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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 19 records

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NASA NTRS2008

Embedded Relative Navigation Sensor Fusion Algorithms for Autonomous Rendezvous and Docking Missions

bd Systems (a subsidiary of SAIC) has developed a suite of embedded relative navigation sensor fusion algorithms to enable NASA autonomous rendezvous and docking (AR&D) missions. Translational and rotational Extended Kalman Filters (EKFs) were developed for integrating measurements based on the vehicles' orbital mechanics and high-fidelity sensor error models and provide a solution with increased accuracy and robustness relative to any single relative navigation sensor. The filters were tested tinough stand-alone covariance analysis, closed-loop testing with a high-fidelity multi-body orbital simulation, and hardware-in-the-loop (HWIL) testing in the Marshall Space Flight Center (MSFC) Flight Robotics Laboratory (FRL).

DeKock, Brandon K.↗

NASA NTRS1990

Sensor fusion II: Human and machine strategies; Proceedings of the Meeting, Philadelphia, PA, Nov. 6-9, 1989

Various papers on human and machine strategies in sensor fusion are presented. The general topics addressed include: active vision, measurement and analysis of visual motion, decision models for sensor fusion, implementation of sensor fusion algorithms, applying sensor fusion to image analysis, perceptual modules and their fusion, perceptual organization and object recognition, planning and the integration of high-level knowledge with perception, using prior knowledge and context in sensor fusion.

Schenker, Paul S.↗

NASA NTRS1989

Neural network implementations of data association algorithms for sensor fusion

The paper is concerned with locating a time varying set of entities in a fixed field when the entities are sensed at discrete time instances. At a given time instant a collection of bivariate Gaussian sensor reports is produced, and these reports estimate the location of a subset of the entities present in the field. A database of reports is maintained, which ideally should contain one report for each entity sensed. Whenever a collection of sensor reports is received, the database must be updated to reflect the new information. This updating requires association processing between the database reports and the new sensor reports to determine which pairs of sensor and database reports correspond to the same entity. Algorithms for performing this association processing are presented. Neural network implementation of the algorithms, along with simulation results comparing the approaches are provided.

Brown, Donald E.↗

DOE OSTI2021

WHISPER: Wireless Home Identification and Sensing Platform for Energy Reduction

Many regions of the world benefit from heating, ventilating, and air-conditioning (HVAC) systems to provide productive, comfortable, and healthy indoor environments, which are enabled by automatic building controls. Due to climate change, population growth, and industrialization, HVAC use is globally on the rise. Unfortunately, these systems often operate in a continuous fashion without regard to actual human presence, leading to unnecessary energy consumption. As a result, the heating, ventilation, and cooling of unoccupied building spaces makes a substantial contribution to the harmful environmental impacts associated with carbon-based electric power generation, which is important to remedy. For our modern electric power system, transitioning to low-carbon renewable energy is facilitated by integration with distributed energy resources. Automatic engagement between the grid and consumers will be necessary to enable a clean yet stable electric grid, when integrating these variable and uncertain renewable energy sources. We present the WHISPER (Wireless Home Identification and Sensing Platform for Energy Reduction) system to address the energy and power demand triggered by human presence in homes. The presented system includes a maintenance-free and privacy-preserving human occupancy detection system wherein a local wireless network of battery-free environmental, acoustic energy, and image sensors are deployed to monitor homes, record empirical data for a range of monitored modalities, and transmit it to a base station. Several machine learning algorithms are implemented at the base station to infer human presence based on the received data, harnessing a hierarchical sensor fusion algorithm. Results from the prototype system demonstrate an accuracy in human presence detection in excess of 95%; ongoing commercialization efforts suggest approximately 99% accuracy. Using machine learning, WHISPER enables various applications based on its binary occupancy prediction, allowing situation-specific controls targeted at both personalized smart home and electric grid modernization opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2012

Localization Using Visual Odometry and a Single Downward-Pointing Camera

Stereo imaging is a technique commonly employed for vision-based navigation. For such applications, two images are acquired from different vantage points and then compared using transformations to extract depth information. The technique is commonly used in robotics for obstacle avoidance or for Simultaneous Localization And Mapping, (SLAM). Yet, the process requires a number of image processing steps and therefore tends to be CPU-intensive, which limits the real-time data rate and use in power-limited applications. Evaluated here is a technique where a monocular camera is used for vision-based odometry. In this work, an optical flow technique with feature recognition is performed to generate odometry measurements. The visual odometry sensor measurements are intended to be used as control inputs or measurements in a sensor fusion algorithm using low-cost MEMS based inertial sensors to provide improved localization information. Presented here are visual odometry results which demonstrate the challenges associated with using ground-pointing cameras for visual odometry. The focus is for rover-based robotic applications for localization within GPS-denied environments.

Swank, Aaron J.↗

NASA NTRS2007

SPARTAN: A High-Fidelity Simulation for Automated Rendezvous and Docking Applications

bd Systems (a subsidiary of SAIC) has developed the Simulation Package for Autonomous Rendezvous Test and ANalysis (SPARTAN), a high-fidelity on-orbit simulation featuring multiple six-degree-of-freedom (6DOF) vehicles. SPARTAN has been developed in a modular fashion in Matlab/Simulink to test next-generation automated rendezvous and docking guidance, navigation,and control algorithms for NASA's new Vision for Space Exploration. SPARTAN includes autonomous state-based mission manager algorithms responsible for sequencing the vehicle through various flight phases based on on-board sensor inputs and closed-loop guidance algorithms, including Lambert transfers, Clohessy-Wiltshire maneuvers, and glideslope approaches The guidance commands are implemented using an integrated translation and attitude control system to provide 6DOF control of each vehicle in the simulation. SPARTAN also includes high-fidelity representations of a variety of absolute and relative navigation sensors that maybe used for NASA missions, including radio frequency, lidar, and video-based rendezvous sensors. Proprietary navigation sensor fusion algorithms have been developed that allow the integration of these sensor measurements through an extended Kalman filter framework to create a single optimal estimate of the relative state of the vehicles. SPARTAN provides capability for Monte Carlo dispersion analysis, allowing for rigorous evaluation of the performance of the complete proposed AR&D system, including software, sensors, and mechanisms. SPARTAN also supports hardware-in-the-loop testing through conversion of the algorithms to C code using Real-Time Workshop in order to be hosted in a mission computer engineering development unit running an embedded real-time operating system. SPARTAN also contains both runtime TCP/IP socket interface and post-processing compatibility with bdStudio, a visualization tool developed by bd Systems, allowing for intuitive evaluation of simulation results. A description of the SPARTAN architecture and capabilities is provided, along with details on the models and algorithms utilized and results from representative missions.

Turbe, Michael A.↗

NASA NTRS1992

Proposed evaluation framework for assessing operator performance with multisensor displays

Despite aggressive work on the development of sensor fusion algorithms and techniques, no formal evaluation procedures have been proposed. Based on existing integration models in the literature, an evaluation framework is developed to assess an operator's ability to use multisensor, or sensor fusion, displays. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The operator's performance with the sensor fusion display can be compared to the models' predictions based on the operator's performance when viewing the original sensor displays prior to fusion. This allows for the determination as to when a sensor fusion system leads to: 1) poorer performance than one of the original sensor displays (clearly an undesirable system in which the fused sensor system causes some distortion or interference); 2) better performance than with either single sensor system alone, but at a sub-optimal (compared to the model predictions) level; 3) optimal performance (compared to model predictions); or, 4) super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays. An experiment demonstrating the usefulness of the proposed evaluation framework is discussed.

Foyle, David C.↗

DOE OSTI2022

Real-time Condition Monitoring of Power Modules in Grid-tied Power Converter

This paper proposes and demonstrates a real-time condition monitoring method using gate driver integrated sensing circuits and sensor fusion algorithms. Power device on-state voltage (VDSon) measurement and junction temperature (Tj) sensing circuits with high noise immunity are built and integrated into an adaptive gate driver circuit for power modules. Considering the inherently noisy measurement environment of power converters, VDSon together with several other measurements are fused together to provide accurate descriptions of the stress and degradation of each power device. Furthermore, the gate driver circuit can actively control the turn-on gate voltage (VGSon) for each device based on the stress and degradation state. The proposed sensing circuits and power device condition assessment algorithms are implemented in a 75 KVA grid-tied power converter. This paper focuses on the sensing circuits hardware designs and testing in grid-tied power converter prototype and device stress index generation. More comprehensive results on the device state of health index generation will be presented in future work.

Fan, Junchong↗

NASA NTRS2005

Development and Application of Non-Linear Image Enhancement and Multi-Sensor Fusion Techniques for Hazy and Dark Imaging

The purpose of this research was to develop enhancement and multi-sensor fusion algorithms and techniques to make it safer for the pilot to fly in what would normally be considered Instrument Flight Rules (IFR) conditions, where pilot visibility is severely restricted due to fog, haze or other weather phenomenon. We proposed to use the non-linear Multiscale Retinex (MSR) as the basic driver for developing an integrated enhancement and fusion engine. When we started this research, the MSR was being applied primarily to grayscale imagery such as medical images, or to three-band color imagery, such as that produced in consumer photography: it was not, however, being applied to other imagery such as that produced by infrared image sources. However, we felt that it was possible by using the MSR algorithm in conjunction with multiple imaging modalities such as long-wave infrared (LWIR), short-wave infrared (SWIR), and visible spectrum (VIS), we could substantially improve over the then state-of-the-art enhancement algorithms, especially in poor visibility conditions. We proposed the following tasks: 1) Investigate the effects of applying the MSR to LWIR and SWIR images. This consisted of optimizing the algorithm in terms of surround scales, and weights for these spectral bands; 2) Fusing the LWIR and SWIR images with the VIS images using the MSR framework to determine the best possible representation of the desired features; 3) Evaluating different mixes of LWIR, SWIR and VIS bands for maximum fog and haze reduction, and low light level compensation; 4) Modifying the existing algorithms to work with video sequences. Over the course of the 3 year research period, we were able to accomplish these tasks and report on them at various internal presentations at NASA Langley Research Center, and in presentations and publications elsewhere. A description of the work performed under the tasks is provided in Section 2. The complete list of relevant publications during the research periods is provided in Section 5. This research also resulted in the generation of intellectual property.

Rahman, Zia-ur↗

NASA NTRS1992

A data fusion algorithm for multi-sensor microburst hazard assessment

A recursive model-based data fusion algorithm for multi-sensor microburst hazard assessment is described. An analytical microburst model is used to approximate the actual windfield, and a set of 'best' model parameters are estimated from measured winds. The winds corresponding to the best parameter set can then be used to compute alerting factors such as microburst position, extent, and intensity. The estimation algorithm is based on an iterated extended Kalman filter which uses the microburst model parameters as state variables. Microburst state dynamic and process noise parameters are chosen based on measured microburst statistics. The estimation method is applied to data from a time-varying computational simulation of a historical microburst event to demonstrate its capabilities and limitations. Selection of filter parameters and initial conditions is discussed. Computational requirements and datalink bandwidth considerations are also addressed.

Wanke, Craig R.↗

NASA NTRS1994

A data fusion algorithm for multi-sensor microburst hazard assessment

Wanke, Craig R.↗

DOE OSTI2021

Fusion-based occupancy sensing for building systems

Sensing and control apparatus for a building HVAC system includes interior and boundary sensors, such as cameras and thermal sensors, generating sensor signals conveying occupancy-related features for an area. A controller uses the sensor signals to produce an occupancy estimate and to generate equipment-control signals to cause the HVAC system to supply conditioned air to the area based on the occupancy estimate. The controller includes fusion systems collectively generating the occupancy estimate by corresponding fusion calculations, the fusion systems producing a boundary occupancy-count change based on sensor signals from the boundary sensors, an interior occupancy count based on sensor signals from the interior sensors, and the overall occupancy estimate. Fusion may be of one or multiple types including cross-modality fusion across different sensor types, within-modality fusion across different instances of same-type sensors, and cross-algorithm fusion using different algorithms for the same sensor(s).

Konrad, Janusz L.↗

DOE OSTI2025

Descriptor: Infrastructure Perception and Control: Multi-Sensor Object Tracking Dataset (IPC-MSOT)

Traffic intersections are crucial and challenging nodes in transportation networks where multiple lanes of vehicles and pedestrians converge. Traffic accidents often occur at traffic intersections, including a large proportion of traffic fatalities and about one-half of all traffic injuries in the United States. Object detection data were collected in 2024 across three intersections in Colorado Springs, CO, USA, over the course of multiple days and various times to induce a heterogeneous mix of traffic conditions and behaviors. The purpose of the data collection exercises was to learn various attributes about infrastructure sensors and to build a repository of high-resolution, object-level data that can be used for research and development (e.g., to develop multisensor data fusion algorithms). The Infrastructure Perception and Control:Multi-Sensor Object tracking (IPC-MSOT) dataset was collected as part of the U.S. Department of Transportation's Strengthening Mobility and Revolutionizing Transportation (SMART) project, where the city of Colorado Springs, Colorado, and the National Renewable Energy Laboratory collaborated to collect object-level trajectory data from road users using multiple types of infrastructure sensors deployed at different intersections. This dataset allows for testing of late-stage sensor fusion algorithms and their ability to ingest multimodal sensor data, and it can be utilized by traffic engineers to design and evaluate trajectory-based signal control strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Low power and privacy preserving sensor platform for occupancy detection

A low-cost, low-power, stand-alone sensor platform having a visible-range camera sensor, a thermopile array, a microphone, a motion sensor, and a microprocessor that is configured to perform occupancy detection and counting while preserving the privacy of occupants. The platform is programmed to extract shape/texture from images in spatial domain; motion from video in time domain; and audio features in frequency domain. Embedded binarized neural networks are used for efficient object of interest detection. The platform is also programmed with advanced fusion algorithms for multiple sensor modalities addressing dependent sensor observations. The platform may be deployed for (i) residential use in detecting occupants for autonomously controlling building systems, such as HVAC and lighting systems, to provide energy savings, (ii) security and surveillance, such as to detect loitering and surveil places of interest, (iii) analyzing customer behavior and flows, (iv) identifying high performing stores by retailers.

Velipasalar, Senem↗

NASA NTRS1987

Orbital navigation, docking and obstacle avoidance as a form of three dimensional model-based image understanding

Range imagery from a laser scanner can be used to provide sufficient information for docking and obstacle avoidance procedures to be performed automatically. Three dimensional model-based computer vision algorithms in development can perform these tasks even with targets which may not be cooperative (that is, objects without special targets or markers to provide unambiguous location points). Roll, pitch and yaw of the vehicle can be taken into account as image scanning takes place, so that these can be corrected when the image is converted from egocentric to world coordinates. Other attributes of the sensor, such as the registered reflectence and texture channels, provide additional data sources for algorithm robustness. Temporal fusion of sensor immages can take place in the work coordinate domain, allowing for the building of complex maps in three dimensional space.

Beyer, J.↗

NASA NTRS1992

Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES, AVHRR, and SSM/I sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

Savage, Richard C.↗

NASA NTRS1993

Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer), and SSM/I (Special Sensor Microwave Imager) sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS (Earth Observation SystemData/Information System) prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

Savage, Richard C.↗

NASA NTRS1989

Design of an auto change mechanism and intelligent gripper for the space station

Robot gripping of objects in space is inherently demanding and dangerous and nowhere is this more clearly reflected than in the design of the robot gripper. An object which escapes the gripper in a micro g environment is launched not dropped. To prevent this, the gripper must have sensors and signal processing to determine that the object is properly grasped, e.g., grip points and gripping forces and, if not, to provide information to the robot to enable closed loop corrections to be made. The sensors and sensor strategies employed in the NASA/GSFC Split-Rail Parallel Gripper are described. Objectives and requirements are given followed by the design of the sensor suite, sensor fusion techniques and supporting algorithms.

Dehoff, Paul H.↗