirements place construction/repair equipment operators in potentially harmful situations. Additionally, force reductions require that human resources be leveraged to the maximum extent possible and that more stringent construction repair requirements push for increased automation. To solve these problems, the U.S. Air Force is undertaking a research and development effort at Tyndall AFB, FL to develop robotic teleoperation, telerobotics, robotic vehicle communications, automated damage assessment, vehicle navigation, mission/vehicle task control architecture, and associated computing environment. The ultimate goal is the fielding of robotic repair capability operating at the level of supervised autonomy. The authors of this paper will discuss current and planned efforts in construction/repair, explosive ordnance disposal, hazardous waste cleanup, fire fighting, and space construction.

Nease, AL↗
NASA NTRS1994

JPL space robotics: Present accomplishments and future thrusts

Complex missions require routine and unscheduled inspection for safe operation. The purpose of research in this task is to facilitate structural inspection of the planned Space Station while mitigating the need for extravehicular activity (EVA), and giving the operator supervisory control over detailed and somewhat mundane, but important tasks. The telerobotic system enables inspection relative to a given reference (e.g., the status of the facility at the time of the last inspection) and alerts the operator to potential anomalies for verification and action. There are two primary objectives of this project: (1) To develop technologies that enable well-integrated NASA ground-to-orbit telerobotics operations, and (2) to develop a prototype common architecture workstation which implements these capabilities for other NASA technology projects and planned NASA flight applications. This task develops and supports three telerobot control modes which are applicable to time delay operation: Preview teleoperation, teleprogramming, and supervised autonomy.

Weisbin, C. R.↗
NASA NTRS2005

Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue

Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion.

Zornetzer, Steve↗
NASA NTRS2007

Solving the AI Planning Plus Scheduling Problem Using Model Checking via Automatic Translation from the Abstract Plan Preparation Language (APPL) to the Symbolic Analysis Laboratory (SAL)

This paper describes a translator from a new planning language named the Abstract Plan Preparation Language (APPL) to the Symbolic Analysis Laboratory (SAL) model checker. This translator has been developed in support of the Spacecraft Autonomy for Vehicles and Habitats (SAVH) project sponsored by the Exploration Technology Development Program, which is seeking to mature autonomy technology for the vehicles and operations centers of Project Constellation.

Butler, Ricky W.↗
NASA NTRS2012

Evidence Report: Risk of Performance Errors Due to Training Deficiencies

The Risk of Performance Errors Due to Training Deficiencies is identified by the National Aeronautics and Space Administration (NASA) Human Research Program (HRP) as a recognized risk to human health and performance in space. The HRP Program Requirements Document (PRD) defines these risks. This Evidence Report provides a summary of the evidence that has been used to identify and characterize this risk. Given that training content, timing, intervals, and delivery methods must support crew task performance, and given that training paradigms will be different for long-duration missions with increased crew autonomy, there is a risk that operators will lack the skills or knowledge necessary to complete critical tasks, resulting in flight and ground crew errors and inefficiencies, failed mission and program objectives, and an increase in crew injuries.

Barshi, Immanuel↗