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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Front Delineation and Tracking with Multiple Underwater Vehicles

This work describes a method for detecting and tracking ocean fronts using multiple autonomous underwater vehicles. Multiple vehicles — equally-spaced along the expected frontal boundary — complete near parallel transects orthogonal to the front. Lateral gradients are used to determine the location of the front crossing from each individual vehicle transect by detecting a change in the observed water property. Adaptive control of the vehicles ensure they remain perpendicular to the estimated front boundary as it evolves over time. This method was demonstrated in and around Monterey Bay, California in May of 2017. We compare the front detection method to previously used methods. We introduce a metric in order to evaluate the adaptive control techniques presented. We show the capability of this method for repeated sampling across a dynamic two-dimensional ocean front using short-range Iver AUVs. This method extends to tracking gradients of different properties using a variety of vehicles.

Chavez, Francisco P.↗
NASA NTRS1999

Communications and Tracking of Visiting Vehicles near ISS: The Design of the Reusable Launch Vehicle Communications

The International Space Station (ISS) will provide for the visitation of various vehicles such as the Shuttle, Automated Transfer Vehicle (ATV), H-II Transfer Vehicle (HTV), Crew Return Vehicle (CRV), Reusable Launch Vehicle (RLV) and Soyuz. These vehicles will provide for crew replacement, consumables resupply, and equipment delivery. In order for these vehicles to approach and eventually dock with the ISS, there must be near continuous communications coverage between the visiting vehicle and the ISS, as well as communications between the vehicle and a Mission Control Center (MCC). Since the ISS communications systems are already designed and scheduled for ISS activation, the vehicles must either utilize these communications systems or provide their own. There are two means of two-way communications with the ISS. These are (1) S-Band communications using TDRSS, and (2) UHF communications using some form of the Space to Space Station Radio (SSSR) link. The RLV utilizes ISS compatible communications systems to communicate with both the ISS and a Mission Control Center. Since all vehicles must adhere to the Visiting Vehicle Interface requirements given in reference 1, the RLV communications system design must meet these requirements during entry into the ISS Approach Ellipsoid (AE) and during Proximity Operations. Included in this paper are descriptions of these communications approaches as well as their potential utilization in the ISS communications system.

Stillwagen, Frederic H.↗
NASA NTRS2014

Tethered Vehicle Control and Tracking System

A kite system includes a kite and a ground station. The ground station includes a sensor that can be utilized to determine an angular position and velocity of the kite relative to the ground station. A controller utilizes a fuzzy logic control system to autonomously fly the kite. The system may include a ground station having powered winding units that generate power as the lines to the kite are unreeled. The control system may be configured to fly the kite in a crosswind trajectory to increase line tension for power generation. The sensors for determining the position of the kite are preferably ground-based.

North, David D.↗
NASA NTRS2017

Tethered Vehicle Control and Tracking System

A kite system includes a kite and a ground station. The ground station includes a sensor that can be utilized to determine an angular position and velocity of the kite relative to the ground station. A controller utilizes a fuzzy logic control system to autonomously fly the kite. The system may include a ground station having powered winding units that generate power as the lines to the kite are unreeled. The control system may be configured to fly the kite in a crosswind trajectory to increase line tension for power generation. The sensors for determining the position of the kite are preferably ground-based.

North, David D.↗
NASA NTRS1983

Comparison of road load simulator test results with track tests on electric vehicle propulsion system

A special-purpose dynamometer, the road load simulator (RLS), is being used at NASA's Lewis Research Center to test and evaluate electric vehicle propulsion systems developed under DOE's Electric and Hybrid Vehicle Program. To improve correlation between system tests on the RLS and track tests, similar tests were conducted on the same propulsion system on the RLS and on a test track. These tests are compared in this report. Battery current to maintain a constant vehicle speed with a fixed throttle was used for the comparison. Scatter in the data was greater in the track test results. This is attributable to variations in tire rolling resistance and wind effects in the track data. It also appeared that the RLS road load, determined by coastdown tests on the track, was lower than that of the vehicle on the track. These differences may be due to differences in tire temperature.

Dustin, M. O.↗
NASA NTRS1972

Tracking the Lunar Rover vehicle with very long baseline interferometry techniques

The principles of operation of Very Long Baseline Interferometry (VLBI) are discussed. The application of VLBI techniques for tracking lunar rover vehicles during the Apollo 16 and 17 missions is reported. A map of the Apollo 16 lunar rover track is provided. Charts are developed to show the incremental motion of the lunar vehicle during the mission.

Shnidman, D.↗
NASA NTRS2018

Planning and Execution for Front Delineation and Tracking with Multiple Underwater Vehicles

This work describes a planning architecture for a heterogeneous fleet of marine assets as well as a method for detecting and tracking ocean fronts using multiple autonomous underwater vehicles. Multiple vehicles — equally-spaced along the expected frontal boundary — complete near parallel transects orthogonal to the front. Lateral gradients are used to determine the location of the front crossing from each individual vehicle transect by detecting a change in the observed water property. Adaptive control of the vehicles ensure they remain perpendicular to the estimated frontal boundary as it evolves over time. This method was demonstrated in several experiment periods totaling weeks, in and around Monterey Bay, California in May and June of 2017. We discuss the challenges associated with the implementation of the planning system. We show the capability of this method for repeated sampling across a dynamic two-dimensional ocean front using a fleet of three types of platforms: short-range Iver AUVs, Tethys-Class Long-Range AUVs, and Seagliders. This method extends to tracking gradients of different properties using a variety of vehicles.

Chavez, Francisco P.↗
NASA NTRS1987

Optical alignment of Centaur's inertial guidance system

During Centaur launch operations the launch azimuth of the inertial platform's U-accelerometer input axis must be accurately established and maintained. This is accomplished by using an optically closed loop system with a long-range autotheodolite whose line of sight was established by a first-order survey. A collimated light beam from the autotheodolite intercepts a reflecting Porro prism mounted on the platform azimuth gimbal. Thus, any deviation of the Porro prism from its predetermined heading is optically detected by the autotheodolite. The error signal produced is used to torque the azimuth gimbal back to its required launch azimuth. The heading of the U-accelerometer input axis is therefore maintained automatically. Previously, the autotheodolite system could not distinguish between vehicle sway and rotational motion of the inertial platform unless at least three prisms were used. One prism was mounted on the inertial platform to maintain azimuth alignment, and two prisms were mounted externally on the vehicle to track sway. For example, the automatic azimuth-laying theodolite (AALT-SV-M2) on the Saturn vehilce used three prisms. The results of testing and modifying the AALT-SV-M2 autotheodolite to simultaneously monitor and maintain alignment of the inertial platform and track the sway of the vehicle from a single Porro prism.

Gordan, Andrew L.↗
NASA NTRS1994

A teleoperated system for remote site characterization

The detection and characterization of buried objects and materials is an important step in the restoration of burial sites containing chemical and radioactive waste materials at Department of Energy (DOE) and Department of Defense (DOD) facilities. By performing these tasks with remotely controlled sensors, it is possible to obtain improved data quality and consistency as well as enhanced safety for on-site workers. Therefore, the DOE Office of Technology Development and the US Army Environmental Center have jointly supported the development of the Remote Characterization System (RCS). One of the main components of the RCS is a small remotely driven survey vehicle that can transport various combinations of geophysical and radiological sensors. Currently implemented sensors include ground-penetrating radar, magnetometers, an electromagnetic induction sensor, and a sodium iodide radiation detector. The survey vehicle was constructed predominantly of non-metallic materials to minimize its effect on the operation of its geophysical sensors. The system operator controls the vehicle from a remote, truck-mounted, base station. Video images are transmitted to the base station by a radio link to give the operator necessary visual information. Vehicle control commands, tracking information, and sensor data are transmitted between the survey vehicle and the base station by means of a radio ethernet link. Precise vehicle tracking coordinates are provided by a differential Global Positioning System (GPS).

Sandness, Gerald A.↗
NASA NTRS2010

eLaunch Hypersonics: An Advanced Launch System

This presentation describes a new space launch system that NASA can and should develop. This approach can significantly reduce ground processing and launch costs, improve reliability, and broaden the scope of what we do in near earth orbit. The concept (not new) is to launch a re-usable air-breathing hypersonic vehicle from a ground based electric track. This vehicle launches a final rocket stage at high altitude/velocity for the final leg to orbit. The proposal here differs from past studies in that we will launch above Mach 1.5 (above transonic pinch point) which further improves the efficiency of air breathing, horizontal take-off launch systems. The approach described here significantly reduces cost per kilogram to orbit, increases safety and reliability of the boost systems, and reduces ground costs due to horizontal-processing. Finally, this approach provides significant technology transfer benefits for our national infrastructure.

Starr, Stanley↗
NASA NTRS1989

Optical Tracker For Longwall Coal Shearer

Photographic record yields information for correction of vehicle path. Tracking system records lateral movements of longwall coal-shearing vehicle. System detects lateral and vertical deviations of path of vehicle moving along coal face, shearing coal as it goes. Rides on rails in mine tunnel, advancing on toothed track in one of rails. As vehicle moves, retroreflective mirror rides up and down on teeth, providing series of pulsed reflections to film recorder. Recorded positions of pulses, having horizontal and vertical orientations, indicate vertical and horizontal deviations, respectively, of vehicle.

Poulsen, Peter D.↗
NASA NTRS2010

360-Degree Visual Detection and Target Tracking on an Autonomous Surface Vehicle

This paper describes perception and planning systems of an autonomous sea surface vehicle (ASV) whose goal is to detect and track other vessels at medium to long ranges and execute responses to determine whether the vessel is adversarial. The Jet Propulsion Laboratory (JPL) has developed a tightly integrated system called CARACaS (Control Architecture for Robotic Agent Command and Sensing) that blends the sensing, planning, and behavior autonomy necessary for such missions. Two patrol scenarios are addressed here: one in which the ASV patrols a large harbor region and checks for vessels near a fixed asset on each pass and one in which the ASV circles a fixed asset and intercepts approaching vessels. This paper focuses on the ASV's central perception and situation awareness system, dubbed Surface Autonomous Visual Analysis and Tracking (SAVAnT), which receives images from an omnidirectional camera head, identifies objects of interest in these images, and probabilistically tracks the objects' presence over time, even as they may exist outside of the vehicle's sensor range. The integrated CARACaS/SAVAnT system has been implemented on U.S. Navy experimental ASVs and tested in on-water field demonstrations.

ASV (AUTONOMOUS SEA SURFACE VEHICLE)↗
NASA NTRS2019

Airborne Radar for sUAS Sense and Avoid

A primary challenge for the safe integration of small UAS operations into the National Airspace System (NAS) is traffic deconfliction, both from manned and unmanned aircraft. The UAS Traffic Management (UTM) project being conducted at the National Aeronautics and Space Administration (NASA) considers a layered approach to separation provision, ranging from segregation of operations through airspace volumes (geofences) to autonomous sense and avoid (SAA) technologies for higher risk, densely occupied airspace. Cooperative SAA systems, such as Automatic Dependent Surveillance-Broadcast (ADS-B) and/or vehicle-to-vehicle communication systems provide significant additional risk mitigation but they fail to adequately mitigate collision risks for non-cooperative (non-transponder equipped) airborne aircraft. The RAAVIN (Radar on Autonomous Aircraft to Verify ICAROUS Navigation) flight test being conducted by NASA and the Mid-Atlantic Aviation Partnership (MAAP) was designed to investigate the applicability and performance of a prototype, commercially available sUAS radar to detect and track non-cooperative airborne traffic, both manned and unmanned. The radar selected for this research was a Frequency Modulated Continuous Wave (FMCW) radar with 120 degree azimuth and 80 degree elevation field of view operating at 24.55GHz center frequency with a 200 MHz bandwidth. The radar transmits 2 watts of power thru a Metamaterial Electronically Scanning Array antenna in horizontal polarization. When the radar is transmitting, personnel must be at least 1 meter away from the active array to limit nonionizing radiation exposure. The radar physical dimensions are 18.7cm by 12.1cm by 4.1cm and it weighs less than 820 grams making it well suited for installation on small UASs. The onboard, SAA capability, known as ICAROUS, (Independent Configurable Architecture for Reliable Operations of Unmanned Systems), developed by NASA to support sUAS operations, will provide autonomous guidance using the traffic radar tracks from the onboard radar. The RAAVIN set of studies will be conducted in three phases. The first phase included outdoor, ground-based radar evaluations performed at the Virginia Tech’s Kentland Farm testing range in Blacksburg, VA. The test was designed to measure how well the radar could detect and track a small UAS flying in the radar’s field of view. The radar was used to monitor 5 test flights consisting of outbound, inbound and crossing routes at different ranges and altitudes. The UAS flown during the ground test was the Inspire 2, a quad copter weighing less than 4250 grams (10 pounds) at maximum payload. The radar was set up to scan and track targets over its full azimuthal field of view from 0 to 40 degrees in elevation. The radar was configured to eliminate tracks generated from any targets located beyond 2000 meters from the radar and moving at velocities under 1.45 meters per second. For subsequent phases of the study the radar will be integrated with a sUAS platform to evaluate its performance in flight for SAA applications ranging from sUAS to manned GA aircraft detections and tracking. Preliminary data analysis from the first outdoor ground tests showed the radar performed well at tracking the vehicle as it flew outbound and repeatedly maintained a track out to 1000 meters (maximum 1387 meters) until the vehicle slowed to a stop to reverse direction to fly inbound. As the Inspire flew inbound tracks from beyond 800 meters, a reacquisition time delay was consistently observed between when the Inspire exceeds a speed of 1.45 meters per second and when the radar indicated an inbound target was present and maintained its track. The time delay varied between 6 seconds to over 37 seconds for the inbound flights examined, and typically resulted in about a 200 meter closure distance before the Inspire track was maintained. The radar performed well at both acquiring and tracking the vehicle as it flew crossing routes out past 400 meters across the azimuthal field of view. The radar and ICAROUS software will be integrated and flown on a BFD-1400-SE8-E UAS during the next phase of the RAAVIN project. The main goal at the conclusion of this effort is to determine if this radar technology can reliably support minimum requirements for SAA applications of sUAS. In particular, the study will measure the range of vehicle detections, lateral and vertical angular errors, false and missed/late detections, and estimated distance at closest point of approach after an avoidance maneuver is executed. This last metric is directly impacted by sensor performance and indicates its suitability for the task.

Szatkowski, George N.↗
DOE OSTI2023

Real-Time Multi-Vehicle Multi-Camera Tracking with Graph-Based Tracklet Features

An essential application in intelligent transportation systems is multi-target multi-camera tracking (MTMCT), where the target’s activity is tracked from different cameras. Although the tracking-by-detection scheme is the primary paradigm in MTMCT, the object association information from the video frames is lost. This is mainly because the multi-camera multi-object matching uses the information from the video frames separately. To solve this problem and leverage this association information, we propose an MTMCT framework, where features are built in the form of a graph and a graph similarity algorithm is used to match multi-camera objects. In this paper, we focus on the real-time scenario, where only the past images are used to match an object. Our method achieves an IDF1 score (the ratio of the number of correctly identified objects to the number of ground truth and average objects) of 0.75 with a rate of 14 frames per second (fps).

Engineering↗