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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2025

Localization of Ad-Hoc Lunar Constellations in Communication Failure Modes for Distributed Spacecraft Autonomy

As Lunar missions increase in complexity, inspired by NASA’s Artemis Program, they will require reliable and sufficient Position, Navigation, and Timing (PNT) capability to support the upcoming Lunar users. The navigation service should also be compatible with the smaller platforms, like CubeSats, being sent by the public and private sectors. A non-dedicated, ad-hoc Lunar navigation constellation can provide PNT services on-demand using the non-dedicated swarm assets. Swarm members cooperatively and autonomously localize themselves with minimal interaction from Earth, freeing up valuable bandwidth and ground segment resources. The autonomous localization of Lunar constellations utilizes neighbor two-way intersatellite link (ISL) measurements in a distributed extended Kalman filter (DEKF) system to minimize operating costs. Because the decentralized Lunar PNT system relies on relay communication amongst the agents, network failures or loss of assets among ad-hoc Lunar constellations may impact localization performance. This study presents an evaluation of localization performance under increasing levels of network degradation. A simulation of an ad-hoc Lunar PNT swarm is augmented to include system faults and the impacts of intermittent and permanent failures on localization performance are evaluated. We investigate three potential causes of network degradation: single spacecraft loss, multiple spacecraft loss, and antenna failure. The numerical assessments from the simulation show that the LPNT system under study, based on an autonomous decentralized concept of operation, is highly robust and resilient to communication failures. Minor faults, such as single spacecraft loss, solar interference, technical malfunctions, message delays, and antenna outages, have minimal impact on state estimation, with only a 4.47% and 3.75% degradation in median position error for assets and a representative ground user, respectively, compared to an ideal communication scenario. However, major faults, such as hardware failures or meteor strikes leading to the loss of multiple spacecrafts, are more concerning. The permanent loss of three spacecraft results in a more severe performance degradation, with median position error increasing by 23.3% for assets and 11.7% for a representative ground user, despite the Lunar PNT system remaining functional.

Yeji Kim↗
NASA NTRSDate not supplied

Uncertainty Quantification using Deep Ensembles for Decision Making in Cyber-Physical-Human Systems

In this paper and its companion, Differential Equation Approximation Using Gradient-Boosted Quantile Regression, Robison et al., we examine an approach to quantifying model uncertainty with the aim of increasing the trustworthiness of computational models in human-machine interactions. In Differential Equation Approximation Using Gradient-Boosted Quantile Regression, we focus on gradient-boosted decision trees, while in this one, we give more details about deep ensembles. Uncertainty quantification is crucial for building trustworthy autonomous decision-making agents in human-machine teams. There are two types of uncertainties: aleatoric and epistemic. The former is related to the inherent stochasticity (noise) of the process, whereas the latter is associated with the lack of knowledge or representation capability of models, such as neural networks. By lack of knowledge, we mean the model’s inability to accurately predict outputs for all possible inputs. The aleatory uncertainty can be estimated fairly easily with, for example, filters, whereas epistemic uncertainty is challenging to compute. This paper uses deep ensembles to quantify both aleatory and epistemic uncertainty. It can act as an uncertainty-aware surrogate transition model for decision-making frameworks. "Uncertainty-aware" means that the surrogate transition model should make predictions along with confidence in those predictions. In the context of decision-making, the transition models are ordinary differential equations (ODEs). Since ODEs can be simulated to make one-step or multi-step predictions, a good surrogate model for them should perform reasonably well in both modes. In a multi-step approach, the trajectory sampling method TS∞ was used to propagate uncertainty over multiple steps. The cartpole dynamical system was selected to demonstrate the ability of deep ensembles as good surrogate transition models for decision-making frameworks. The deep ensembles modeled the dynamics of cartpole ODEs and made uncertainty-aware predictions in single-step and multi-step transition modes.

CPH systems↗
NASA NTRS2006

Addressing the Tension Between Strong Perimeter Control an Usability

This paper describes a strong perimeter control system for a general purpose processing system, with the perimeter control system taking significant steps to address usability issues, thus mitigating the tension between strong perimeter protection and usability. A secure front end enforces two-factor authentication for all interactive access to an enclave that contains a large supercomputer and various associated systems, with each requiring their own authentication. Usability is addressed through a design in which the user has to perform two-factor authentication at the secure front end in order to gain access to the enclave, while an agent transparently performs public key authentication as needed to authenticate to specific systems within the enclave. The paper then describes a proxy system that allows users to transfer files into the enclave under script control, when the user is not present to perform two-factor authentication. This uses a pre-authorization approach based on public key technology, which is still strongly tied to both two-factor authentication and strict control over where files can be transferred on the target system. Finally the paper describes an approach to support network applications and systems such as grids or parallel file transfer protocols that require the use of many ports through the perimeter. The paper describes a least privilege approach that dynamically opens ports on a host-specific, if-authorized, as-needed, just-in-time basis.

Hinke, Thomas H.↗
NASA NTRS2005

Workshop on Radical Agent Concepts (WRAC)

Agent technology, along with autonomous and autonomic computing, has emerged as a major field in computing, and will greatly influence the future development of complex computer-based systems. The area of research is strongly influenced by the Autonomic Computing initiative as well as by developments in biologically-inspired computing, and involves interdisciplinary interaction from those involved in research in social intelligence, psychology, arts, biology, computer science, computer communications and philosophy. This volume includes revised versions of papers presented at the workshop. The workshop was structured so as to allow adequate time for discussion and interaction, to exchange ideas and reflect on the motivations, scientific grounds and practical consequences of the concepts presented. Many of the ideas are truly "radical", and so authors were given time to revise their papers to reflect further thoughts on the ideas presented, and to reflect feedback received at the workshop.

Hinchey, Michael G.↗
NASA NTRS2005

Towards the Verification of Human-Robot Teams

Human-Agent collaboration is increasingly important. Not only do high-profile activities such as NASA missions to Mars intend to employ such teams, but our everyday activities involving interaction with computational devices falls into this category. In many of these scenarios, we are expected to trust that the agents will do what we expect and that the agents and humans will work together as expected. But how can we be sure? In this paper, we bring together previous work on the verification of multi-agent systems with work on the modelling of human-agent teamwork. Specifically, we target human-robot teamwork. This paper provides an outline of the way we are using formal verification techniques in order to analyse such collaborative activities. A particular application is the analysis of human-robot teams intended for use in future space exploration.

Fisher, Michael↗
NASA NTRS1992

Design for interaction between humans and intelligent systems during real-time fault management

Initial results are reported to provide guidance and assistance for designers of intelligent systems and their human interfaces. The objective is to achieve more effective human-computer interaction (HCI) for real time fault management support systems. Studies of the development of intelligent fault management systems within NASA have resulted in a new perspective of the user. If the user is viewed as one of the subsystems in a heterogeneous, distributed system, system design becomes the design of a flexible architecture for accomplishing system tasks with both human and computer agents. HCI requirements and design should be distinguished from user interface (displays and controls) requirements and design. Effective HCI design for multi-agent systems requires explicit identification of activities and information that support coordination and communication between agents. The effects are characterized of HCI design on overall system design and approaches are identified to addressing HCI requirements in system design. The results include definition of (1) guidance based on information level requirements analysis of HCI, (2) high level requirements for a design methodology that integrates the HCI perspective into system design, and (3) requirements for embedding HCI design tools into intelligent system development environments.

Malin, Jane T.↗
NASA NTRS2019

A Planning Pipeline for Large Multi-Agent Missions

In complex multi-agent applications, human operators are often tasked with planning and managing large heterogeneous teams of humans and autonomous vehicles. Although the use of these autonomous vehicles broadens the scope of meaningful applications, many of their systems remain unintuitive and difficult to master for human operators whose expertise lies in the application domain and not at the platform level. Current research focuses on the development of individual capabilities necessary to plan multi-agent missions of this scope, placing little emphasis on the integration of these components in to a full pipeline. The work presented in this paper presents a complete and user-agnostic planning pipeline for large multiagent missions known as the HOLII GRAILLE. The system takes a holistic approach to mission planning by integrating capabilities in human machine interaction, flight path generation, and validation and verification. Components – modules – of the pipeline are explored on an individual level, as well as their integration into a whole system. Lastly, implications for future mission planning are discussed.

Chandarana, Meghan↗
NASA NTRSDate not supplied

Creating an Interface to view Multi-Spacecraft Swarm Telemetry

Distributed Spacecraft Systems are a type of multi-spacecraft mission architecture that can not only provide improved resolution, coverage, and availability of existing missions, but also enable missions that would be previously infeasible using traditional approaches. Distributed Spacecraft Autonomy (DSA) is a project developed by the National Aeronautics and Space Administration that enables distributed spacecraft systems. In previous science swarm missions, the spacecraft involved have not been able to communicate with each other without utilizing a ground station. Now that the spacecraft can perform inter-satellite communication, the spacecraft can be treated as a collective. Swarm autonomy is critical for a growing number of satellites which means novel ways of displaying swarm data needs to be implemented. Such systems introduce unique challenges to traditional approaches for command and control of these spacecraft, due to the large number of spacecraft and the complexity of the interactions between them. The ground data system for DSA addresses these challenges through the creation of a custom user interface that allows a single operator to orchestrate a multi-spacecraft swarm in a scalable way. This plenary describes the details of the autonomy demonstration being performed, the requirements of those using the interface to analyze the spacecraft telemetry to assess demonstration success, and the approach taken by the ground systems team to create an interface that satisfies these requirements. This approach involves the creation of several distinct components that correspond to the level of detail presented to the user. These components are based on conventional user roles in human-robot interaction, including supervisor, operator, and mechanic, extended to accommodate the additional overhead of coordinating actions between agents. One main feature of the interface is the listenability matrix component which will represent inter-satellite communications in a heat mapped matrix. The above work described will enable users to command and interact with the spacecraft as a collective.

human-swarm interaction↗
NASA NTRS2006

Adjustably Autonomous Multi-agent Plan Execution with an Internal Spacecraft Free-Flying Robot Prototype

We present an multi-agent model-based autonomy architecture with monitoring, planning, diagnosis, and execution elements. We discuss an internal spacecraft free-flying robot prototype controlled by an implementation of this architecture and a ground test facility used for development. In addition, we discuss a simplified environment control life support system for the spacecraft domain also controlled by an implementation of this architecture. We discuss adjustable autonomy and how it applies to this architecture. We describe an interface that provides the user situation awareness of both autonomous systems and enables the user to dynamically edit the plans prior to and during execution as well as control these agents at various levels of autonomy. This interface also permits the agents to query the user or request the user to perform tasks to help achieve the commanded goals. We conclude by describing a scenario where these two agents and a human interact to cooperatively detect, diagnose and recover from a simulated spacecraft fault.

Dorais, Gregory A.↗
NASA NTRS2002

A Solar System Perspective on Laboratory Astrophysics

Planetary science deals with a wide variety of natural materials in a wide variety of environments. These materials include metals, minerals, ices, gases, plasmas, and organic chemicals. In addition, the newly defined discipline of astrobiology introduces biological materials to planetary science. The environments range from the interiors of planets with megapascal pressures to planetary magnetospheres, encompassing planetary mantles, surfaces, atmospheres, and ionospheres. The interplanetary environment includes magnetic and electrical fields, plasma, and dust. In order to understand planetary processes over these vast ranges, the properties of materials must be known, and most of the necessary information comes from the laboratory. Observations of the bodies and materials in the Solar System are accomplished over the full range of the electromagnetic spectrum by remote sensing from Earth or spacecraft. Comets exemplify this; molecular and atomic identifications are made from the hard ultraviolet to radio wavelengths, while X-rays are emitted as comets interact with the solar wind. Gamma rays from the surfaces of the Moon and asteroids are diagnostic of the mineral and ice content of those bodies; eventually, gamma rays will also be observed by probes to comets. A number of planetary materials are available in the laboratory for extensive Study: rocks from the Moon, Mars, several asteroids, as well as dust from comets (and perhaps the Kuiper Belt) are closely studied at every level, including atomic (isotopic). Even pre-solar interstellar grains isolated from meteorites are scrutinized for composition and crystalline structure. Beyond the materials themselves, various agents and processes have altered them over the 4.6-Gy age of the Solar System. Solar radiation, solar wind particles, trapped magnetospheric particles, cosmic rays, and micrometeoroid impacts have produced chemical, physical, and morphological changes in the atmospheres and on the surfaces of all planetary bodies. These processes are not well understood, so studies in a laboratory setting are especially needed.

Cruikshank, Dale P.↗
NASA NTRSDate not supplied

Enabling Advanced Air Mobility Operations through Appropriate Trust in Human-Autonomy Teaming: Foundational Research Approaches and Applications

Emerging Advanced Air Mobility(AAM)operations will be enabled by increasingly autonomous systems, requiring technologies to take on more responsibilities and fundamentally altering traditional human-automation interaction paradigms. The growing reliance on higher levels of automation will necessitate research to identify capabilities and principles that facilitate humans and machines working and thinking better together, i.e., human-autonomy teaming (HAT). Trust is an inherent requirement in effective teams because when members work interdependently, those agents (human, automation) must be willing to accept a level of risk to rely upon each other to reach goals and contribute to team tasks. This work provides an initial approach to enabling AAM operations through appropriate trust within HAT. The main contributions of this approach resides in connecting the construct of trust to mental models. Using the outlined mental model approach, we propose novel HAT strategies, such as Adaptive Trust Calibration, and preview planned research activities derived from this approach. Additionally, we propose several practical applications that can currently be employed by AAM development communities.

Eric T Chancey↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Reinforcement Learning

To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. The goal of reinforcement learning is for an agent to learn a policy (task strategy) through interactions with an environment. When the agent performs an action, a change occurs in environment state and a numerical reward is received which informs the agent whether the action performed was good or not. Since reinforcement learning algorithms learn through trial-and-error, a simulation is a desirable first environment for development and learning. We developed two simulations, the first is a 2D excavation simulation developed to facilitate parameter selection, and a 3D simulation developed using a game physics engine, to simulate simplified soil interactions and increase the fidelity of the dynamic models of the robotic agents. The development of this 3D simulation has enabled the training of additional sensing capabilities and research both at the granular mechanics and operations levels. We experimented with various virtual sensor payloads to identify a combination that enabled efficient excavation operation and learning. Our reward function is based on how much material is excavated per step. A penalty is also received for leaving the dig site and to smooth the acceleration of the drum arms. We implemented pseudo time-of-flight sensors to report distance from each drum to ground and the height above ground which was found to be more efficient than existing solutions. Our findings suggest that reinforcement learning for autonomous operations has learned viable trenching strategies within 3000 training episodes in our simplified 2D environment and helped identify desirable sensing capabilities, arrangements, and considerations such as the positioning of time-of-flight sensors. Future work includes expanding our simulation to more complex environments and scenarios, and transfer learning from simulation to RASSOR 2.0 hardware for deployment in the Regolith Test Bin at NASA's Kennedy Space Center.

rassor↗
NASA NTRS2013

Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Muti-agent System↗
NASA NTRS1991

Who or what saved the day? A comparison of traditional and glass cockpits

This study examined incidents reported to NASAs Aviation Safety Reporting System from a different perspective: rather than focusing on the factors contributing to or causing incidents, this study concentrated on who and what (subsystems and information) enabled the recovery from an anomaly. Incident reports describing altitude deviations were classified as to cockpit type (glass or traditional), flight phase, agent restoring safety, and cockpit subsystems providing specific information that helped restore safety. The data revealed and quantified the agents, information, and factors that 'saved the day'. The flight crews used many sources of information to detect the altitude deviations: altimeter, outside scene, altitude alert, kinesthesia, attitude and communications monitoring. In the glass cockpits the crews also used the map display and autothrottles to detect deviations from assigned altitudes. There was an interaction between the person detecting the anomaly (controller/flight crew) and the type of cockpit. Glass cockpit flight crews detect proportionally more deviations than their counterparts in traditional cockpits, while controllers tend to detect more deviations involving traditional cockpits. There was no effect of cockpit position (captain/first officer). A model that details the flow of altitude information between air traffic control, flight crews, and cockpit subsystems, was developed and validated. This model identifies strengths and weaknesses in the flow of altitude information within the current ground/air system.

Degani, Asaf↗
NASA NTRS2017

Effects of Contamination and Cleaning on Parachute Structural Textile Elements

Throughout their lifecycle, parachute textiles come into contact with various other substances. This contact may occur during manufacturing and repair, storage and transportation, packing, or actual use. While this interaction does not always result in negative repercussions, it may cause a loss in material strength. This paper examines the strength degradation due to several contaminants as well as the effects of cleaning agents on common parachute materials. Materials tested were: Kevlar cord and webbing, Nylon broadcloth and webbing, and Vectran cord; all of these constitute the major structural elements for CPAS (Capsule Parachute Assembly System), the parachute system for the NASA Orion Crew Module. Contaminants tested were: sewing machine oil, dried stamping ink, dirt, basting glue, Sergene, and rust. Recommendations for cleaning (or not cleaning) these materials with respect to each of the contaminants are given in this paper, as well as recommendations for future tests.

Mollmann, Catherine↗
NASA NTRS1994

Integrating deliberative planning in a robot architecture

The role of planning and reactive control in an architecture for autonomous agents is discussed. The postulated architecture seperates the general robot intelligence problem into three interacting pieces: (1) robot reactive skills, i.e., grasping, object tracking, etc.; (2) a sequencing capability to differentially ativate the reactive skills; and (3) a delibrative planning capability to reason in depth about goals, preconditions, resources, and timing constraints. Within the sequencing module, caching techniques are used for handling routine activities. The planning system then builds on these cached solutions to routine tasks to build larger grain sized primitives. This eliminates large numbers of essentially linear planning problems. The architecture will be used in the future to incorporate in robots cognitive capabilites normally associated with intelligent behavior.

Elsaesser, Chris↗
NASA NTRS2005

Multi-Agent Modeling and Simulation Approach for Design and Analysis of MER Mission Operations

A space mission operations system is a complex network of human organizations, information and deep-space network systems and spacecraft hardware. As in other organizations, one of the problems in mission operations is managing the relationship of the mission information systems related to how people actually work (practices). Brahms, a multi-agent modeling and simulation tool, was used to model and simulate NASA's Mars Exploration Rover (MER) mission work practice. The objective was to investigate the value of work practice modeling for mission operations design. From spring 2002 until winter 2003, a Brahms modeler participated in mission systems design sessions and operations testing for the MER mission held at Jet Propulsion Laboratory (JPL). He observed how designers interacted with the Brahms tool. This paper discussed mission system designers' reactions to the simulation output during model validation and the presentation of generated work procedures. This project spurred JPL's interest in the Brahms model, but it was never included as part of the formal mission design process. We discuss why this occurred. Subsequently, we used the MER model to develop a future mission operations concept. Team members were reluctant to use the MER model, even though it appeared to be highly relevant to their effort. We describe some of the tool issues we encountered.

Seah, Chin↗
NASA NTRS2007

The Naturalistic Flight Deck System: An Integrated System Concept for Improved Single-Pilot Operations

This paper reviews current and emerging operational experiences, technologies, and human-machine interaction theories to develop an integrated flight system concept designed to increase the safety, reliability, and performance of single-pilot operations in an increasingly accommodating but stringent national airspace system. This concept, know as the Naturalistic Flight Deck (NFD), uses a form of human-centered automation known as complementary-automation (or complemation) to structure the relationship between the human operator and the aircraft as independent, collaborative agents having complimentary capabilities. The human provides commonsense knowledge, general intelligence, and creative thinking, while the machine contributes specialized intelligence and control, extreme vigilance, resistance to fatigue, and encyclopedic memory. To support the development of the NFD, an initial Concept of Operations has been created and selected normal and non-normal scenarios are presented in this document.

Schutte, Paul C.↗