Search NASA⌕ Search

SEARCH · Search NASA

Results for “autonomous teams”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight frameworks is paramount for establishing an effective architecture for autonomous systems. Hardware test flights are time-consuming and cost prohibitive during early system design and development. Simulation environments can be useful tools to accelerate algorithm development and testing. However, transitions from simulation to flight (sim-to-flight) can be challenging, unless systems are designed with this transition in mind and with the necessary capabilities built into the architecture and framework. One of the objectives of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. ATTRACTOR’s objective was to construct computational concepts of trustworthiness and justifiable trust in multi-agent autonomous teams, to inform future certification of safety-critical and time-critical autonomous systems in aviation. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation (ModSim) environment for test and evaluation of autonomous systems. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single-and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. The Autonomous Entity Operational Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications, enabling sim-to-flight with minimal configuration changes. Using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley↗
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 NTRSDate not supplied

Generic Urban Air Mobility Simulation

This research presents a simulation framework for autonomous research for a UAM vehicle using the NASA Revolutionary Vertical Lift Technology Lift+Cruise concept vehicle. Our research results were produced using the open-source, six degree of freedom, rigid-body, nonlinear generic urban air mobility (GUAM) simulation. The intent of this paper is to demonstrate the GUAM simulation and a series of Challenge Problems that our researchers have posed to the broader autonomous vehicle research community. Our team has developed the GUAM simulation for the express purpose of providing a high-fidelity transition vehicle dynamics model to foster collaboration and algorithm performance comparison across research teams. In this paper, we demonstrate some of the autonomous flight research challenges and some of our current approaches to tackling basic autonomous flight tasks (e.g., trajectory following, stationary and moving obstacle avoidance). Additionally, we propose some flight metrics to assess autonomous algorithm performance while accomplishing these basic autonomous tasks.

autonomous flight↗
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 NTRS2017

Preliminary GN&C Design for the On-Orbit Autonomous Assembly of Nanosatellite Demonstration Mission

Small spacecraft autonomous rendezvous and docking (ARD) is an essential technology for future space structure assembly missions. The On-orbit Autonomous Assembly of Nanosatellites (OAAN) team at NASA Langley Research Center (LaRC) intends to demonstrate the technology to autonomously dock two nanosatellites to form an integrated system. The team has developed a novel magnetic capture and latching mechanism that allows for docking of two CubeSats without precise sensors and actuators. The proposed magnetic docking hardware not only provides the means to latch the CubeSats, but it also significantly increases the likelihood of successful docking in the presence of relative attitude and position errors. The simplicity of the design allows it to be implemented on many CubeSat rendezvous missions. Prior to demonstrating the docking subsystem capabilities on orbit, the GN&C subsystem should have a robust design such that it is capable of bringing the CubeSats from an arbitrary initial separation distance of as many as a few thousand kilometers down to a few meters. The main OAAN Mission can be separated into the following phases: 1) Launch, checkout, and drift, 2) Far-Field Rendezvous or Drift Recovery, 3) Proximity Operations, 4) Docking. This paper discusses the preliminary GN&C design and simulation results for each phase of the mission.

Pei, Jing↗
NASA NTRS2015

Collaborating with Autonomous Agents

With the anticipated increase of small unmanned aircraft systems (sUAS) entering into the National Airspace System, it is highly likely that vehicle operators will be teaming with fleets of small autonomous vehicles. The small vehicles may consist of sUAS, which are 55 pounds or less that typically will y at altitudes 400 feet and below, and small ground vehicles typically operating in buildings or defined small campuses. Typically, the vehicle operators are not concerned with manual control of the vehicle; instead they are concerned with the overall mission. In order for this vision of high-level mission operators working with fleets of vehicles to come to fruition, many human factors related challenges must be investigated and solved. First, the interface between the human operator and the autonomous agent must be at a level that the operator needs and the agents can understand. This paper details the natural language human factors e orts that NASA Langley's Autonomy Incubator is focusing on. In particular these e orts focus on allowing the operator to interact with the system using speech and gestures rather than a mouse and keyboard. With this ability of the system to understand both speech and gestures, operators not familiar with the vehicle dynamics will be able to easily plan, initiate, and change missions using a language familiar to them rather than having to learn and converse in the vehicle's language. This will foster better teaming between the operator and the autonomous agent which will help lower workload, increase situation awareness, and improve performance of the system as a whole.

Trujillo, Anna C.↗
NASA NTRSDate not supplied

Moon to Mars Planetary Autonomous Construction Technology (MMPACT) Lunar Surface Construction Activity at NASA Marshall Space Flight Center

Introduction: The goal of the Moon to Mars Planetary Autonomous Construction Technology (MMPACT) Project at NASA Marshall Space Flight Center (MSFC) is to develop, deliver, and demonstrate on-demand capabilities to protect astronauts and create infrastructure elements on the lunar surface via construction of landing pads, habitats, shelters, roadways, berms, and blast shields using lunar regolith-based materials. MSFC has strong collaborations with industry, academia, and other NASA Centers to accomplish this goal. The MMPACT project consists of three elements. The first focuses on the development of an autonomous construction system. The second focuses on construction feedstock materials development. The third element focuses on the development of a microwave sintering construction capability. The team plans to demonstrate construction on a small Commercial Lunar Payload Services (CLPS) lander in the 2025 timeframe, with a future goal of constructing a subscale landing pad in 2028-2029.The MMPACT project is funded through the Lunar Surface Innovation Initiative, which is part of the Space Technology Mission Directorate. Technology Development: The MMPACT team will evaluate multiple autonomous construction and microwave construction technologies, materials, and construction element forms. Selected technologies will be matured; processes and operations will be defined for the two flight missions. Evaluations of materials, as well as the technology itself, will be demonstrated in simulated lunar environments as part of the technology maturation process. The team is keenly aware of the properties of the lunar environment. Its temperature swings, negligible exosphere, and unprepared site foundations factor into the materials for both construction and hardware, the concept of operations, and the technology’s interdependencies. Materials: The team is looking at materials that can be produced from in-situ resources in an effort to make lunar construction cost-effective. The particular focus of the materials team is cementitious materials, metals, and sintered and melted regolith. These materials will be studied for tensile, compressive, and flexural strength. They will also be tested for their ability to handle thermal swings and vacuum. They will be fully characterized using various microscopy techniques to examine micro-structures, chemistry, and crystal formation. Interdependencies: There are many interdependencies that MMPACT has already identified. These include: •Excavation interface •Regolith feedstock beneficiation •Regolith feedstock storage and provision •Requirements for structures •Site-to-site mobility systems •Availability of lunar simulant •Lander off-loading capabilities •Navigation systems •Power •Regolith composition and mineralogy •Lander specifications •Communication protocols Technology developments in these additional areas would be beneficial to MMPACT.

Moon to Mars Planetary Autonomous Construction Tec↗
NASA NTRS2003

Information for Successful Interaction with Autonomous Systems

Interaction in heterogeneous mission operations teams is not well matched to classical models of coordination with autonomous systems. We describe methods of loose coordination and information management in mission operations. We describe an information agent and information management tool suite for managing information from many sources, including autonomous agents. We present an integrated model of levels of complexity of agent and human behavior, which shows types of information processing and points of potential error in agent activities. We discuss the types of information needed for diagnosing problems and planning interactions with an autonomous system. We discuss types of coordination for which designs are needed for autonomous system functions.

Malin, Jane T.↗
NASA NTRS2019

Lessons Learned from International Space Station Crew Autonomous Scheduling Test

In 2017, our team investigated and evaluated the novel concept of operations of astronaut self-scheduling (rescheduling their own timeline without creating violations) onboard International Space Station (ISS). Five test sessions were completed for this technology demonstration called Crew Autonomous Scheduling Test (CAST). For the first time in a spaceflight operational environment, an ISS crewmember planned, rescheduled, and executed their activities in real-time on a mobile device while abiding by flight and scheduling constraints. This paper discusses the lessons learned from deployment to execution.

planning and scheduling↗
NASA NTRS1999

Autonomous Command Operations of the WIRE Spacecraft

This paper presents operational innovations which will be introduced on NASA's Wide Field Infrared Explorer (WIRE) mission. These innovations include an end-to-end design architecture for an autonomous commanding capability for the uplink of command loads during unattended station contacts. The WIRE mission is the fifth and final mission of NASA's Goddard Space Flight Center Small Explorer (SMEX) series to be launched in March of 1999. Its primary mission is the targeting of deep space fields using an ultra-cooled infrared telescope. Due to its mission design WIRE command loads are large (approximately 40 Kbytes per 24 hours) and must be performed daily. To reduce the cost of mission operations support that would be required in order to uplink command loads, the WIRE Flight Operations Team has implemented all autonomous command loading capability. This capability allows completely unattended operations over a typical two-day weekend period. The key factors driving design and implementation of this capability were: 1) integration with already existing ground system autonomous capabilities and systems, 2) the desire to evolve autonomous operations capabilities based upon previous SMEX operations experience - specifically the TRACE mission, 3) integration with ground station operations - both autonomous and man-tended, 4) low cost and quick implementation, and 5) end-to-end system robustness. A trade-off study was performed to examine these factors in light of the low-cost, higher-risk SMEX mission philosophy. The study concluded that a STOL (Spacecraft Test and Operations Language) based script, highly integrated with other scripts used to perform autonomous operations, was best suited given the budget and goals of the mission. Each of these factors is discussed in addition to use of the TRACE mission as a testbed for autonomous commanding prior to implementation on WIRE. The capabilities implemented on the WIRE mission are an example of a low-cost, robust, and efficient method for autonomous command loading when implemented with other autonomous features of the ground system. They call be used as a design and implementation template by other missions interested in evolving toward autonomous and lower cost operations. Additionally, the WIRE spacecraft will be used as an operational testbed upon completion of its nominal mission later in 1999. One idea being studied is advanced on-board modeling. Advanced on-board modeling techniques will be used to more efficiently display the spacecraft state. This health and safety information could be used by engineers on the ground or could be used by tile spacecraft for its own assessments. Additionally, this same state information could also be input into the event-driven scheduling system, as the scheduling system will need to assess the spacecraft state before undertaking a new activity. Advanced modeling techniques are being evaluated for a number of NASA missions including The Next Generation Space Telescope (NGST), which is scheduled to launch in 2007.

Walyus, Keith↗
NASA NTRS1999

Autonomous Command Operation of the WIRE Spacecraft

This paper presents the end-to-end design architecture for an autonomous commanding capability to be used on the Wide Field Infrared Explorer (WIRE) mission for the uplink of command loads during unattended station contacts. The WIRE mission is the fifth and final mission of NASA's Goddard Space Flight Center Small Explorer (SMEX) series to be launched in March of 1999. Its primary mission is the targeting of deep space fields using an ultra-cooled infrared telescope. Due to its mission design WIRE command loads are large (approximately 40 Kbytes per 24 hours) and must be performed daily. To reduce the cost of mission operations support that would be required in order to uplink command loads, the WIRE Flight Operations Team has implemented an autonomous command loading capability. This capability allows completely unattended operations over a typical two-day weekend period.

Prior, Mike↗
NASA NTRS1999

Autonomous Commanding of the WIRE Spacecraft

This paper presents the end-to-end design architecture for an autonomous commanding capability to be used on the Wide Field Infrared Explorer (WIRE) mission for the uplink of command loads during unattended station contacts. The WIRE mission is the fifth and final mission of NASA's Goddard Space Flight Center Small Explorer (SMEX) series to be launched in March of 1999. Its primary mission is the targeting of deep space fields using an ultra-cooled infrared telescope. Due to its mission design WIRE command loads are large (approximately 40 Kbytes per 24 hours) and must be performed daily. To reduce the cost of mission operations support that would be required in order to uplink command loads, the WIRE Flight Operations Team has implemented an autonomous command loading capability. This capability allows completely unattended operations over a typical two- day weekend period. The key factors driving design and implementation of this capability were: 1) Integration with already existing ground system autonomous capabilities and systems, 2) The desire to evolve autonomous operations capabilities based upon previous SMEX operations experience 3) Integration with ground station operations - both autonomous and man-tended, 4) Low cost and quick implementation, and 5) End-to-end system robustness. A trade-off study was performed to examine these factors in light of the low-cost, higher-risk SMEX mission philosophy. The study concluded that a STOL (Spacecraft Test and Operations Language) based script, highly integrated with other scripts used to perform autonomous operations, was best suited given the budget and goals of the mission. Each of these factors is discussed to provide an overview of the autonomous operations capabilities implemented for the mission. The capabilities implemented on the WIRE mission are an example of a low-cost, robust, and efficient method for autonomous command loading when implemented with other autonomous features of the ground system. They can be used as a design and implementation template by other small satellite missions interested in evolving toward autonomous and lower cost operations.

Prior, Mike↗
NASA NTRS2023

Tall Lunar Tower: An Autonomously Assembled Tower for Early Lunar Infrastructure

The Tall Lunar Tower (TLT) In-Space Assembly (ISA) team aims to design, model, fabricate, autonomously assemble, and characterize a TLT engineering development unit (EDU). The autonomous assembly of a tower also demonstrates a cross-cutting technology that can be applied to other lunar structures, such as blast shields, radiation shelters, and safe havens.

In-Space Assembly↗
NASA NTRS2011

The Next Generation of Mars-GRAM and Its Role in the Autonomous Aerobraking Development Plan

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM 2010 is currently being used to develop the onboard atmospheric density estimator that is part of the Autonomous Aerobraking Development Plan. In previous versions, Mars-GRAM was less than realistic when used for sensitivity studies for Thermal Emission Spectrometer (TES) MapYear=0 and large optical depth values, such as tau=3. A comparison analysis has been completed between Mars-GRAM, TES and data from the Planetary Data System (PDS) resulting in updated coefficients for the functions relating density, latitude, and longitude of the sun. The adjustment factors are expressed as a function of height (z), Latitude (Lat) and areocentric solar longitude (Ls). The latest release of Mars-GRAM 2010 includes these adjustment factors that alter the in-put data from MGCM and MTGCM for the Mapping Year 0 (user-controlled dust) case. The greatest adjustment occurs at large optical depths such as tau greater than 1. The addition of the adjustment factors has led to better correspondence to TES Limb data from 0-60 km as well as better agreement with MGS, ODY and MRO data at approximately 90-135 km. Improved simulations utilizing Mars-GRAM 2010 are vital to developing the onboard atmospheric density estimator for the Autonomous Aerobraking Development Plan. Mars-GRAM 2010 was not the only planetary GRAM utilized during phase 1 of this plan; Titan-GRAM and Venus-GRAM were used to generate density data sets for Aerobraking Design Reference Missions. These data sets included altitude profiles (both vertical and along a trajectory), GRAM perturbations (tides, gravity waves, etc.) and provided density and scale height values for analysis by other Autonomous Aero-braking team members.

Justh, Hilary L.↗
NASA NTRS2012

MSL-RAD Cruise Operations Concept

The Mars Science Laboratory (MSL) payload includes the Radiation Assessment Detector (RAD) instrument, intended to fully characterize the radiation environment for the MSL mission. The RAD instrument operations concept is intended to reduce impact to spacecraft resources and effort for the MSL operations team. By design, RAD autonomously performs regular science observations without the need for frequent commanding from the Rover Compute Element (RCE). RAD operates with pre-defined "sleep" and "observe" periods, with an adjustable duty cycle for meeting power and data volume constraints during the mission. At the start of a new science observation, RAD performs a pre-observation activity to assess count rates for selected RAD detector elements. Based on this assessment, RAD can enter "solar event" mode, in which instrument parameters (including observation duration) are selected to more effectively characterize the environment. At the end of each observation period, RAD stores a time-tagged, fixed length science data packet in its non-volatile mass memory storage. The operating cadence is defined by adjustable parameters, also stored in non-volatile memory within the instrument. Periodically, the RCE executes an on-board sequence to transfer RAD science data packets from the instrument mass storage to the MSL downlink buffer. Infrequently, the RAD instrument operating configuration is modified by updating internal parameter tables and configuration entries.

Mars Science Laboratory (MSL)↗
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

Exploring Multimodal Interactions in Human-Autonomy Teaming Using a Natural User Interface

The creation of a multimodal, natural user interface to facilitate multi-agent interaction is essential to establishing trust among human and machine teammates in multi-agent systems. Trust is being researched, along with trustworthiness, as a path to certification of autonomous systems by the Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project at NASA. The Autonomous Mission Experimental Logistics Interactive Assistant (AMELIA) is a natural user interface that enables multimodal interaction and is designed for rapid mission planning. AMELIA is an intelligent system that considers the user’s preferred communication strategies, as well as the time-critical aspect of the multi-agent system decision-making process. Twenty-four participants planned a multi-agent search and rescue mission, with the aid of an intelligent assistant. The results show that while the combined use of touch and speech was faster than speech alone, the single modality, touch, was still the most efficient. Future research should investigate additional input technologies.

Lisa R Le Vie↗