Search NASA⌕ Search

SEARCH · Search NASA

Results for “Autonomous”

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 379 records · Page 21

An Architecture to Enable Autonomous Control of Spacecraft

Autonomy is required for manned spacecraft missions distant enough that light-time communication delays make ground-based mission control infeasible. Presently, ground controllers develop a complete schedule of power modes for all spacecraft components based on a large number of factors. The proposed architecture is an early attempt to formalize and automate this process using on-vehicle computation resources. In order to demonstrate this architecture, an autonomous electrical power system controller and vehicle Mission Manager are constructed. These two components are designed to work together in order to plan upcoming load use as well as respond to unanticipated deviations from the plan. The communication protocol was developed using "paper" simulations prior to formally encoding the messages and developing software to implement the required functionality. These software routines exchange data via TCP/IP sockets with the Mission Manager operating at NASA Ames Research Center and the autonomous power controller running at NASA Glenn Research Center. The interconnected systems are tested and shown to be effective at planning the operation of a simulated quasi-steady state spacecraft power system and responding to unexpected disturbances.

space power systems↗

Synchronization of Human Autonomic Nervous System Rhythms with Geomagnetic Activity in Human Subjects

A coupling between geomagnetic activity and the human nervous system's function was identified by virtue of continuous monitoring of heart rate variability (HRV) and the time-varying geomagnetic field over a 31-day period in a group of 10 individuals who went about their normal day-to-day lives. A time series correlation analysis identified a response of the group's autonomic nervous systems to various dynamic changes in the solar, cosmic ray, and ambient magnetic field. Correlation coefficients and p values were calculated between the HRV variables and environmental measures during three distinct time periods of environmental activity. There were significant correlations between the group's HRV and solar wind speed, Kp, Ap, solar radio flux, cosmic ray counts, Schumann resonance power, and the total variations in the magnetic field. In addition, the time series data were time synchronized and normalized, after which all circadian rhythms were removed. It was found that the participants' HRV rhythms synchronized across the 31-day period at a period of approximately 2.5 days, even though all participants were in separate locations. Overall, this suggests that daily autonomic nervous system activity not only responds to changes in solar and geomagnetic activity, but is synchronized with the time-varying magnetic fields associated with geomagnetic field-line resonances and Schumann resonances.

Magnetic Fields↗

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems.

context-sensitive↗

Autonomous Coordinated Airspace Services for Terminal and Enroute Operations with Wind Errors

As novel uses of the airspace continue to multiply, there is increasing demand for access to high-density terminal areas around major airports. Since the predicted demand for urban-air-mobility and urban-package-delivery is very high, and the interactions between these different types of aircraft and missions will be extremely complex, increasingly autonomous systems will be required to manage safety and efficiency. This paper presents the current status of an autonomous safety system designed to ensure safe and efficient trajectories for aircraft in terminal airspace, the Terminal Advanced Airspace Concept. Previous papers have demonstrated the efficacy of this algorithm for handling commercial arrivals into a complex metroplex when there is no uncertainty present. This study extends that work to demonstrate the performance of the algorithm under high levels of uncertainty.

terminal operations↗

Autonomous Coordinated Airspace Services for Terminal and Enroute Operations with Wind Errors

As novel uses of the airspace continue to multiply, there is increasing demand for access to high-density terminal areas around major airports. Since the predicted demand for urban-air-mobility and urban-package-delivery is very high, and the interactions between these different types of aircraft and missions will be extremely complex, increasingly autonomous systems will be required to manage safety and efficiency. This paper presents the current status of an autonomous safety system designed to ensure safe and efficient trajectories for aircraft in terminal airspace, the Terminal Advanced Airspace Concept. Previous papers have demonstrated the efficacy of this algorithm for handling commercial arrivals into a complex metroplex when there is no uncertainty present. This study extends that work to demonstrate the performance of the algorithm under high levels of uncertainty.

terminal operations↗

Development and Testing of a Vehicle Management System for Autonomous Spacecraft Habitat Operations

As the increased distance between Earth-based mission control and the spacecraft results in increasing communication delays, 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. In addition, both near-term and future missions will feature significant periods when crew is not present, meaning the vehicles will need to operate themselves autonomously. NASA's Advanced Exploration Systems Program pioneers new approaches for rapidly developing prototype systems, demonstrating key capabilities, and validating operational concepts for future human missions beyond low-Earth orbit. Under this program, NASA has developed and demonstrated multiple technologies to enable the autonomous operation of a dormant space habitat. These technologies included a fault-tolerant avionics architecture, novel spacecraft power system and power system controller, and autonomy software to control the habitat. The demonstration involved simulation of the habitat and multiple spacecraft sub-systems (power storage and distribution, avionics, and air-side life-support) during a multi-day test at NASA's Johnson Space Center. The foundation of the demonstration was ‘quiescent operations' of a habitat during a 55 minute eclipse period. For this demonstration, the spacecraft power distribution system and air-side life support system were simulated at a high level of fidelity; additional systems were managed, but with lower fidelity operational constraints and system behavior. Operational constraints for real and simulated loads were developed by analyzing on-orbit hardware and evaluating future Exploration capable technology. A total of 13 real and simulated loads were used during the test. Eight scenarios including both nominal and off-nominal conditions were performed. Over the course of the test, every application performed its desired functions successfully during the simulated tests. The results will inform both future tests, as well as provide insight to NASA's domestic and international partners, as they construct the next generation of space habitats to be used on beyond-Earth missions.

Autonomous Systems and Operations↗

Demonstrating Autonomous Mission Operations Onboard the International Space Station

The NASA Autonomous Mission Operations (AMO) project conducted an experiment to turn over operation and management of selected International Space Station (ISS) sys- tems to the on-board crew. ISS crews managed two different spacecraft systems: the Total Organic Carbon Analyzer (TOCA), a water quality analyzer, and Station Support Com- puters (SSC) laptops, which are non-critical crew computer systems. These systems were selected because they are representative of systems a future crew may need to operate au- tonomously during a deep space mission. The crew autonomously operated these systems, taking on mission operations functions traditionally performed by support teams on the ground, using new software tools that provide decision support algorithms for planning, monitoring and fault management, hardware schematics, system briefs, and data displays that are normally unavailable to the crew. The experiment lasted seven months, during which ISS crews managed TOCA and SSCs on 22 occasions. The AMO software processed data from TOCA and SSCs continuously during this seven month period. The combined performance of the software and crew achieved a 88 success rate on managing TOCA activity, the system for which ground-truth was available.

Autonomous Mission Operations↗

A New Market for Terrestrial Single-Event Effects: Autonomous Vehicles

ISO-26262, the road vehicle functional safety standard, underwent a major overhaul that was released in December 2018. Radiation effects, and single-event effect (SEE) hazards in particular, play an important role in autonomous vehicle safety. This connection will only increase as the level of driving automation goes from "hands off," to "eyes off," to "mind off." This translates to increased coupling with space climate and weather in addition to other traditional terrestrial radiation sources like thorium and uranium contamination in process and packaging materials. We will focus on autonomous vehicle radiation effects and present both benefits and challenges to the space weather and radiation engineering communities.

Autonomous Vehicles↗

Capability Considerations for Enhancing Safety on Long Duration Crewed Missions: Insights from a Technical Interchange Meeting on Autonomous Crew Operations

As future flight crews on long duration deep space missions are expected to operate more autonomously, considerations must be given to onboard capabilities and human-computer teaming that will fortify the safety net traditionally provided by the Mission Control Center. In August 2018, the Human Factors and Behavioral Performance Element of NASA's Human Research Program convened a Technical Interchange Meeting (TIM) on Autonomous Crew Operations at NASA Ames Research Center to address how intelligent technologies can be utilized to augment crew capabilities to support real-time anomaly response. In this paper, we highlight three topic areas discussed at the TIM that have direct implications for future crew anomaly response capabilities: smart structures, cognitive assistants, and manpower.

autonomous crew operations↗

Supporting Crew Autonomy in Deep Space Exploration: Preliminary Onboard Capability Requirements and Proposed Research Questions. Technical Report of the Autonomous Crew Operations Technical Interchange Meeting

Communication delays are a critical challenge posed by long duration deep space exploration. Space missions historically have relied on an ever-present Mission Control Center (MCC) to direct operations in near real-time. As unanticipated anomalies that defeat fault detection and resolution systems do arise, the lack of real-time communication will significantly weaken what the MCC support represents: a reliable safety net for the flight crew through its deep and diverse areas of expertise and investigative resources. As a consequence, future space vehicles and habitats need to be equipped with capabilities to support the flight crew to operate with little or no ground support. Considerations must be given to vehicle and mission designs that will fortify the traditionally ground-centered safety net and forge new support systems, when communication delays exist. In August 2018, NASA’s Human Research Program, through its Human Factors and Behavioral Performance Element, convened a Technical Interchange Meeting (TIM) on Autonomous Crew Operations at NASA Ames Research Center. The goal of the meeting was to gather input from NASA centers, industry, academia, and branches of the Department of Defense (DoD) to address how intelligent technologies can be applied to augment onboard capabilities to support crew anomaly response. The TIM featured 24 presentations by 29 speakers and hosted a total of 59 attendees, including 43 from 5 NASA centers (Ames, Johnson, Langley, Marshall, and Jet Propulsion Lab) and 4 from the DoD (3 from Army Research Lab and 1 from Naval Postgraduate School), with remaining attendees from academia (e.g., UC Davis, CMU) and industry (e.g., IBM, Siemens). Discussions were centered around three themes: standards and guidelines, lessons learned in analog environments, and technologies. To help provide a framework for discussion, a concept matrix describing anomaly response processes was created prior to the TIM (Figure 1, page 6). The matrix captures the steps involved (monitoring and detection, diagnosis, solution development and evaluation, solution implementation and verification, resolution documentation) as well as the resources and capabilities required to support these steps (data, knowledge, analysis, synthesis, resource management). A wallpaper size printout of the matrix was utilized at the TIM to solicit attendee inputs along the three themes; the activity garnered 108 submissions of ideas. Overall, what emerged from TIM discussions was a picture of mismatch between crew anomaly response needs and support that can be provided by existing intelligent technologies. The needs are broad, spanning multiple steps and processes/resources, with many of which lacking support from existing technologies, such as knowledge management throughout the steps of problem solving (especially in resolution documentation) and manpower management. The solutions provided by existing intelligent technologies are specific to the steps/processes that they are designed to support and constrained to solving only problems similar to those that have occurred before. What is lacking from technologies is typically made up by humans, specifically their complex critical thinking, creative problem solving, and domain expertise. In the end, the TIM highlighted the pressing need to support responses to onboard anomalies during autonomous crew operations, particularly those that have eluded the system tests, inspection, and other assurance processes. Such anomalies can potentially threaten crew and vehicle safety, as well as significantly impact overall operations with additional workload. These fairly rare events are difficult to anticipate and prepare for, given the state-of-the-art in intelligent technologies. This is true even for anomalies that stem from “unknown knowns”—cases in which there is sufficient external information to characterize the problem but the overall pattern fails to be recognized by the problem solver, or in which the internal knowledge needed to solve a problem is held tacitly and potentially accessible by the problem solver but not articulated. It follows that the ability to tackle anomalies lies not only with the availability of relevant information and knowledge but also their accessibility in times of need. To that end, we propose research questions along the following three broad themes: • How intelligent technologies can help make relevant knowledge and information available? • How intelligent technologies can help make relevant knowledge and information accessible? • How intelligent technologies can help support the crew operating as a team in anomaly response processes?

autonomous crew operations↗

NASA Platform for Autonomous Systems (NPAS)

Autonomous operations are critical for the success, safety and crew survival of NASA deep space missions beyond low Earth orbit, including Gateway. For the past 10 years, Stennis Space Center (SSC) has been developing, and has demonstrated an innovative software platform, along with expertise and processes for implementation of autonomous operations.

Integrated Power Avionics and Software↗

An Autonomous sUAS Operating in UTM TCL4+ and STEReO Fire Scenario

This study presents a sUAS payload point design that enables autonomous BVLOS flightin UTM TCL4+ urban environments and STEReO fire responses. The payload components include an onboard computer, 360 deg LIDAR, range finder altimeter, downward-facing monocular camera, forward-facing thermal and visible light dual camera, vehicle-to-vehicle radio modem, and Li-ion smart battery. The components are mounted on an enclosed structural frame that was designed in-house. Placing the autonomy components onboard leverages the advantages of sUAS over manned aircraft such as low-cost, quick response time, and increased scalability. Autonomous capabilities include object and fire detection, V2V communication, embedded processing, and SLAM. Data processing is conducted on-board the aircraft to eliminate the dependency on a ground station downlink. The payload is evaluated in both software simulation as well as flight tests.

Autonomous UAS↗

From Requirements to Autonomous Flight: An Overview of the Monitoring ICAROUS Project

The Independent Configurable Architecture for Reliable Operations of Unmanned Systems(ICAROUS) is a software architecture incorporating a set of algorithms to enable autonomous operations of unmanned aircraft applications. This paper provides an overview of Monitoring ICAROUS, a project whose objective is to provide a formal approach to generating runtime monitors for autonomous systems from requirements written in a structured natural language. This approach integrates FRET, a formal requirement elicitation and authoring tool, and Copilot, a runtime verification framework. FRET is used to specify formal requirements in structured natural language. These requirements are translated into temporal logic formulae. Copilot is then used to generate executable runtime monitors from these temporal logic specifications. The generated monitors are directly integrated into ICAROUS to perform runtime verification during flight.

Formal Methods↗

Monitoring ICAROUS: From Requirements to Autonomous Flight

The Independent Configurable Architecture for Reliable Operations of Unmanned Systems (ICAROUS) is a software architecture incorporating a set of algorithms to enable autonomous operations of unmanned aircraft applications. This paper provides an overview of Monitoring ICAROUS, a project whose objective is to provide a formal approach to generating runtime monitors for autonomous systems from requirements written in a structured natural language. This approach integrates FRET, a formal requirement elicitation and authoring tool, and Copilot, a runtime verification framework. FRET is used to specify formal requirements in structured natural language. These requirements are translated into temporal logic formulae. Copilot is then used to generate executable runtime monitors from these temporal logic specifications. The generated monitors are directly integrated into ICAROUS to perform runtime verification during flight.

Formal Methods↗

Towards An Autonomous sUAS Operating in UTM TCL4+ and STEReO Fire Scenario

This study presents two sUAS payload point designs for enabling autonomous BVLOS flight in UTM TCL4+ urban environments and STEReO fire responses. The payload components for the first payload include an onboard computer and a 360 LIDAR. The second payload, which is a continuation of the first, adds a range finder altimeter, downward-facing monocular camera, forward-facing thermal and visible light dual camera, vehicle-to-vehicle radio modem, and Li-ion smart battery. The components are mounted on enclosed structural frames that were designed in-house. Placing the autonomy components onboard leverages the advantages of sUAS over manned aircraft such as low-cost, quick response time, and increased scalability. Autonomous capabilities include embedded processing, SLAM, object and fire detection, and V2V communication. Data processing is conducted onboard the aircraft to eliminate the dependency on a groundstation downlink. The first iteration of the payload is tested in both simulation and flight tests while the continuing iteration is in development.

Autonomous UAS↗

The Techsat-21 autonomous sciencecraft experiment

The Autonomous Sciencecraft Experiment flight demonstration (ASE) will fly onboard the US Air Forces's TechSat-21 constellation, an unclassified mission scheduled for launch in 2004. ASE will use onboard science analysis, replanning, robust execution, and formation flying to radically increase science return by enabling intelligent downlink selection and autonomous retargeting.

autonomous↗

An Uncertainty Quantification Framework for Autonomous Flight System Tracking and Health Monitoring

This work proposes a perspective towards establishing a framework for uncertainty quantification of autonomous system tracking and health monitoring. The approach leverages the use of a predictive process structure, which maps uncertainty sources and their interaction according to the quantity of interest and the goal of the predictive estimation. It is systematic and uses basic elements that are system agnostic, and therefore needs to be tailored according to the specificity of the application. This work is motivated by the interest in low-altitude unmanned aerial vehicle operations, where awareness of vehicle and airspace state becomes more relevant as the density of autonomous operations grows rapidly. Predicted scenarios in the area of small vehicle operations and urban air mobility have no precedent, and holistic frameworks to perform prognostics and health management (PHM) at the system- and airspace-level are missing formal approaches to account for uncertainty. At the end of the paper, two case studies demonstrate implementation framework of trajectory tracking and health diagnosis for a small unmanned aerial vehicle. This work has been accepted for publication at the International Journal of Prognostics and Health Management Jan 2021. Minor edits have been incorporated to this original submission to incorporate complete overview and software integration.

Uncertainty Quantification↗