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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 55 records · Page 3

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NASA NTRS2021

Dual Quaternion Visual Servo Control

This paper focuses on a dual quaternion-based estimation and control approach for position-based visual servoing (PBVS). The pose estimation of the camera is achieved using a dual quaternion-based Extended Kalman Filter (EKF), which estimates the position and orientation of the camera based on feature points acquired through a sequence of camera images. Based on the estimation, a dual quaternion control law is developed to regulate the camera to the desired pose. Leveraging the local exponential stability of the EKF and the global exponential stability of the designed controller, a nonlinear separation principle is used to prove the stability of the joint estimation and control for PBVS. The method is distinguished from other PBVS methods in the sense that a compact representation of dual quaternion is used to represent the pose, and a joint stability of estimator and controller for PBVS in dual quaternion space is presented. The proposed dual quaternion PBVS method is validated using a simulation.

Quaternions↗

NASA NTRS1994

Design and control of active vision based mechanisms for intelligent robots

In this paper, we propose a design of an active vision system for intelligent robot application purposes. The system has the degrees of freedom of pan, tilt, vergence, camera height adjustment, and baseline adjustment with a hierarchical control system structure. Based on this vision system, we discuss two problems involved in the binocular gaze stabilization process: fixation point selection and vergence disparity extraction. A hierarchical approach to determining point of fixation from potential gaze targets using evaluation function representing human visual behavior to outside stimuli is suggested. We also characterize different visual tasks in two cameras for vergence control purposes, and a phase-based method based on binarized images to extract vergence disparity for vergence control is presented. A control algorithm for vergence control is discussed.

Wu, Liwei↗

NASA NTRS2017

Mission Use of the SpaceCube Hybrid Data Processing System

The award-winning SpaceCube v2.0 system is a high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. This presentation provides an overview of the design architecture, flexibility, and the advantages of the modular SpaceCube v2.0 high performance data processing system for space applications. The current state of the proven SpaceCube technology is based on 11 years of engineering and operations. Eight systems have been successfully operated in space starting in 2008 with eight more to be delivered for payload integration in 2018 in support of various missions. This presentation will highlight how this multipurpose system is currently being used to solve design challenges of a variety of independent applications. The SpaceCube hardware adapts to new system requirements by allowing for application-unique interface cards that are utilized by reconfiguring the underlying programmable elements on the core processor card. We will show how this system is being used to improve on a heritage NASA GPS technology, enable a cutting-edge LiDAR instrument, and serve as a typical command and data handling (CDH) computer for a space robotics technology demonstration.Finally, this presentation will highlight the use of the SpaceCube v2.0 system on the Restore-L robotic satellite servicing mission. SpaceCube v2.0 is the central avionics responsible for the real-time vision system and autonomous robotic control necessary to find, capture, and service a national asset weather satellite.

Petrick, Dave↗

DOE OSTI2026

A Smart Vision-Aided RICH (Robotic Interface Control and Handling) System for VULCAN

High-flux neutron beams and high-efficiency detectors enable rapid neutron diffraction measurements at the Engineering Materials Diffractometer (VULCAN) at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory (ORNL). To optimize beam time utilization, efficient sample exchange, alignment, and automated measurements are essential. Recent advances in artificial intelligence (AI) have expanded the capabilities of robotic systems. Here, we report the development of a Robotic Interactive Control and Handling (RICH) system for sample handling at VULCAN, designed to support high-throughput experiments and reduce overhead time. The RICH system employs a six-axis desktop robot integrated with AI-based computer vision models capable of recognizing and localizing samples in real time from instrument and depth-resolving cameras. Vision algorithms combine these detections to align samples with designated measurement positions or place them within complex sample environments such as furnaces. This integration of machine learning-assisted vision with robotic handling demonstrates the feasibility of autonomous sample detection and preparation, offering a pathway toward fully unmanned neutron scattering experiments.

automation↗

NASA NTRS1995

Investigation of registration algorithms for the automatic tile processing system

The Robotic Tile Inspection System (RTPS), under development in NASA-KSC, is expected to automate the processes of post-flight re-water-proofing and the process of inspection of the Shuttle heat absorbing tiles. An important task of the robot vision sub-system is to register the 'real-world' coordinates with the coordinates of the robot model of the Shuttle tiles. The model coordinates relate to a tile data-base and pre-flight tile-images. In the registration process, current (post-flight) images are aligned with pre-flight images to detect the rotation and translation displacement required for the coordinate systems rectification. The research activities performed this summer included study and evaluation of the registration algorithm that is currently implemented by the RTPS, as well as, investigation of the utility of other registration algorithms. It has been found that the current algorithm is not robust enough. This algorithm has a success rate of less than 80% and is, therefore, not suitable for complying with the requirements of the RTPS. Modifications to the current algorithm has been developed and tested. These modifications can improve the performance of the registration algorithm in a significant way. However, this improvement is not sufficient to satisfy system requirements. A new algorithm for registration has been developed and tested. This algorithm presented very high degree of robustness with success rate of 96%.

Tamir, Dan E.↗

NASA NTRS1981

Laser electro-optic system for rapid three-dimensional /3-D/ topographic mapping of surfaces

It is pointed out that the generic utility of a robot in a factory/assembly environment could be substantially enhanced by providing a vision capability to the robot. A standard videocamera for robot vision provides a two-dimensional image which contains insufficient information for a detailed three-dimensional reconstruction of an object. Approaches which supply the additional information needed for the three-dimensional mapping of objects with complex surface shapes are briefly considered and a description is presented of a laser-based system which can provide three-dimensional vision to a robot. The system consists of a laser beam array generator, an optical image recorder, and software for controlling the required operations. The projection of a laser beam array onto a surface produces a dot pattern image which is viewed from one or more suitable perspectives. Attention is given to the mathematical method employed, the space coding technique, the approaches used for obtaining the transformation parameters, the optics for laser beam array generation, the hardware for beam array coding, and aspects of image acquisition.

Altschuler, M. D.↗

NASA NTRS2012

Real-time Accurate Surface Reconstruction Pipeline for Vision Guided Planetary Exploration Using Unmanned Ground and Aerial Vehicles

This report discusses work completed over the summer at the Jet Propulsion Laboratory (JPL), California Institute of Technology. A system is presented to guide ground or aerial unmanned robots using computer vision. The system performs accurate camera calibration, camera pose refinement and surface extraction from images collected by a camera mounted on the vehicle. The application motivating the research is planetary exploration and the vehicles are typically rovers or unmanned aerial vehicles. The information extracted from imagery is used primarily for navigation, as robot location is the same as the camera location and the surfaces represent the terrain that rovers traverse. The processed information must be very accurate and acquired very fast in order to be useful in practice. The main challenge being addressed by this project is to achieve high estimation accuracy and high computation speed simultaneously, a difficult task due to many technical reasons.

computer vision↗

NASA NTRS2002

Intellectual Dummies

Goddard Space Flight Center and Triangle Research & Development Corporation collaborated to create "Smart Eyes," a charge coupled device camera that, for the first time, could read and measure bar codes without the use of lasers. The camera operated in conjunction with software and algorithms created by Goddard and Triangle R&D that could track bar code position and direction with speed and precision, as well as with software that could control robotic actions based on vision system input. This accomplishment was intended for robotic assembly of the International Space Station, helping NASA to increase production while using less manpower. After successfully completing the two- phase SBIR project with Goddard, Triangle R&D was awarded a separate contract from the U.S. Department of Transportation (DOT), which was interested in using the newly developed NASA camera technology to heighten automotive safety standards. In 1990, Triangle R&D and the DOT developed a mask made from a synthetic, plastic skin covering to measure facial lacerations resulting from automobile accidents. By pairing NASA's camera technology with Triangle R&D's and the DOT's newly developed mask, a system that could provide repeatable, computerized evaluations of laceration injury was born.

Source record↗

DOE OSTI2025

Automating Testing of DUNE Electronics via a Finite State Machine

The Deep Underground Neutrino Experiment (DUNE) is a flagship international collaboration designed to study neutrinos tiny, nearly massless particles that may hold answers to fundamental questions about the Universe. Fermilab s Robotic Test Stand (RTS) plays a critical role in ensuring the quality of approximately 50,000 Application-Specific Integrated Circuit (ASIC) chips that will be used in DUNE s massive liquid argon detectors. These electronics will be inside the cryostat; therefore, they will need to have a high yield of working chips and low noise. To improve the automation and reliability of the RTS, this project focused on designing and implementing a Python-based finite state machine (FSM) to manage chip handling workflows. The FSM was developed as a modular software framework to coordinate robotic arm movements, manage chip tray positions, and monitor system states during testing. Key features include robust error handling routines, a pause/resume system for safe mid-cycle interruptions, and a simulation mode for iterative testing without hardware dependencies. The system was designed to prepare for seamless integration with RTS hardware components such as the robotic arm and vision system. This integration will streamline collaboration and enable efficient deployment of updates across the six total institutions performing testing. The outcomes of this internship contribute to Fermilab s mission to advance high-energy physics and support the DOE s national goals by directly improving the testing of equipment to be used in DUNE. The project also provided valuable experience in software design and contributing to the success of DUNE.

Kang, Caleb [William Rainey Harper Coll.]↗

DOE OSTI2025

Automating Testing of DUNE Electronics via a Finite State Machine

The Deep Underground Neutrino Experiment (DUNE) is a flagship international collaboration designed to study neutrinos—tiny, nearly massless particles that may hold answers to fundamental questions about the Universe. Fermilab’s Robotic Test Stand (RTS) plays a critical role in ensuring the quality of approximately 50,000 Application-Specific Integrated Circuit (ASIC) chips that will be used in DUNE’s massive liquid argon detectors. These electronics will be inside the cryostat; therefore, they will need to have a high yield of working chips and low noise. To improve the automation and reliability of the RTS, this project focused on designing and implementing a Python-based finite state machine (FSM) to manage chip handling workflows. The FSM was developed as a modular software framework to coordinate robotic arm movements, manage chip tray positions, and monitor system states during testing. Key features include robust error handling routines, a pause/resume system for safe mid-cycle interruptions, and a simulation mode for iterative testing without hardware dependencies. The system was designed to prepare for seamless integration with RTS hardware components such as the robotic arm and vision system. This integration will streamline collaboration and enable efficient deployment of updates across the six institutions performing testing. The outcomes of this internship contribute to Fermilab’s mission to advance high-energy physics and support the DOE’s national goals by directly improving the testing of equipment to be used in DUNE. The project also provided valuable experience in software design and contributing to the success of DUNE.

Kang, Caleb [Fermilab]↗

NASA NTRS1992

Algorithm For Simplified Robotic Tracking Of Weld Seams

Algorithm computes small cross-seam corrections to programmed path of welding robot. Intended for use with add-on vision system loosely coupled to robot, transmitting small amount of information about weld seam ahead of torch. Position of welding torch in reference frame of moving window estimated on basis of data on weld seam and speed of torch. Does not need data on position of torch, and does not transform data on seam to another reference frame.

Gutow, David A.↗

NASA NTRS1991

A cost-effective intelligent robotic system with dual-arm dexterous coordination and real-time vision

Dexterous coordination of manipulators based on the use of redundant degrees of freedom, multiple sensors, and built-in robot intelligence represents a critical breakthrough in development of advanced manufacturing technology. A cost-effective approach for achieving this new generation of robotics has been made possible by the unprecedented growth of the latest microcomputer and network systems. The resulting flexible automation offers the opportunity to improve the product quality, increase the reliability of the manufacturing process, and augment the production procedures for optimizing the utilization of the robotic system. Moreover, the Advanced Robotic System (ARS) is modular in design and can be upgraded by closely following technological advancements as they occur in various fields. This approach to manufacturing automation enhances the financial justification and ensures the long-term profitability and most efficient implementation of robotic technology. The new system also addresses a broad spectrum of manufacturing demand and has the potential to address both complex jobs as well as highly labor-intensive tasks. The ARS prototype employs the decomposed optimization technique in spatial planning. This technique is implemented to the framework of the sensor-actuator network to establish the general-purpose geometric reasoning system. The development computer system is a multiple microcomputer network system, which provides the architecture for executing the modular network computing algorithms. The knowledge-based approach used in both the robot vision subsystem and the manipulation control subsystems results in the real-time image processing vision-based capability. The vision-based task environment analysis capability and the responsive motion capability are under the command of the local intelligence centers. An array of ultrasonic, proximity, and optoelectronic sensors is used for path planning. The ARS currently has 18 degrees of freedom made up by two articulated arms, one movable robot head, and two charged coupled device (CCD) cameras for producing the stereoscopic views, and articulated cylindrical-type lower body, and an optional mobile base. A functional prototype is demonstrated.

Marzwell, Neville I.↗

NASA NTRS1986

Fundamentals and advances in the development of remote welding fabrication systems

Operational and man-machine issues for welding underwater, in outer space, and at other remote sites are investigated, and recent process developments are described. Probable remote welding missions are classified, and the essential characteristics of fundamental remote welding tasks are analyzed. Various possible operational modes for remote welding fabrication are identified, and appropriate roles for humans and machines are suggested. Human operator performance in remote welding fabrication tasks is discussed, and recent advances in the development of remote welding systems are described, including packaged welding systems, stud welding systems, remotely operated welding systems, and vision-aided remote robotic welding and autonomous welding systems.

Agapakis, J. E.↗

NASA NTRS1993

Self-organization via active exploration in robotic applications. Phase 2: Hybrid hardware prototype

In many environments human-like intelligent behavior is required from robots to assist and/or replace human operators. The purpose of these robots is to reduce human time and effort in various tasks. Thus the robot should be robust and as autonomous as possible in order to eliminate or to keep to a strict minimum its maintenance and external control. Such requirements lead to the following properties: fault tolerance, self organization, and intelligence. A good insight into implementing these properties in a robot can be gained by considering human behavior. In the first phase of this project, a neural network architecture was developed that captures some fundamental aspects of human categorization, habit, novelty, and reinforcement behavior. The model, called FRONTAL, is a 'cognitive unit' regulating the exploratory behavior of the robot. In the second phase of the project, FRONTAL was interfaced with an off-the-shelf robotic arm and a real-time vision system. The components of this robotic system, a review of FRONTAL, and simulation studies are presented in this report.

Oegmen, Haluk↗

NASA NTRS1973

Robot Vision

The operation of a system is described that is built both to model the vision of primate animals, including man, and serve as a pre-prototype of possible object recognition system. It was employed in a series of experiments to determine the practicability of matching left and right images of a scene to determine the range and form of objects. The experiments started with computer generated random-dot stereograms as inputs and progressed through random square stereograms to a real scene. The major problems were the elimination of spurious matches, between the left and right views, and the interpretation of ambiguous regions, on the left side of an object that can be viewed only by the left camera, and on the right side of an object that can be viewed only by the right camera.

Sutro, L. L.↗

NASA NTRS1985

Laser Rangefinder and Remote Profilometer

Proposed laser rangefinder and profilometer operates with precision of about 1mm at ranges of up to 100m. With scanning optics, device could track objects or accurately measure shapes of objects in field of view. New microprocessor-controlled design uses variable-length fiber-optic delay line as distance reference. New rangefinding method used in vision systems for industrial robots.

Mclauchlan, J. M.↗

NASA NTRS1987

Optical Welding Torch

Gas/tungsten-arc welding torch supports electrode at center while enabling viewing of weld area along torch axis. Gas torch accommodates lens and optical fibers, all part of vision system for welding robot. Welding torch includes spoked structure in central bore of optical body. Structure supports welding electrode, carries electric current to it, and takes heat away from it. Spokes formed by drilling six holes 60 degrees apart around center line of torch.

Richardson, R. W.↗

NASA NTRS1989

Knowledge-based machine vision systems for space station automation

Computer vision techniques which have the potential for use on the space station and related applications are assessed. A knowledge-based vision system (expert vision system) and the development of a demonstration system for it are described. This system implements some of the capabilities that would be necessary in a machine vision system for the robot arm of the laboratory module in the space station. A Perceptics 9200e image processor, on a host VAXstation, was used to develop the demonstration system. In order to use realistic test images, photographs of actual space shuttle simulator panels were used. The system's capabilities of scene identification and scene matching are discussed.

Ranganath, Heggere S.↗