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

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At least 271 records · Page 15
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NASA NTRS2014

Ground Operations Autonomous Control and Integrated Health Management

An intelligent autonomous control capability has been developed and is currently being validated in ground cryogenic fluid management operations. The capability embodies a physical architecture consistent with typical launch infrastructure and control systems, augmented by a higher level autonomous control (AC) system enabled to make knowledge-based decisions. The AC system is supported by an integrated system health management (ISHM) capability that detects anomalies, diagnoses causes, determines effects, and could predict future anomalies. AC is implemented using the concept of programmed sequences that could be considered to be building blocks of more generic mission plans. A sequence is a series of steps, and each executes actions once conditions for the step are met (e.g. desired temperatures or fluid state are achieved). For autonomous capability, conditions must consider also health management outcomes, as they will determine whether or not an action is executed, or how an action may be executed, or if an alternative action is executed instead. Aside from health, higher level objectives can also drive how a mission is carried out. The capability was developed using the G2 software environment (www.gensym.com) augmented by a NASA Toolkit that significantly shortens time to deployment. G2 is a commercial product to develop intelligent applications. It is fully object oriented. The core of the capability is a Domain Model of the system where all elements of the system are represented as objects (sensors, instruments, components, pipes, etc.). Reasoning and decision making can be done with all elements in the domain model. The toolkit also enables implementation of failure modes and effects analysis (FMEA), which are represented as root cause trees. FMEA's are programmed graphically, they are reusable, as they address generic FMEA referring to classes of subsystems or objects and their functional relationships. User interfaces for integrated awareness by operators have been created.

Figueroa, Fernando↗
NASA NTRS2014

Autonomous Deep-Space Optical Navigation Project

This project will advance the Autonomous Deep-space navigation capability applied to Autonomous Rendezvous and Docking (AR&D) Guidance, Navigation and Control (GNC) system by testing it on hardware, particularly in a flight processor, with a goal of limited testing in the Integrated Power, Avionics and Software (IPAS) with the ARCM (Asteroid Retrieval Crewed Mission) DRO (Distant Retrograde Orbit) Autonomous Rendezvous and Docking (AR&D) scenario. The technology, which will be harnessed, is called 'optical flow', also known as 'visual odometry'. It is being matured in the automotive and SLAM (Simultaneous Localization and Mapping) applications but has yet to be applied to spacecraft navigation. In light of the tremendous potential of this technique, we believe that NASA needs to design a optical navigation architecture that will use this technique. It is flexible enough to be applicable to navigating around planetary bodies, such as asteroids.

D'Souza, Christopher↗
NASA NTRS2014

Vision Based Autonomous Robotic Control for Advanced Inspection and Repair

The advanced inspection system is an autonomous control and analysis system that improves the inspection and remediation operations for ground and surface systems. It uses optical imaging technology with intelligent computer vision algorithms to analyze physical features of the real-world environment to make decisions and learn from experience. The advanced inspection system plans to control a robotic manipulator arm, an unmanned ground vehicle and cameras remotely, automatically and autonomously. There are many computer vision, image processing and machine learning techniques available as open source for using vision as a sensory feedback in decision-making and autonomous robotic movement. My responsibilities for the advanced inspection system are to create a software architecture that integrates and provides a framework for all the different subsystem components; identify open-source algorithms and techniques; and integrate robot hardware.

sensory feedback↗
NASA NTRS2015

Autonomic and Apoptotic, Aeronautical and Aerospace Systems, and Controlling Scientific Data Generated Therefrom

A self-managing system that uses autonomy and autonomicity is provided with the self-* property of autopoiesis (self-creation). In the event of an agent in the system self-destructing, autopoiesis auto-generates a replacement. A self-esteem reward scheme is also provided and can be used for autonomic agents, based on their performance and trust. Art agent with greater self-esteem may clone at a greater rate compared to the rate of an agent with lower self-esteem. A self-managing system is provided for a high volume of distributed autonomic/self-managing mobile agents, and autonomic adhesion is used to attract similar agents together or to repel dissimilar agents from an event horizon. An apoptotic system is also provided that accords an "expiry date" to data and digital objects, for example, that are available on the internet, which finds usefulness not only in general but also for controlling the loaning and use of space scientific data.

Sterritt, Roy↗
NASA NTRS2003

Design, Development and Testing of the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) Guidance, Navigation and Control System

Engineers at NASA Johnson Space Center have designed, developed, and tested a nanosatellite-class free-flyer intended for future external inspection and remote viewing of human spaceflight activities. The technology demonstration system, known as the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam), has been integrated into the approximate form and function of a flight system. The primary focus has been to develop a system capable of providing external views of the International Space Station. The Mini AERCam system is spherical-shaped and less than eight inches in diameter. It has a full suite of guidance, navigation, and control hardware and software, and is equipped with two digital video cameras and a high resolution still image camera. The vehicle is designed for either remotely piloted operations or supervised autonomous operations. Tests have been performed in both a six degree-of-freedom closed-loop orbital simulation and on an air-bearing table. The Mini AERCam system can also be used as a test platform for evaluating algorithms and relative navigation for autonomous proximity operations and docking around the Space Shuttle Orbiter or the ISS.

Wagenknecht, J.↗
NASA NTRS2015

On-Orbit Autonomous Assembly from Nanosatellites

The On-Orbit Autonomous Assembly from Nanosatellites (OAAN) project will demonstrate autonomous control algorithms for rendezvous and docking maneuvers; low-power reconfigurable magnetic docking technology; and compact, lightweight and inexpensive precision relative navigation using carrier-phase differential (CD) GPS with a three-degree of freedom ground demonstration. CDGPS is a specific relative position determination method that measures the phase of the GPS carrier wave to yield relative position data accurate to.4 inch (1 centimeter). CDGPS is a technology commonly found in the surveying industry. The development and demonstration of these technologies will fill a current gap in the availability of proven autonomous rendezvous and docking systems for small satellites.

Precision relative navigation↗
NASA NTRS2016

The NASA/AFRL Meter Class Autonomous Telescope

For the past decade, the NASA Orbital Debris Program Office (ODPO) has relied on using various ground-based telescopes in Chile to acquire statistical survey data as well as photometric and spectroscopic data of orbital debris in geosynchronous Earth orbit (GEO). The statistical survey data have been used to supply the Orbital Debris Engineering Model (ORDEM) v.3.0 with debris detections in GEO to better model the environment at altitudes where radar detections are limited. The data produced for the statistical survey ranged from 30 to 40 nights per year, which only accounted for ~10% of the possible observing time. Data collection was restricted by ODPO resources and weather conditions. In order to improve the statistical sampling in GEO, as well as observe and sample other orbits, NASA's ODPO with support from the Air Force Research Laboratory (AFRL), has constructed a new observatory dedicated to orbital debris - the Meter Class Autonomous Telescope (MCAT) on Ascension Island. This location provides MCAT with the unique ability to access targets orbiting at an altitude of less than 1,000 km and low inclinations (< 20 deg). This orbital regime currently has little to no coverage by the U.S. Space Surveillance Network. Unlike previous ODPO optical assets, the ability to operate autonomously will allow rapid response observations of break-up events, an observing mode that was only available via radar tasking prior to MCAT's deployment. The primary goal of MCAT is to statistically characterize GEO via daily tasking files uploaded from ODPO. These tasking files define which operating mode to follow, providing the field center, rates, and/or targets to observe over the entire observing period. The system is also capable of tracking fast-moving targets in low Earth orbit (LEO), middle Earth orbit (MEO), as well as highly eccentric orbits like geostationary transfer orbits. On 25 August 2015, MCAT successfully acquired scientific first light, imaging the Bug Nebula and tracked objects in LEO, MEO, and GEO. NASA is working towards characterizing the system and thoroughly testing the integrated hardware and software control to achieve fully autonomous operations by late 2016. This paper will review the history and current status of the MCAT project, the details of the telescope system, and its five currently manifested operating modes.

Cowardin, H.↗
NASA NTRS2016

Environmentally Friendly Coating Technology for Autonomous Corrosion Control

This work concerns the development of environmentally friendly encapsulation technology, specifically designed to incorporate corrosion indicators, inhibitors, and self-healing agents into a coating, in such a way that the delivery of the indicators and inhibitors is triggered by the corrosion process, and the delivery of self-healing agents is triggered by mechanical damage to the coating. Encapsulation of the active corrosion control ingredients allows the incorporation of desired autonomous corrosion control functions such as: early corrosion detection, hidden corrosion detection, corrosion inhibition, and self-healing of mechanical damage into a coating. The technology offers the versatility needed to include one or several corrosion control functions into the same coating.The development of the encapsulation technology has progressed from the initial proof-of-concept work, in which a corrosion indicator was encapsulated into an oil-core (hydrophobic) microcapsule and shown to be delivered autonomously, under simulated corrosion conditions, to a sophisticated portfolio of micro carriers (organic, inorganic, and hybrid) that can be used to deliver a wide range of active corrosion ingredients at a rate that can be adjusted to offer immediate as well as long-term corrosion control. The micro carriers have been incorporated into different coating formulas to test and optimize the autonomous corrosion detection, inhibition, and self-healing functions of the coatings. This paper provides an overview of progress made to date and highlights recent technical developments, such as improved corrosion detection sensitivity, inhibitor test results in various types of coatings, and highly effective self-healing coatings based on green chemistry.

Coatings↗
NASA NTRS2016

Towards Autonomous Operations of the Robonaut 2 Humanoid Robotic Testbed

The Robonaut project has been conducting research in robotics technology on board the International Space Station (ISS) since 2012. Recently, the original upper body humanoid robot was upgraded by the addition of two climbing manipulators ("legs"), more capable processors, and new sensors, as shown in Figure 1. While Robonaut 2 (R2) has been working through checkout exercises on orbit following the upgrade, technology development on the ground has continued to advance. Through the Active Reduced Gravity Offload System (ARGOS), the Robonaut team has been able to develop technologies that will enable full operation of the robotic testbed on orbit using similar robots located at the Johnson Space Center. Once these technologies have been vetted in this way, they will be implemented and tested on the R2 unit on board the ISS. The goal of this work is to create a fully-featured robotics research platform on board the ISS to increase the technology readiness level of technologies that will aid in future exploration missions. Technology development has thus far followed two main paths, autonomous climbing and efficient tool manipulation. Central to both technologies has been the incorporation of a human robotic interaction paradigm that involves the visualization of sensory and pre-planned command data with models of the robot and its environment. Figure 2 shows screenshots of these interactive tools, built in rviz, that are used to develop and implement these technologies on R2. Robonaut 2 is designed to move along the handrails and seat track around the US lab inside the ISS. This is difficult for many reasons, namely the environment is cluttered and constrained, the robot has many degrees of freedom (DOF) it can utilize for climbing, and remote commanding for precision tasks such as grasping handrails is time-consuming and difficult. Because of this, it is important to develop the technologies needed to allow the robot to reach operator-specified positions as autonomously as possible. The most important progress in this area has been the work towards efficient path planning for high DOF, highly constrained systems. Other advances include machine vision algorithms for localizing and automatically docking with handrails, the ability of the operator to place obstacles in the robot's virtual environment, autonomous obstacle avoidance techniques, and constraint management.

Badger, Julia↗
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 NTRS2015

Multigenerational Independent Colony for Extraterrestrial Habitation, Autonomy, and Behavior Health (MICEHAB): An Investigation of a Long Duration, Partial Gravity, Autonomous Rodent Colony

The path from Earth to Mars requires exploration missions to be increasingly Earth-independent as the foundation is laid for a sustained human presence in the following decades. NASA pioneering of Mars will expand the boundaries of human exploration, as a sustainable presence on the surface requires humans to successfully reproduce in a partial gravity environment independent from Earth intervention. Before significant investment is made in capabilities leading to such pioneering efforts, the challenges of multigenerational mammalian reproduction in a partial gravity environment need be investigated. The Multi-generational Independent Colony for Extraterrestrial Habitation, Autonomy, and Behavior health is designed to study these challenges. The proposed concept is a conceptual, long duration, autonomous habitat designed to house rodents in a partial gravity environment with the goal of understanding the effects of partial gravity on mammalian reproduction over multiple generations and how to effectively design such a facility to operate autonomously while keeping the rodents healthy in order to achieve multiple generations. All systems are designed to feed forward directly to full-scale human missions to Mars. This paper presents the baseline design concept formulated after considering challenges in the mission and vehicle architectures such as: vehicle automation, automated crew health management/medical care, unique automated waste disposal and hygiene, handling of deceased crew members, reliable long-duration crew support systems, and radiation protection. This concept was selected from an architectural trade space considering the balance between mission science return and robotic and autonomy capabilities. The baseline design is described in detail including: transportation and facility operation constraints, artificial gravity system design, habitat design, and a full-scale mock-up demonstration of autonomous rodent care facilities. The proposed concept has the potential to integrate into existing mission architectures in order to achieve exploration objectives, and to demonstrate and mature common capabilities that enable a range of destinations and missions.

Rodgers, Erica M.↗
NASA NTRS2015

Multi-Spacecraft Autonomous Positioning System

As the number of spacecraft in simultaneous operation continues to grow, there is an increased dependency on ground-based navigation support. The current baseline system for deep space navigation utilizes Earth-based radiometric tracking, requiring long-duration observations to perform orbit determination and generate a state update. The age, complexity, and high utilization of the ground assets pose a risk to spacecraft navigation performance. In order to perform complex operations at large distances from Earth, such as extraterrestrial landing and proximity operations, autonomous systems are required. With increasingly complex mission operations, the need for frequent and Earth-independent navigation capabilities is further reinforced. The Multi-spacecraft Autonomous Positioning System (MAPS) takes advantage of the growing interspacecraft communication network and infrastructure to allow for Earth-autonomous state measurements to enable network-based space navigation. A notional concept of operations is given in figure 1. This network is already being implemented and routinely used in Martian communications through the use of the Mars Reconnaissance Orbiter and Mars Odyssey spacecraft as relays for surface assets. The growth of this communications architecture is continued through MAVEN, and future potential commercial Mars telecom orbiters. This growing network provides an initial Marslocal capability for inter-spacecraft communication and navigation. These navigation updates are enabled by cross-communication between assets in the network, coupled with onboard navigation estimation routines to integrate packet travel time to generate ranging measurements. Inter-spacecraft communication allows for frequent state broadcasts and time updates from trusted references. The architecture is a software-based solution, enabling its implementation on a wide variety of current assets, with the operational constraints and measurement accuracy determined by onboard systems.

Anzalone, Evan↗
NASA NTRS2017

PHM Enabled Autonomous Propellant Loading Operations

The utility of Prognostics and Health Management (PHM) software capability applied to Autonomous Operations (AO) remains an active research area within aerospace applications. The ability to gain insight into which assets and subsystems are functioning properly, along with the derivation of confident predictions concerning future ability, reliability, and availability, are important enablers for making sound mission planning decisions. When coupled with software that fully supports mission planning and execution, an integrated solution can be developed that leverages state assessment and estimation for the purposes of delivering autonomous operations. The authors have been applying this integrated, model-based approach to the autonomous loading of cryogenic spacecraft propellants at Kennedy Space Center.

Walker, Mark↗
NASA NTRS2017

Development of Increasingly Autonomous Traffic Data Manager Using Pilot Relevancy and Ranking Data

NASA's Safe Autonomous Systems Operations (SASO) project goal is to define and safely enable all future airspace operations by justifiable and optimal autonomy for advanced air, ground, and connected capabilities. This work showcases how Increasingly Autonomous Systems (IAS) could create operational transformations beneficial to the enhancement of civil aviation safety and efficiency. One such IAS under development is the Traffic Data Manager (TDM). This concept is a prototype 'intelligent party-line' system that would declutter and parse out non-relevant air traffic, displaying only relevant air traffic to the aircrew in a digital data communications (Data Comm) environment. As an initial step, over 22,000 data points were gathered from 31 Airline Transport Pilots to train the machine learning algorithms designed to mimic human experts and expertise. The test collection used an analog of the Navigation Display. Pilots were asked to rate the relevancy of the displayed traffic using an interactive tablet application. Pilots were also asked to rank the order of importance of the information given, to better weight the variables within the algorithm. They were also asked if the information given was enough data, and more importantly the "right" data to best inform the algorithm. The paper will describe the findings and their impact to the further development of the algorithm for TDM and, in general, address the issue of how can we train supervised machine learning algorithms, critical to increasingly autonomous systems, with the knowledge and expertise of expert human pilots.

Le Vie, Lisa R.↗
NASA NTRS2017

NASA's Optical Program on Ascension Island: Bringing MCAT to Life as the Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT)

In June 2015, the construction of the Meter Class Autonomous Telescope was completed and MCAT saw the light of the stars for the first time. In 2017, MCAT was newly dedicated as the Eugene Stansbery-MCAT telescope by NASA's Orbital Debris Program Office (ODPO), in honor of his inspiration and dedication to this newest optical member of the NASA ODPO. Since that time, MCAT has viewed the skies with one engineering camera and two scientific cameras, and the ODPO optical team has begun the process of vetting the entire system. The full system vetting includes verification and validation of: (1) the hardware comprising the system (e.g. the telescopes and its instruments, the dome, weather systems, all-sky camera, FLIR cloud infrared camera, etc.), (2) the custom-written Observatory Control System (OCS) master software designed to autonomously control this complex system of instruments, each with its own control software, and (3) the custom written Orbital Debris Processing software for post-processing the data. ES-MCAT is now capable of autonomous observing to include Geosynchronous survey, TLE (Two-line element) tracking of individual catalogued debris at all orbital regimes (Low-Earth Orbit all the way to Geosynchronous (GEO) orbit), tracking at specified non-sidereal rates, as well as sidereal rates for proper calibration with standard stars. Ultimately, the data will be used for validation of NASA's Orbital Debris Engineering Model, ORDEM, which aids in engineering designs of spacecraft that require knowledge of the orbital debris environment and long-term risks for collisions with Resident Space Objects (RSOs).

Lederer, S. M.↗
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 NTRS2017

Modular Autonomous Systems Technology Framework: A Distributed Solution for System Monitoring and Control

The Modular Autonomous Systems Technology (MAST) framework is a tool for building distributed, hierarchical autonomous systems. Originally intended for the autonomous monitoring and control of spacecraft, this framework concept provides support for variable autonomy, assume-guarantee contracts, and efficient communication between subsystems and a centralized systems manager. MAST was developed at NASA's Johnson Space Center (JSC) and has been applied to an integrated spacecraft example scenario.

Badger, Julia M.↗
NASA NTRS2018

An Autonomous Power Controller for the NASA Human Deep Space Gateway

Autonomous control of a spacecraft is an enabling technology that must be developed for deep space human exploration. NASA's current long term human space platform, the International Space Station which is in Low Earth Orbit, is in almost continuous communication with ground based mission control. This allows near real-time control of all the vehicle core systems, including power, to be controlled by the ground. As the focus shifts from Low Earth Orbit, communication time-lag and bandwidth limitations beyond geosynchronous orbit does not permit this type of ground based operation. This paper presents the ongoing work at NASA to develop an architecture for autonomous power control system and a vehicle manager which monitors, coordinates, and delegates all the onboard subsystems to enable autonomous control of the complete spacecraft.

power control↗