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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Compact Optical Correlator

Optical cross-correlator indicates position of target (if any) in scene matching target encoded in matched filter. Size reduced by use of prisms to fold optical path. Device designed, assembled from commercial components, and tested to verify feasibility of miniaturization for eventual incorporation into navigational and/or control systems of autonomous vehicles. For example, aircraft equipped with optical correlator recognizes prescribed target and measures its position, so that it lands on target under automatic control.

Scholl, Marija S.↗
NASA NTRS1992

Sensors and sensor systems for guidance and navigation II; Proceedings of the Meeting, Orlando, FL, Apr. 22, 23, 1992

Topics discussed in this volume include aircraft guidance and navigation, optics for visual guidance of aircraft, spacecraft and missile guidance and navigation, lidar and ladar systems, microdevices, gyroscopes, cockpit displays, and automotive displays. Papers are presented on optical processing for range and attitude determination, aircraft collision avoidance using a statistical decision theory, a scanning laser aircraft surveillance system for carrier flight operations, star sensor simulation for astroinertial guidance and navigation, autonomous millimeter-wave radar guidance systems, and a 1.32-micron long-range solid state imaging ladar. Attention is also given to a microfabricated magnetometer using Young's modulus changes in magnetoelastic materials, an integrated microgyroscope, a pulsed diode ring laser gyroscope, self-scanned polysilicon active-matrix liquid-crystal displays, the history and development of coated contrast enhancement filters for cockpit displays, and the effect of the display configuration on the attentional sampling performance.

Welch, Sharon S.↗
NASA NTRS2018

Daring You to Ask What If? Centennial Challenges

Centennial Challenges: Cube Quest - Propulsion, communication around Moon and into deep space; 3D-Printed Habitat - Additive construction for in-space habitats using regolith and recyclables; Vascular Tissue - 3D-printed human organ tissue to advance medicine in space and on Earth; CO2 Conversion - Bio-manufacturing using carbon dioxide and in-situ resources on Mars; Space Robotics II - Autonomous robotic navigation and decision systems for ISRU tasks.

Centennial challenges↗
NASA NTRS2021

Demonstrations of System-Level Autonomy for Spacecraft

System-level autonomy refers to autonomously meeting the crosscutting needs of a system through awareness and coordinated control spanning the system's breadth of capabilities. In contrast to function-level autonomy, which focuses on capabilities required to achieve a specific function such as surface navigation or image recognition, system-level autonomy addresses the needs to coordinate and manage activities and resources, and estimate the state, across subsystems. This paper describes demonstrations that were conducted on a spacecraft workstation testbed. The autonomy was provided by system-level planning and execution integrated with system-level estimators of orbit knowledge and spacecraft hardware health. These components are embedded in a system-level framework defining how goals are formed and executed, which elements exist, and how control authority is distributed among components. The planning and execution system at the heart of the framework has the capability to schedule, execute and monitor completion of tasks, as well as plan around unexpected events including new science opportunities and anomalies. The planning and scheduling system is the Multi-mission EXECutive (MEXEC), supported by the system-level health state estimator Model-Based Off-Nominal State Identification and Detection (MONSID), and Autonomous Navigation (AutoNav) algorithms, which determine the orbital system state based on optical observation of other targets. These components are applicable to many kinds of missions on different platforms. These demonstrations were elaborations of earlier experiments conducted on the ASTERIA (Arcsecond Space Telescope Enabling Research In Astrophysics) CubeSat, described in a companion submission [1]. The spacecraft’s extended mission served as an in-flight test platform, during which some individual autonomous capabilities were flown successfully. The autonomy experiments described here were performed on the ASTERIA workstation testbed.

Prather, Maurice↗
NASA NTRS2018

Cobalt: Terrestrial Flight Test of Landing Navigation Using Lander Vision System with Navigation Doppler Lidar

COBALT (CoOperative Blending of Autonomous Landing Technologies) is a NASA technology development and test program to advance precision landing capabilities for future soft landers. The COBALT payload demonstrated terrain relative navigation utilizing the Lander Vision System and Navigation Doppler Lidar sensors on the Masten Space Systems Xodiac rocket. In spring 2017, the program culminated in two open-loop free flights to 500 m altitude with downrange diverts of 300 m. The COBALT system performed well, navigating within meters of the Xodiac vehicle’s GPS-based solution. This paper outlines details of the navigation filter and its performance during the test campaign.

Carson, John M. III↗
NASA NTRS1993

Driving a car with custom-designed fuzzy inferencing VLSI chips and boards

Vehicle control in a-priori unknown, unpredictable, and dynamic environments requires many calculational and reasoning schemes to operate on the basis of very imprecise, incomplete, or unreliable data. For such systems, in which all the uncertainties can not be engineered away, approximate reasoning may provide an alternative to the complexity and computational requirements of conventional uncertainty analysis and propagation techniques. Two types of computer boards including custom-designed VLSI chips were developed to add a fuzzy inferencing capability to real-time control systems. All inferencing rules on a chip are processed in parallel, allowing execution of the entire rule base in about 30 microseconds, and therefore, making control of 'reflex-type' of motions envisionable. The use of these boards and the approach using superposition of elemental sensor-based behaviors for the development of qualitative reasoning schemes emulating human-like navigation in a-priori unknown environments are first discussed. Then how the human-like navigation scheme implemented on one of the qualitative inferencing boards was installed on a test-bed platform to investigate two control modes for driving a car in a-priori unknown environments on the basis of sparse and imprecise sensor data is described. In the first mode, the car navigates fully autonomously, while in the second mode, the system acts as a driver's aid providing the driver with linguistic (fuzzy) commands to turn left or right and speed up or slow down depending on the obstacles perceived by the sensors. Experiments with both modes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Simulation results as well as indoors and outdoors experiments are presented and discussed to illustrate the feasibility and robustness of autonomous navigation and/or safety enhancing driver's aid using the new fuzzy inferencing hardware system and some human-like reasoning schemes which may include as little as six elemental behaviors embodied in fourteen qualitative rules.

Pin, Francois G.↗
NASA NTRS2008

The Next 25 Years of Deep Space Navigation

This slide presentation reviews the missions that will be flown into deep space in the next 25 years, the navigational challenges for these missions, and the strategies that will be used to overcome these challenges. The challenges include: (1) an incresed need for autonomous navigation, (2) an increased use of in-situ and optical navigation, (3) an increased use of low-thrust propulsion, (4) an increased need for higher accuracy in guidance, navigation, and control, and an increased need for integration between flight path and attitude control. The enabling strategies that are planned for use are: (1) Advance Radio-Metric Tracking Capabilities, (2) Expand the Use of Optical Navigation, (3) Develop General-Purpose Autonomous Navigation Capabilities, (4) Improve Frequency and Timing Systems, and (5) Develop In-situ Tracking Infrastructure. Future trends that are being developed are Optical and Autonomous Navigation

optical navigation↗
NASA NTRS1993

A parallel implementation of a multisensor feature-based range-estimation method

There are many proposed vision based methods to perform obstacle detection and avoidance for autonomous or semi-autonomous vehicles. All methods, however, will require very high processing rates to achieve real time performance. A system capable of supporting autonomous helicopter navigation will need to extract obstacle information from imagery at rates varying from ten frames per second to thirty or more frames per second depending on the vehicle speed. Such a system will need to sustain billions of operations per second. To reach such high processing rates using current technology, a parallel implementation of the obstacle detection/ranging method is required. This paper describes an efficient and flexible parallel implementation of a multisensor feature-based range-estimation algorithm, targeted for helicopter flight, realized on both a distributed-memory and shared-memory parallel computer.

Suorsa, Raymond E.↗
NASA NTRS1993

A parallel implementation of a multisensor feature-based range-estimation method

There are many proposed vision based methods to perform obstacle detection and avoidance for autonomous or semi-autonomous vehicles. All methods, however, will require very high processing rates to achieve real time performance. A system capable of supporting autonomous helicopter navigation will need to extract obstacle information from imagery at rates varying from ten frames per second to thirty or more frames per second depending on the vehicle speed. Such a system will need to sustain billions of operations per second. To reach such high processing rates using current technology, a parallel implementation of the obstacle detection/ranging method is required. This paper describes an efficient and flexible parallel implementation of a multisensor feature-based range-estimation algorithm, targeted for helicopter flight, realized on both a distributed-memory and shared-memory parallel computer.

Suorsa, Raymond E.↗
NASA NTRS2015

Systems and Methods for Automated Vessel Navigation Using Sea State Prediction

Systems and methods for sea state prediction and autonomous navigation in accordance with embodiments of the invention are disclosed. One embodiment of the invention includes a method of predicting a future sea state including generating a sequence of at least two 3D images of a sea surface using at least two image sensors, detecting peaks and troughs in the 3D images using a processor, identifying at least one wavefront in each 3D image based upon the detected peaks and troughs using the processor, characterizing at least one propagating wave based upon the propagation of wavefronts detected in the sequence of 3D images using the processor, and predicting a future sea state using at least one propagating wave characterizing the propagation of wavefronts in the sequence of 3D images using the processor. Another embodiment includes a method of autonomous vessel navigation based upon a predicted sea state and target location.

Huntsberger, Terrance L.↗
NASA NTRS2017

Systems and Methods for Automated Vessel Navigation Using Sea State Prediction

Systems and methods for sea state prediction and autonomous navigation in accordance with embodiments of the invention are disclosed. One embodiment of the invention includes a method of predicting a future sea state including generating a sequence of at least two 3D images of a sea surface using at least two image sensors, detecting peaks and troughs in the 3D images using a processor, identifying at least one wavefront in each 3D image based upon the detected peaks and troughs using the processor, characterizing at least one propagating wave based upon the propagation of wavefronts detected in the sequence of 3D images using the processor, and predicting a future sea state using at least one propagating wave characterizing the propagation of wavefronts in the sequence of 3D images using the processor. Another embodiment includes a method of autonomous vessel navigation based upon a predicted sea state and target location.

Huntsberger, Terrance L.↗
NASA NTRS2019

Predicted Performance of an X-Ray Navigation System for Future Deep Space and Lunar Missions

In November 2017, the NASA Goddard Space Flight Center (GSFC) Station Explorer for X-ray Timing and Navigation Technology (SEXTANT) experiment successfully demonstrated the feasibility of X-ray Pulsar Navigation (XNAV) as part of the Neutron Star Interior Composition Explorer (NICER) mission, which is an X-ray Astrophysics Mission of Opportunity currently operating onboard the International Space Station (ISS). XNAV provides a GPS-like absolute autonomous navigation and timing capability available anywhere in the Solar System and beyond. While the most significant benefits of XNAV are expected to come in support of very deep-space missions, the absolute autonomous navigation and timing capability also has utility for inner Solar System missions where increased autonomy or backup navigation and timing services are required, e.g., address loss of communication scenarios.The NASA commitment to develop a Gateway to support exploration of the Moon and eventually Mars, as well as current and future robotic missions such as James Webb Space Telescope (JWST), New Horizons, and much more, certainly will tax the existing ground based infrastructure in terms of availability. There- fore, an extended look at the feasibility and potential performance of XNAV for comparable missions is warranted. In this paper, we briefly review the XNAV concept and present case studies of its utility and performance for a Gateway orbit, Sun-Earth libration orbit, and a deep space transit trajectory.

Getchius, Joel↗
NASA NTRSDate not supplied

A Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

The emergence and development of advanced technologies and vehicle types has created a growing demand for the introduction of new forms of flight operations. These new and increasingly complex operational paradigms such as Advanced and Urban Air Mobility (AAM/UAM) present regulatory authorities and the aviation community with several design and implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is finding methods to integrate these emerging operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. This paper focus on the development and testing of a prognostic service aimed at estimating the quality of Global Navigation Satellite System (GNSS) performance for an autonomous aircraft in complex environments. The intent of this function is to proactively reduce a flight operations risk of exposure to states that may induce poor or unacceptable navigation system performance by factoring in estimates of GNSS quality into pre-flight and/or in-flight route planning. Methodologies for producing quality estimates are specified and results are provided for selected simulation and flight test cases.

GNSS↗
DOE OSTI2022

Autonomous Aerial Power Plant Inspection in GPS-denied Environments

Inspection of coal-fired power plants is frequently dangerous, includes difficult places to reach, and can turn expensive due to the downtimes and cost of inspection crew. Robotic systems have shown capabilities to address some of these issues, but most of the current robotic inspection technology in power plants is designed for specific components. Conversely, recent advances in machine vision have empowered aerial platforms for long-range, remotely-controlled, GPS-based inspections of industrial plants. This capability has led to wide spread utilization of aerial robots (commonly termed Drones, UVS or UAS) platforms for inspection in less challenging environments where both collision avoidance, and GPS reception are not significant issues. The challenge in adapting airborne technology for power plant inspection lies in internal structures and the complex network of piping, and distribution systems, which impose significant risks for collision and can hinder the reception and transmission of GPS signals. The current state of the art in aerial inspection technology within the energy sector is controlled via radio control, and utilizes GPS-based navigation, for inspection of large-scale plants such as offshore platforms and wind turbine parks. Nevertheless, close-range and autonomous inspection in the GPS-denied environments of power plants has not yet been achieved, as it requires precise guidance and navigation with real-time situational awareness and obstacle avoidance capabilities. This endeavor introduced the use of rotary wing flying robots, due to their station keeping and vertical take-off capabilities for power plant components inspection. To enable close quarter inspection two methods were used. One method uses the 3D CAD (Three-dimensional Computer-Aided Design) model of the asset to inspect to generate the UAV’s inspection path. To acquire, analyze and process the 3D model, first, the STL file is produced to obtain surface points and vectors normal to the surface. Later, by introducing other variables such as wall offset and a controlled trajectory between each outline and each subsequent layer, the flight path is generated. The proposed framework will generate a path that will pass as close as desired from the surface and navigate in intricate environments. A second method, use advanced manufacturing techniques such as CNC (Computer Numerical Control) and additive manufacturing. Once the inspection flight path is obtained, vision-based navigation systems are employed to have the UAV autonomously tracking the provided trajectory. Finally, Artificial Intelligence-enabled developments are in charge of detecting cracks and corrosion in structural components of power plants. The proposed methods are validated in simulations, laboratory and industrial setups, where it is shown that the developed systems acting together enable close-quarter autonomous aerial inspection and mapping in power plant assets. The system can be further improved by adding more sensors to navigate in different GPS-denied environments, with non-homogeneous lighting conditions, dust and in general situations where vision-based systems may fail.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2008

Wind-Based Navigation of a Hot-air Balloon on Titan: A Feasibility Study

Current analysis of data streamed back to Earth by the Cassini spacecraft features Titan as one of the most exciting places in the solar system. NASA centers and universities around the US, as well as the European Space Agency, are studying the possibility of sending, as part of the next mission to this giant moon of Saturn, a hot-air balloon (Montgolfier-type) for further and more in-depth exploration. The basic idea would be to design a reliable, semi-autonomous, and yet cheap Montgolfier capable of using continuous flow of waste heat from a power source to lift the balloon and sustain its altitude in the Titan environment. In this paper we study the problem of locally navigating a hot-air balloon in the nitrogen-based Titan atmosphere. The basic idea is to define a strategy (i.e. design of a suitable guidance system) that allows autonomous and semi-autonomous navigation of the balloon using the available (and partial) knowledge of the wind structure blowing on the saturnian satellite surface. Starting from first principles we determined the appropriate thermal and dynamical models describing (a) the vertical dynamics of the balloon and (b) the dynamics of the balloon moving on a vertical plane (2-D motion). Next, various non-linear fuzzy-based control strategies have been evaluated, analyzed and implemented in MATLAB to numerically simulate the capability of the system to simultaneously maintain altitude, as well as a scientifically desirable trajectory. We also looked at the ability of the balloon to perform station keeping. The results of the simulation are encouraging and show the effectiveness of such a system to cheaply and effectively perform semiautonomous exploration of Titan.

balloon dynamics↗
NASA NTRS1993

Real-time qualitative reasoning for telerobotic systems

This paper discusses the sensor-based telerobotic driving of a car in a-priori unknown environments using 'human-like' reasoning schemes implemented on custom-designed VLSI fuzzy inferencing boards. These boards use the Fuzzy Set theoretic framework to allow very vast (30 kHz) processing of full sets of information that are expressed in qualitative form using membership functions. The sensor-based and fuzzy inferencing system was incorporated on an outdoor test-bed platform to investigate two control modes for driving a car on the basis of very sparse and imprecise range data. In the first mode, the car navigates fully autonomously to a goal specified by the operator, while in the second mode, the system acts as a telerobotic driver's aid providing the driver with linguistic (fuzzy) commands to turn left or right, speed up, slow down, stop, or back up depending on the obstacles perceived by the sensors. Indoor and outdoor experiments with both modes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Sample results are presented that illustrate the feasibility of developing autonomous navigation modules and robust, safety-enhancing driver's aids for telerobotic systems using the new fuzzy inferencing VLSI hardware and 'human-like' reasoning schemes.

Pin, Eancois G.↗
NASA NTRS2002

Fast and reliable obstacle detection and segmentation for cross-country navigation

Obstacle detection is one of the main components of the control system of autonomous vehicles. In the case of indoor/urban navigation, obstacles are typically defined as surface points that are higher than the ground plane. This characterization, however, cannot be used in cross-country and unstructured environments, where the notion of ground plane is often not meaningful.

autonomous navigation obstacle detection terrain p↗