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At least 253 records · Page 14

A contribution to laser range imaging technology

The goal of the project was to develop a methodology for fusion of a Laser Range Imaging Device (LRID) and camera data. Our initial work in the project led to the conclusion that none of the LRID's that were available were sufficiently adequate for this purpose. Thus we spent the time and effort on the development of the new LRID with several novel features which elicit the desired fusion objectives. In what follows, we describe the device developed and built under contract. The Laser Range Imaging Device (LRID) is an instrument which scans a scene using a laser and returns range and reflection intensity data. Such a system would be extremely useful in scene analysis in industry and space applications. The LRID will be eventually implemented on board a mobile robot. The current system has several advantages over some commercially available systems. One improvement is the use of X-Y galvonometer scanning mirrors instead of polygonal mirrors present in some systems. The advantage of the X-Y scanning mirrors is that the mirror system can be programmed to provide adjustable scanning regions. For each mirror there are two controls accessible by the computer. The first is the mirror position and the second is a zoom factor which modifies the amplitude of the position of the parameter. Another advantage of the LRID is the use of a visible low power laser. Some of the commercial systems use a higher intensity invisible laser which causes safety concerns. By using a low power visible laser, not only can one see the beam and avoid direct eye contact, but also the lower intensity reduces the risk of damage to the eye, and no protective eyeware is required.

Defigueiredo, Rui J. P.↗

Toward an IMU-based Space Suit Motion Capture System

Spacesuits are complex engineering systems that sustain human health and enable performance outside of Earth-like environments. These systems must support human mobility and physical workload demands while minimizing injury risk during extravehicular activity (EVA). Future EVA on the lunar surface during the Artemis program is expected to be more frequent and require higher physical workloads than previous EVAs during the ISS, Shuttle, or Apollo programs. Hence it is important to optimize future as well as current spacesuits to be efficient and comfortable for the success of space and planetary missions. To enable this, an efficient method is needed to test these spacesuits on the ground.When testing spacesuits in ground environments, it is often necessary to understand the kinematics of the suit to validate the design against relevant requirements or characterize the physical workload necessary to operate the suit. This is a challenging task for traditional optical motion capture (OMC) approaches: suit-mounted OMC markers are easily occluded by the subject or environment and may become detached during testing. Controlling lighting and reflectivity of objects in the motion capture volume is also difficult. Fixed-position OMC cameras also constrain testing to a small and contrived laboratory environment, disallowing kinematics capture in field environments.One promising alternative is the use of suit-mounted inertial measurement units (IMUs). These sensors are small, unobtrusive, and portable, but come at the cost of increased sensor noise and complexity of the software and mathematics to analyze the collected data. To this end, engineers at NASA are developing the Augmented Suit Inverse Kinematics (ASIK) system, a complete motion capture methodand inverse kinematics solver which relies solely on a network of wireless IMUs attached to the major kinematic segments of the spacesuit. The ASIK modeling language allows for the simple inclusion of probabilistic priors such as suit size and shape or IMU positions and rotations. Furthermore, to increase accuracy and reduce operational overhead to use this motion capture approach, the developed inverse kinematics solver exploits so-called self-calibratingalgorithmic techniques, which reduce the need for precise alignment of the sensors on the segments or scripted functional calibration procedures. The ASIK system was tested in a 7-subject pilot study. Each subject donned NASA’s new prototype exploration spacesuit in the Active Response Gravity Offload System (ARGOS) facility at the NASA Johnson Space Center. The subjects were outfitted with a set of 14 APDM (Portland, OR, USA) Opal IMUs, 12 of which were used in the ASIK model to estimate lower body and trunk kinematics. The subjects were also outfitted with a set of reflective OMC markers and traditional OMC data was collected and processed. Presented results will include characterization of ASIK-derived suit joint angles accuracy against an optical motion capture datum. Discussion of these results, as well as discussion of system calibration and nuances of mathematical observability, will be included.If successful, IMU-based motion capture will enable testing and validation of spacesuits more frequently, with less overhead, in more extreme environments. Future work will apply these techniques to common spacesuit testing tasks, such as gait, mobility, and balance assessment, physical workload characterization, and ergonomics evaluations.

Timothy Mcgrath↗

Adaptive Urban Traffic Signal Control for Multiple Intersections: An LQR Approach

Traffic congestion leads to severe problems especially in urban traffic networks. It increases the chance of accidents, energy waste, and social costs. In order to address these problems, an adaptive linear quadratic regulator (LQR) approach is developed for traffic signal control at multiple intersections in an urban area. The proposed method controls the green time of the traffic signals to reduce traffic congestion and smooth traffic flow. Real-world data from vision-based traffic sensors are used to build the traffic network model, which mimics the real-world traffic behavior. In addition, the proposed control utilizes recursive least square parameter estimation, which is capable of tracking dynamic changes in traffic conditions. Simulation of Urban MObility (SUMO) is used to analyze the efficacy of the proposed method. Results of the simulation show that the proposed method outperforms pretimed control in various aspects.

adaptive LQR control↗

Development of Field-Controlled Smart Optic Materials (ScN, AlN) with Rare Earth Dopants

The purpose of this investigation is to develop the fundamental materials and fabrication technology for field-controlled spectrally active optics that are essential for industry, NASA, and DOD applications such as: membrane optics, filters for LIDARs, windows for sensors, telescopes, spectroscopes, cameras, flat-panel displays, etc. ScN and AlN thin films were fabricated on c-axis Sapphire (0001) or quartz substrate with the RF and DC magnetron sputtering. The crystal structure of AlN in fcc (rocksalt) and hcp (wurtzite) were controlled. Advanced electrical characterizations were performed, including I-V and Hall Effect Measurement. ScN film has a free carrier density of 5.8 x 10(exp 20)/per cubic centimeter and a conductivity of 1.1 x 10(exp 3) per centimeter. The background ntype conductivity of as-grown ScN has enough free electrons that can readily interact with the photons. The high density of free electrons and relatively low mobility indicate that these films contain a high level of shallow donors as well as deep levels. Also, the UV-Vis spectrum of ScN and AlN thin films with rare earth elements (Er or Ho) were measured at room temperature. Their optical band gaps were estimated to be about 2.33eV and 2.24eV, respectively, which are obviously smaller than that of undoped thin film ScN (2.4eV). The red-shifted absorption onset gives direct evidence for the decrease of band gap (Eg) and the energy broadening of valence band states are attributable to the doping. As the doped elements enter the ScN crystal lattices, the localized band edge states form at the doped sites with a reduction of Eg. Using a variable angle spectroscopic ellipsometer, the decrease in refractive index with applied field is observed with a smaller shift in absorption coefficient.

Kim, Hyun-Jung↗

A Microphone Phased Array for Launch Acoustics Application

A new, portable, phased array of microphones is built at NASA Ames Research Center specifically for the harsh environment encountered in launch pads of rocket vehicles. It uses 70 piezoresistive, dynamic pressure sensors, optimally distributed on a 10.5ft diameter open frame dome structure. The open frame is light yet robust to sustain the high wind load of typical seaside launch pads, and the blast and acoustic loads from the launch. A 200-ft long cable bundle carries the microphone signals to a weather-protected cabinet containing the data systems, and allows for the placement of the array tall structures. The array is equipped with an infra-red camera and a visible wavelength camera for imaging the launch pad. The beamformed noise maps will be superimposed on the video footages collected by the cameras for correct identification of the noise sources. The array is tested with very loud speaker sources to determine the beamforming ability using different schemes, such as the conventional beamforming, orthogonal-functional beamforming, and spectral element methods. A comparative study was conducted to determine the minimum attainable spatial resolution. Data from a validation test in an outdoor setup, where the array was placed on a Telehandler at several different heights and distances from either a single or a pair of speakers, is presented in this paper. The final goal is to use the array during NASA’s Artemis-II launch to determine the distribution of noise sources on the Mobile Launcher.

Acoustics↗

Perception Testing in Fog for Autonomous Flight

As the path towards Urban Air Mobility (UAM) continues to take shape, there are outstanding technical challenges to achieving safe and effective air transportation operations under this new paradigm. To inform and guide technology development for UAM, NASA is investigating the current state-of-the-art in key technology areas including traffic management, detect-and-avoid, and autonomy. In support of this effort, a new perception testbed was developed at NASA Ames Research Center to collect data from an array of sensing systems representative of those that could be found on a future UAM vehicle. This testbed, featuring a Light-Detection-and-Ranging (LIDAR) instrument, a long-wave infrared sensor, and a visible spectrum camera was deployed for a multiday test campaign in the Fog Chamber at Sandia National Laboratories (SNL), in Albuquerque, New Mexico. During the test campaign, fog conditions were created for tests with targets including a human, a resolution chart, and a small unmanned aerial vehicle (sUAV). Here, this paper describes in detail, the developed perception testbed, the experimental setup in the fog chamber, the resulting data, and presents an initial result from analysis of the data with the evaluation of methods to increase contrast through filtering techniques.

aeronautics↗

Distributed Vision Sensing of Small Uncrewed Aircraft Systems in Urban Traffic Corridors

The NASA Advanced Air Mobility mission will enable widespread low altitude passenger travel, cargo delivery, and a variety of public services through the development of Uncrewed Aerial Systems (UAS) operations. Ensuring safe, autonomous operations in densely populated environments requires careful consideration towards hazards including other aircraft, infrastructure, and evolving weather. Small Uncrewed Aerial Systems (SUAS) present a unique hazard to UAS operations as they share airspace and may be readily operated in a non-cooperative fashion. This work investigates distributed sensing of SUAS traversing an air traffic corridor in an urban setting. This work develops a distributed vision detect and track strategy at NASA Langley Research Center. Three nodes, each with at least one global shutter camera, are distributed around a traffic corridor to surveil flight operations for two SUAS performing low altitude flight operations. Each node is equipped with a GPS and cellular modem to enable timestamping and remote control of acquisition. Node one faces a traffic roundabout with buildings in the background and achieves 99% surveillance coverage for two SUAS against building and tree backgrounds at ranges 50 to 130m. The second node points down Langley Boulevard with trees and buildings in the background and achieves 99% coverage at separation distances between 70 and 180m. The analysis for the second node is limited to ranges below 180m due to low contrast against dark, tree backgrounds. Finally, the third node points down Langley Boulevard from another perspective and achieves 99% coverage at ranges 60m to 200m against mostly building with a few sections of trees in the background.

Chester V Dolph↗

Robust, Flexible Motion Control for the Mars Explorer Rovers

The Mobility Flight Software, running on computers aboard the Mars Explorer Rover (MER) robotic vehicles Spirit and Opportunity, affords the robustness and flexibility of control to enable safe and effective operation of these vehicles in traversing natural terrain. It can make the vehicles perform specific maneuvers commanded from Earth, and/or can autonomously administer multiple aspects of mobility, including choice of motion, measurement of actual motion, and even selection of targets to be approached. Motion of a vehicle can be commanded by use of multiple layers of control, ranging from motor control at a low level, direct drive operations (e.g., motion along a circular arc, motion along a straight line, or turn in place) at an intermediate level to goal-position driving (that is, driving to a specified location) at a high level. The software can also perform high-level assessment of terrain and selection of safe paths across the terrain: this involves processing of the digital equivalent of a local traversability map generated from images acquired by stereoscopic pairs of cameras aboard the vehicles. Other functions of the software include interacting with the rest of the MER flight software and performing safety checks.

Maimone, Mark↗

Ground-Based Vision Tracker for Advanced Air Mobility and Urban Air Mobility

Advanced Air Mobility (AAM) Air Mobility and Urban Air Mobility (UAM) require aircraft surveillance and monitoring for safety and security. Persistent tracking of flying objects provides Air Traffic Control (ATC) and Air Traffic Management (ATM) continuous coverage and knowledge of the national airspace system (NAS). Given the significant disparity in the number of AAM and UAM aircraft compared to commercial aircraft in the NAS, coupled with the dense AAM/UAM operations in urban environments, employing the existing ATC/ATM architectures poses considerable challenges. A first step in creating a similar ATC/ATM architecture for AAM/UAM will require ground-based and airborne-based sensors to provide monitoring, which will be difficult in urban environments due to GPS degradation. This paper proposes a vision-based tracking method with static cameras by utilizing image subtraction and blob detection, which avoids adding additional electromagnetic interferences in the environment with sensors such as radar. The ground-based vision tracker (GBVT) outputs the detected objects' azimuth and elevation angles from unmanned aerial system (UAS) flight tests. Future and ongoing work includes sending the detected objects' azimuth and elevation angles as inputs for an extended Kalman filter (EKF) to estimate the position and velocity of the detected object.

distributed sensing↗

Rover Wheel-Actuated Tool Interface

A report describes an interface for utilizing some of the mobility features of a mobile robot for general-purpose manipulation of tools and other objects. The robot in question, now undergoing conceptual development for use on the Moon, is the All-Terrain Hex-Limbed Extra-Terrestrial Explorer (ATHLETE) rover, which is designed to roll over gentle terrain or walk over rough or steep terrain. Each leg of the robot is a six-degree-of-freedom general purpose manipulator tipped by a wheel with a motor drive. The tool interface includes a square cross-section peg, equivalent to a conventional socket-wrench drive, that rotates with the wheel. The tool interface also includes a clamp that holds a tool on the peg, and a pair of fold-out cameras that provides close-up stereoscopic images of the tool and its vicinity. The field of view of the imagers is actuated by the clamp mechanism and is specific to each tool. The motor drive can power any of a variety of tools, including rotating tools for helical fasteners, drills, and such clamping tools as pliers. With the addition of a flexible coupling, it could also power another tool or remote manipulator at a short distance. The socket drive can provide very high torque and power because it is driven by the wheel motor.

Matthews, Janet↗

IDEAS and App Development Internship in Hardware and Software Design

In this report, I will discuss the tasks and projects I have completed while working as an electrical engineering intern during the spring semester of 2016 at NASA Kennedy Space Center. In the field of software development, I completed tasks for the G-O Caching Mobile App and the Asbestos Management Information System (AMIS) Web App. The G-O Caching Mobile App was written in HTML, CSS, and JavaScript on the Cordova framework, while the AMIS Web App is written in HTML, CSS, JavaScript, and C# on the AngularJS framework. My goals and objectives on these two projects were to produce an app with an eye-catching and intuitive User Interface (UI), which will attract more employees to participate; to produce a fully-tested, fully functional app which supports workforce engagement and exploration; to produce a fully-tested, fully functional web app that assists technicians working in asbestos management. I also worked in hardware development on the Integrated Display and Environmental Awareness System (IDEAS) wearable technology project. My tasks on this project were focused in PCB design and camera integration. My goals and objectives for this project were to successfully integrate fully functioning custom hardware extenders on the wearable technology headset to minimize the size of hardware on the smart glasses headset for maximum user comfort; to successfully integrate fully functioning camera onto the headset. By the end of this semester, I was able to successfully develop four extender boards to minimize hardware on the headset, and assisted in integrating a fully-functioning camera into the system.

CSS↗

Reinforcement Learning-based Traffic Control to Optimize Energy Usage and Throughput (CRADA report)

The US roadways are critical to meeting the mobility and economic needs of the nation. The United States uses 28% of its energy in moving goods and people, with approximately 60% of that utilized by cars, light trucks, and motorcycles. Thus, improved transportation efficiency is vital to America’s economic progress. The increasing congestion and energy resource requirements of transportation systems for metropolitan areas require research in methods to improve and optimize control methods. Coordinating and optimizing traffic in urban areas may introduce hundreds of thousands of vehicles and traffic management systems, which can require high performance computing (HPC) resources to model and manage. In this work, we seek to use machine learning, computer vision, and HPC to improve the energy efficiency aspects of traffic control by leveraging GRIDSMART traffic cameras as sensors for adaptive traffic control, with a sensitivity to the fuel consumption characteristics of the traffic in the camera’s visual field. Traffic control use cases using reinforcement learning have been published and achieved good results. Surveys from DOE national laboratories estimate that the fuel cost of idling is 6 billion gallons wasted annually [Argonne National Laboratory, 2019]. GRIDSMART cameras—an existing, fielded commercial product—sense the presence of vehicles at intersections and replace more conventional sensors (such as inductive loops) to issue calls to traffic control. These cameras, which have horizon-to-horizon view, offer the potential for an improved view of the traffic environment which can be used to generate better control algorithms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Adaptive Multi-Sensor Localization Information Fusion for Autonomous Urban Air Mobility Operations

An adaptive method is developed to iteratively fuse the information provided by multiple sensors to enable autonomous urban air mobility type operations. First, noisy and bias corrupted IMU readings are processed as soon as they arrive using kinematic equations represented in the vehicle's body frame. To correct the systems drift resulting from the integration, an information content measure is introduced to decide on the environment. For the cluttered environment the information provided by environmental sensors is counted as reliable and the drift correction as accurate. For the open space, the GPS data is counted as reliable, and the drift correction is done based on the GPS readings. The measurement noise effects are minimize using Iterated Extended Kalman Filter framework. The algorithm is implemented in the in-house developed FlightDeckz simulation environment using an IMU model, simulated video recorded from a camera mounted on the vehicle (for the purpose of this study, outside scenery was generated with XPlane), which flies in an urban environment, and GPS data generated from the environment's digital map.

Onboard Perception↗

The ORNL Overhead Vehicle Dataset (OOVD)

Roadways are critical to meeting the mobility and economic needs of the nation. The United States uses 28% of its energy in moving goods and people, with approximately 60% of that utilized by cars, light trucks, and motorcycles. Thus, improved transportation efficiency is vital to America’s economic progress. The increasing congestion and energy resource requirements of transportation systems for metropolitan areas require research in methods to improve and optimize control methods. Coordinating and optimizing traffic in urban areas may introduce hundreds of thousands of vehicles and traffic management systems, which can require high performance computing (HPC) resources to model and manage. This data set was created to understand the potential for machine learning, computer vision, and HPC to improve the energy efficiency aspects of traffic control by leveraging GRIDSMART traffic cameras as sensors for adaptive traffic control, with a sensitivity to the fuel consumption characteristics of the traffic in the camera’s visual field. GRIDSMART cameras—an existing, fielded commercial product—sense the presence of vehicles at intersections and replace more conventional sensors (such as inductive loops) to issue calls to traffic control. These cameras, which have horizon-to-horizon view, offer the potential for an improved view of the traffic environment which can be used to generate better control algorithms.

Karnowski, Thomas P.↗

NASA Tech Briefs, June 2004

Topics covered include: COTS MEMS Flow-Measurement Probes; Measurement of an Evaporating Drop on a Reflective Substrate; Airplane Ice Detector Based on a Microwave Transmission Line; Microwave/Sonic Apparatus Measures Flow and Density in Pipe; Reducing Errors by Use of Redundancy in Gravity Measurements; Membrane-Based Water Evaporator for a Space Suit; Compact Microscope Imaging System with Intelligent Controls; Chirped-Superlattice, Blocked-Intersubband QWIP; Charge-Dissipative Electrical Cables; Deep-Sea Video Cameras Without Pressure Housings; RFID and Memory Devices Fabricated Integrally on Substrates; Analyzing Dynamics of Cooperating Spacecraft; Spacecraft Attitude Maneuver Planning Using Genetic Algorithms; Forensic Analysis of Compromised Computers; Document Concurrence System; Managing an Archive of Images; MPT Prediction of Aircraft-Engine Fan Noise; Improving Control of Two Motor Controllers; Electro-deionization Using Micro-separated Bipolar Membranes; Safer Electrolytes for Lithium-Ion Cells; Rotating Reverse-Osmosis for Water Purification; Making Precise Resonators for Mesoscale Vibratory Gyroscopes; Robotic End Effectors for Hard-Rock Climbing; Improved Nutation Damper for a Spin-Stabilized Spacecraft; Exhaust Nozzle for a Multitube Detonative Combustion Engine; Arc-Second Pointer for Balloon-Borne Astronomical Instrument; Compact, Automated Centrifugal Slide-Staining System; Two-Armed, Mobile, Sensate Research Robot; Compensating for Effects of Humidity on Electronic Noses; Brush/Fin Thermal Interfaces; Multispectral Scanner for Monitoring Plants; Coding for Communication Channels with Dead-Time Constraints; System for Better Spacing of Airplanes En Route; Algorithm for Training a Recurrent Multilayer Perceptron; Orbiter Interface Unit and Early Communication System; White-Light Nulling Interferometers for Detecting Planets; and Development of Methodology for Programming Autonomous Agents.

Source record↗

xEMU Spacesuit Boot Lunar South Pole Thermal Vacuum Testing

The Exploration Extravehicular Mobility Unit (xEMU) spacesuit lunar boot was evaluated in the Jet Propulsion Lab (JPL) CITADEL thermal vacuum chamber at lunar South Pole conditions. The JPL CITADEL chamber provides a radiation environment and contact plate temperature of 48K, simulating the temperature of a lunar Permanently Shadowed Region (PSR) at the South Pole of the Moon. The main objectives of the test series were: to evaluate the risk lunar PSRs pose to advanced spacesuit boots, validate the xEMU lunar boot thermal model, and develop a test methodology to evaluate lunar spacesuit boots. To simulate the thermal effects of a crewmember’s foot inside the boot, a thermal manikin foot was developed to inject heat into the spacesuit boot. Thermal data was collected through a variety of sensors including thermocouples, thermistors, heat flux sensors, and infrared cameras. A test matrix was developed to investigate the variables of foot contact force, simulated skin temperature, external contact plate temperature, and ventilation flowrate. The JPL CITADEL chamber includes a loadlock (airlock) that afforded the ability to simulate the transition of the boot from a thermally neutral IVA condition to a cold EVA condition within seconds. This paper will document the test design, test objectives, success criteria, test support equipment, spacesuit boot to chamber interfaces, and configuration of the test article. Additionally, this paper will document the high-level results of the testing. More detailed test results will be presented in a different paper.

TVAC↗

xEMU Spacesuit Boot Lunar South Pole Thermal Vacuum Testing

The Exploration Extravehicular Mobility Unit (xEMU) spacesuit lunar boot was evaluated in the Jet Propulsion Lab (JPL) CITADEL thermal vacuum chamber at lunar South Pole conditions. The JPL CITADEL chamber provides a radiation environment and contact plate temperature of 48K, simulating the temperature of a lunar Permanently Shadowed Region (PSR) at the South Pole of the Moon. The main objectives of the test series are: to evaluate the risk lunar PSRs pose to advanced spacesuit boots, validate the xEMU lunar boot thermal model, and to develop a test methodology to evaluate lunar spacesuit boots. To simulate the thermal effects of a crewmember’s foot inside the boot, a thermal manikin foot was developed to inject heat into the spacesuit boot. Thermal data was collected through a variety of sensors including thermocouples, thermistors, heat flux sensors, and infrared cameras. A test matrix was developed to investigate the variables of foot contact force, simulated skin temperature, external contact plate temperature, and ventilation flowrate. The JPL CITADEL chamber includes a loadlock (airlock) that afforded the ability to simulate the transition of the boot from a thermally neutral IVA condition to a cold EVA condition within seconds. This paper will document the test design, test objectives, success criteria, test support equipment, spacesuit boot to chamber interfaces, and configuration of the test article. Additionally, this paper will document the high-level results of the testing. More detailed test results will be presented in a different paper.

Ben Swartout↗

Measurement of Visual Reaction Times Using Hand-held Mobile Devices

Modern mobile devices provide a convenient platform for collecting research data in the field. But,because the working of these devices is often cloaked behind multiple layers of proprietary system software, it can bedifficult to assess the accuracy of the data they produce, particularly in the case of timing. We have been collecting datain a simple visual reaction time experiment, as part of a fatigue testing protocol known as the Psychomotor Vigilance Test (PVT). In this protocol, subjects run a 5-minute block consisting of a sequence of trials in which a visual stimulus appears after an unpredictable variable delay. The subject is required to tap the screen as soon as possible after the appearance of the stimulus. In order to validate the reaction times reported by our program, we had subjects perform the task while a high-speed video camera recorded both the display screen, and a side view of the finger (observed in a mirror). Simple image-processing methods were applied to determine the frames in which the stimulus appeared and disappeared, and in which the finger made and broke contact with the screen. The results demonstrate a systematic delay between the initial contact by the finger and the detection of the touch by the software, having a value of 80 +- 20 milliseconds.

reaction time↗