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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Low computation vision-based navigation for a Martian rover

Construction and design details of the Mobot Vision System, a small, self-contained, mobile vision system, are presented. This system uses the view from the top of a small, roving, robotic vehicle to supply data that is processed in real-time to safely navigate the surface of Mars. A simple, low-computation algorithm for constructing a 3-D navigational map of the Martian environment to be used by the rover is discussed.

Gavin, Andrew S.↗
NASA NTRS1990

Vision-based planetary rover navigation

NASA and JPL have developed a testbed 'planetary rover' vehicle with sufficient power supplies, sensors, and computational resources for the demonstration of semiautonomous navigation. Attention is presently given to this vehicle's vision-based navigation techniques. The proposed design and its variants allow advantage to be taken of enormous quantities of both spatial and temporal information that are normally wasted, by sampling very fine detail over the full focal plane area to precisely determine those parts of the image that are accurately at the focus range of the pinhole array used. This should generate accurate and reliable real-time range information in a wide variety of natural scenes, with little or no computation.

Wilcox, Brian H.↗
NASA NTRS2005

Micro-Inspector Spacecraft for Space Exploration Missions

NASA is seeking to embark on a new set of human and robotic exploration missions back to the Moon, to Mars, and destinations beyond. Key strategic technical challenges will need to be addressed to realize this new vision for space exploration, including improvements in safety and reliability to improve robustness of space operations. Under sponsorship by NASA's Exploration Systems Mission, the Jet Propulsion Laboratory (JPL), together with its partners in government (NASA Johnson Space Center) and industry (Boeing, Vacco Industries, Ashwin-Ushas Inc.) is developing an ultra-low mass (<3.0 kg) free-flying micro-inspector spacecraft in an effort to enhance safety and reduce risk in future human and exploration missions. The micro-inspector will provide remote vehicle inspections to ensure safety and reliability, or to provide monitoring of in-space assembly. The micro-inspector spacecraft represents an inherently modular system addition that can improve safety and support multiple host vehicles in multiple applications. On human missions, it may help extend the reach of human explorers, decreasing human EVA time to reduce mission cost and risk. The micro-inspector development is the continuation of an effort begun under NASA's Office of Aerospace Technology Enabling Concepts and Technology (ECT) program. The micro-inspector uses miniaturized celestial sensors; relies on a combination of solar power and batteries (allowing for unlimited operation in the sun and up to 4 hours in the shade); utilizes a low-pressure, low-leakage liquid butane propellant system for added safety; and includes multi-functional structure for high system-level integration and miniaturization. Versions of this system to be designed and developed under the H&RT program will include additional capabilities for on-board, vision-based navigation, spacecraft inspection, and collision avoidance, and will be demonstrated in a ground-based, space-related environment. These features make the micro-inspector design unique in its ability to serve crewed as well as robotic spacecraft, well beyond Earth-orbit and into arenas such as robotic missions, where human teleoperation capability is not locally available.

microspacecraft↗
NASA NTRS1991

Experiments in teleoperator and autonomous control of space robotic vehicles

A program of research embracing teleoperator and automatic navigational control of freely flying satellite robots is presented. Current research goals include: (1) developing visual operator interfaces for improved vehicle teleoperation; (2) determining the effects of different visual interface system designs on operator performance; and (3) achieving autonomous vision-based vehicle navigation and control. This research program combines virtual-environment teleoperation studies and neutral-buoyancy experiments using a space-robot simulator vehicle currently under development. Visual-interface design options under investigation include monoscopic versus stereoscopic displays and cameras, helmet-mounted versus panel-mounted display monitors, head-tracking versus fixed or manually steerable remote cameras, and the provision of vehicle-fixed visual cues, or markers, in the remote scene for improved sensing of vehicle position, orientation, and motion.

Alexander, Harold L.↗
NASA NTRS1985

Computers in Aerospace Conference, 5th, Long Beach, CA, October 21-23, 1985, Technical Papers

Among the topics discussed are: access control models for a distributed CAIS-conforming system; a knowledge-based advisory system for casualty procedures; and automated interactive simulation modeling system. Consideration is also given to: reusable software concepts and software development methodologies; the electronic device aspects of neutral network memories; an expert system for automated satellite anomaly resolution; and the use of automatic programming techniques for fault-tolerant computing systems. Among additional topics discussed are: systems approaches to software fault tolerance; a Space Shuttle navigation validation system; and a vision-based road following system for an autonomous land vehicle.

Source record↗
NASA NTRS2004

An Integrated Vision-Based System for Spacecraft Attitude and Topology Determination for Formation Flight Missions

With the space industry's increasing focus upon multi-spacecraft formation flight missions, the ability to precisely determine system topology and the orientation of member spacecraft relative to both inertial space and each other is becoming a critical design requirement. Topology determination in satellite systems has traditionally made use of GPS or ground uplink position data for low Earth orbits, or, alternatively, inter-satellite ranging between all formation pairs. While these techniques work, they are not ideal for extension to interplanetary missions or to large fleets of decentralized, mixed-function spacecraft. The Vision-Based Attitude and Formation Determination System (VBAFDS) represents a novel solution to both the navigation and topology determination problems with an integrated approach that combines a miniature star tracker with a suite of robust processing algorithms. By combining a single range measurement with vision data to resolve complete system topology, the VBAFDS design represents a simple, resource-efficient solution that is not constrained to certain Earth orbits or formation geometries. In this paper, analysis and design of the VBAFDS integrated guidance, navigation and control (GN&C) technology will be discussed, including hardware requirements, algorithm development, and simulation results in the context of potential mission applications.

Rogers, Aaron↗
NASA NTRS1997

Initial Results from Vision-based Control of the Marsokhod Rover

A geologist characterizing a field site typically wanders from one interesting geologic feature to another. Performing geology remotely with a mobile robot, we have observed the same behavior: geologists see a visually-interesting feature and wish to approach it for closer inspection. To date, navigating a mobile robot to a visually-interesting feature has been accomplished by driving to a location close to the feature. This introduces two problems: assigning a location to the feature and navigating the rover to that location. In practice, solutions to both of these problems are susceptable to positional error. Fundamentally, we can see where we want the robot to go, but it is difficult to precisely quantify where either the target or the robot are located. The development of vision-based control of robot manipulators suggests an alternative approach for mobile robot explorers. We have developed a vision-based control system that enables the Marsokhod rover to drive to within sampling distance of visually-designated rock or natural feature. We will describe this system and our initial results using it during a field experiment in the Painted Desert of Arizona.

Wettergreen, David↗
NASA NTRS1994

Perception for mobile robot navigation: A survey of the state of the art

In order for mobile robots to navigate safely in unmapped and dynamic environments they must perceive their environment and decide on actions based on those perceptions. There are many different sensing modalities that can be used for mobile robot perception; the two most popular are ultrasonic sonar sensors and vision sensors. This paper examines the state-of-the-art in sensory-based mobile robot navigation. The first issue in mobile robot navigation is safety. This paper summarizes several competing sonar-based obstacle avoidance techniques and compares them. Another issue in mobile robot navigation is determining the robot's position and orientation (sometimes called the robot's pose) in the environment. This paper examines several different classes of vision-based approaches to pose determination. One class of approaches uses detailed, a prior models of the robot's environment. Another class of approaches triangulates using fixed, artificial landmarks. A third class of approaches builds maps using natural landmarks. Example implementations from each of these three classes are described and compared. Finally, the paper presents a completely implemented mobile robot system that integrates sonar-based obstacle avoidance with vision-based pose determination to perform a simple task.

Kortenkamp, David↗
NASA NTRS1992

A rotorcraft flight database for validation of vision-based ranging algorithms

A helicopter flight test experiment was conducted at the NASA Ames Research Center to obtain a database consisting of video imagery and accurate measurements of camera motion, camera calibration parameters, and true range information. The database was developed to allow verification of monocular passive range estimation algorithms for use in the autonomous navigation of rotorcraft during low altitude flight. The helicopter flight experiment is briefly described. Four data sets representative of the different helicopter maneuvers and the visual scenery encountered during the flight test are presented. These data sets will be made available to researchers in the computer vision community.

Smith, Phillip N.↗
NASA NTRS1992

Achieving safe autonomous landings on Mars using vision-based approaches

Autonomous landing capabilities will be critical to the success of planetary exploration missions, and in particular to the exploration of Mars. Past studies have indicated that the probability of failure associated with open-loop landings is unacceptably high. Two approaches to achieving autonomous landings with higher probabilities of success are currently under analysis. If a landing site has been certified as hazard free, then navigational aids can be used to facilitate a precision landing. When only limited surface knowledge is available and landing areas cannot be certified as hazard free, then a hazard detection and avoidance approach can be used, in which the vehicle selects hazard free landing sites in real-time during its descent. Issues pertinent to both approaches, including sensors and algorithms, are presented. Preliminary results indicate that one promising approach to achieving high accuracy precision landing is to correlate optical images of the terrain acquired during the terminal descent phase with a reference image. For hazard detection scenarios, a sensor suite comprised of a passive intensity sensor and a laser ranging sensor appears promising as a means of achieving robust landings.

Pien, Homer↗
NASA NTRS2011

Autonomous Landing and Ingress of Micro-Air-Vehicles in Urban Environments Based on Monocular Vision

Unmanned micro air vehicles (MAVs) will play an important role in future reconnaissance and search and rescue applications. In order to conduct persistent surveillance and to conserve energy, MAVs need the ability to land, and they need the ability to enter (ingress) buildings and other structures to conduct reconnaissance. To be safe and practical under a wide range of environmental conditions, landing and ingress maneuvers must be autonomous, using real-time, onboard sensor feedback. To address these key behaviors, we present a novel method for vision-based autonomous MAV landing and ingress using a single camera for two urban scenarios: landing on an elevated surface, representative of a rooftop, and ingress through a rectangular opening, representative of a door or window. Real-world scenarios will not include special navigation markers, so we rely on tracking arbitrary scene features; however, we do currently exploit planarity of the scene. Our vision system uses a planar homography decomposition to detect navigation targets and to produce approach waypoints as inputs to the vehicle control algorithm. Scene perception, planning, and control run onboard in real-time; at present we obtain aircraft position knowledge from an external motion capture system, but we expect to replace this in the near future with a fully self-contained, onboard, vision-aided state estimation algorithm. We demonstrate autonomous vision-based landing and ingress target detection with two different quadrotor MAV platforms. To our knowledge, this is the first demonstration of onboard, vision-based autonomous landing and ingress algorithms that do not use special purpose scene markers to identify the destination.

micro air vehicles (MAVs)↗
NASA NTRS2004

Autonomous Navigation Results from the Mars Exploration Rover (MER) Mission

In January, 2004, the Mars Exploration Rover (MER) mission landed two rovers, Spirit and Opportunity, on the surface of Mars. Several autonomous navigation capabilities were employed in space for the first time in this mission. ]n the Entry, Descent, and Landing (EDL) phase, both landers used a vision system called the, Descent Image Motion Estimation System (DIMES) to estimate horizontal velocity during the last 2000 meters (m) of descent, by tracking features on the ground with a downlooking camera, in order to control retro-rocket firing to reduce horizontal velocity before impact. During surface operations, the rovers navigate autonomously using stereo vision for local terrain mapping and a local, reactive planning algorithm called Grid-based Estimation of Surface Traversability Applied to Local Terrain (GESTALT) for obstacle avoidance. ]n areas of high slip, stereo vision-based visual odometry has been used to estimate rover motion, As of mid-June, Spirit had traversed 3405 m, of which 1253 m were done autonomously; Opportunity had traversed 1264 m, of which 224 m were autonomous. These results have contributed substantially to the success of the mission and paved the way for increased levels of autonomy in future missions.

autonomous↗
NASA NTRS1990

Flight data acquisition methodology for validation of passive ranging algorithms for obstacle avoidance

The automation of low-altitude rotorcraft flight depends on the ability to detect, locate, and navigate around obstacles lying in the rotorcraft's intended flightpath. Computer vision techniques provide a passive method of obstacle detection and range estimation, for obstacle avoidance. Several algorithms based on computer vision methods have been developed for this purpose using laboratory data; however, further development and validation of candidate algorithms require data collected from rotorcraft flight. A data base containing low-altitude imagery augmented with the rotorcraft and sensor parameters required for passive range estimation is not readily available. Here, the emphasis is on the methodology used to develop such a data base from flight-test data consisting of imagery, rotorcraft and sensor parameters, and ground-truth range measurements. As part of the data preparation, a technique for obtaining the sensor calibration parameters is described. The data base will enable the further development of algorithms for computer vision-based obstacle detection and passive range estimation, as well as provide a benchmark for verification of range estimates against ground-truth measurements.

Smith, Phillip N.↗
NASA NTRS1991

Image-based ranging and guidance for rotorcraft

This report documents the research carried out under NASA Cooperative Agreement No. NCC2-575 during the period Oct. 1988 - Dec. 1991. Primary emphasis of this effort was on the development of vision based navigation methods for rotorcraft nap-of-the-earth flight regime. A family of field-based ranging algorithms were developed during this research period. These ranging schemes are capable of handling both stereo and motion image sequences, and permits both translational and rotational camera motion. The algorithms require minimal computational effort and appear to be implementable in real time. A series of papers were presented on these ranging schemes, some of which are included in this report. A small part of the research effort was expended on synthesizing a rotorcraft guidance law that directly uses the vision-based ranging data. This work is discussed in the last section.

Menon, P. K. A.↗
NASA NTRS1991

Vision based techniques for rotorcraft low altitude flight

An overview of research in obstacle detection at NASA Ames Research Center is presented. The research applies techniques from computer vision to automation of rotorcraft navigation. The development of a methodology for detecting the range to obstacles based on the maximum utilization of passive sensors is emphasized. The development of a flight and image data base for verification of vision-based algorithms, and a passive ranging methodology tailored to the needs of helicopter flight are discussed. Preliminary results indicate that it is possible to obtain adequate range estimates except at regions close to the FOE. Closer to the FOE, the error in range increases since the magnitude of the disparity gets smaller, resulting in a low SNR.

Sridhar, Banavar↗
NASA NTRS2005

Target Tracking, Approach, and Camera Handoff for Automated Instrument Placement

This paper describes the target designation, tracking, approach, and camera handoff technologies required to achieve accurate, single-command autonomous instrument placement for a planetary rover. It focuses on robust tracking integrated with obstacle avoidance during the approach phase, and image-based camera handoff to allow vision-based instrument placement. It also provides initial results from a complete system combining these technologies with rover base placement to maximize arm manipulability and image-based instrument placement.

target tracking↗
NASA NTRS2007

NASA Tech Briefs, September 2007

Topics covered include; Rapid Fabrication of Carbide Matrix/Carbon Fiber Composites; Coating Thermoelectric Devices To Suppress Sublimation; Ultrahigh-Temperature Ceramics; Improved C/SiC Ceramic Composites Made Using PIP; Coating Carbon Fibers With Platinum; Two-Band, Low-Loss Microwave Window; MCM Polarimetric Radiometers for Planar Arrays; Aperture-Coupled Thin-Membrane L-Band Antenna; WGM-Based Photonic Local Oscillators and Modulators; Focal-Plane Arrays of Quantum-Dot Infrared Photodetectors; Laser Range and Bearing Finder With No Moving Parts; Microrectenna: A Terahertz Antenna and Rectifier on a Chip; Miniature L-Band Radar Transceiver; Robotic Vision-Based Localization in an Urban Environment; Programs for Testing an SSME-Monitoring System; Cathodoluminescent Source of Intense White Light; Displaying and Analyzing Antenna Radiation Patterns; Payload Operations Support Team Tools; Space-Shuttle Emulator Software; Soft Real-Time PID Control on a VME Computer; Analyzing Radio-Frequency Coverage for the ISS; Nanorod-Based Fast-Response Pressure-Sensitive Paints; Capacitors Would Help Protect Against Hypervelocity Impacts; Diaphragm Pump With Resonant Piezoelectric Drive; Improved Quick-Release Pin Mechanism; Designing Rolling-Element Bearings; Reverse-Tangent Injection in a Centrifugal Compressor; Inertial Measurements for Aero-assisted Navigation (IMAN); Analysis of Complex Valve and Feed Systems; Improved Path Planning Onboard the Mars Exploration Rovers; Robust, Flexible Motion Control for the Mars Explorer Rovers; Solar Sail Spaceflight Simulation; Fluorine-Based DRIE of Fused Silica; Mechanical Alloying for Making Thermoelectric Compounds; Process for High-Rate Fabrication of Alumina Nanotemplates; Electroform/Plasma-Spray Laminates for X-Ray Optics; An Automated Flying-Insect Detection System; Calligraphic Poling of Ferroelectric Material; Blackbody Cavity for Calibrations at 200 to 273 K; KML Super Overlay to WMS Translator; High-Performance Tiled WMS and KML Web Server; Modeling of Radiative Transfer in Protostellar Disks; Composite Pulse Tube; Photometric Calibration of Consumer Video Cameras; Criterion for Identifying Vortices in High- Pressure Flows; Amplified Thermionic Cooling Using Arrays of Nanowires; Delamination-Indicating Thermal Barrier Coatings; Preventing Raman Lasing in High-Q WGM Resonators; Procedures for Tuning a Multiresonator Photonic Filter; Robust Mapping of Incoherent Fiber-Optic Bundles; Extended-Range Ultrarefractive 1D Photonic Crystal Prisms; Rapid Analysis of Mass Distribution of Radiation Shielding; Modeling Magnetic Properties in EZTB; Deep Space Network Antenna Logic Controller; Modeling Carbon and Hydrocarbon Molecular Structures in EZTB; BigView Image Viewing on Tiled Displays; and Imaging Sensor Flight and Test Equipment Software.

Source record↗
NASA NTRS2011

Visual SLAM Using Variance Grid Maps

An algorithm denoted Gamma-SLAM performs further processing, in real time, of preprocessed digitized images acquired by a stereoscopic pair of electronic cameras aboard an off-road robotic ground vehicle to build accurate maps of the terrain and determine the location of the vehicle with respect to the maps. Part of the name of the algorithm reflects the fact that the process of building the maps and determining the location with respect to them is denoted simultaneous localization and mapping (SLAM). Most prior real-time SLAM algorithms have been limited in applicability to (1) systems equipped with scanning laser range finders as the primary sensors in (2) indoor environments (or relatively simply structured outdoor environments). The few prior vision-based SLAM algorithms have been feature-based and not suitable for real-time applications and, hence, not suitable for autonomous navigation on irregularly structured terrain. The Gamma-SLAM algorithm incorporates two key innovations: Visual odometry (in contradistinction to wheel odometry) is used to estimate the motion of the vehicle. An elevation variance map (in contradistinction to an occupancy or an elevation map) is used to represent the terrain. The Gamma-SLAM algorithm makes use of a Rao-Blackwellized particle filter (RBPF) from Bayesian estimation theory for maintaining a distribution over poses and maps. The core idea of the RBPF approach is that the SLAM problem can be factored into two parts: (1) finding the distribution over robot trajectories, and (2) finding the map conditioned on any given trajectory. The factorization involves the use of a particle filter in which each particle encodes both a possible trajectory and a map conditioned on that trajectory. The base estimate of the trajectory is derived from visual odometry, and the map conditioned on that trajectory is a Cartesian grid of elevation variances. In comparison with traditional occupancy or elevation grid maps, the grid elevation variance maps are much better for representing the structure of vegetated or rocky terrain.

Howard, Andrew B.↗