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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Improved Path Planning Onboard the Mars Exploration Rovers

A revised version of the AutoNav (autonomous navigation with hazard avoidance) software running onboard each Mars Exploration Rover (MER) affords better obstacle avoidance than does the previous version. Both versions include GESTALT (Grid-based Estimation of Surface Traversability Applied to Local Terrain), a navigation program that generates local-terrain models from stereoscopic image pairs captured by onboard rover cameras; uses this information to evaluate candidate arcs that extend across the terrain from the current rover location; ranks the arcs with respect to hazard avoidance, minimization of steering time, and the direction towards the goal; and combines the rankings in a weighted vote to select an arc, along which the rover is then driven. GESTALT works well in navigating around small isolated obstacles, but tends to fail when the goal is on the other side of a large obstacle or multiple closely spaced small obstacles. When that occurs, the goal seeking votes and hazard avoidance votes conflict severely. The hazard avoidance votes will not allow the rover to drive through the unsafe area, and the waypoint votes will not allow enough deviation from the straight-line path for the rover to get around the hazard. The rover becomes stuck and is unable to reach the goal. The revised version of AutoNav utilizes a global path-planning program, Field D*, to evaluate the cost of traveling from the end of each GESTALT arc to the goal. In the voting process, Field D* arc votes supplant GESTALT goal-seeking arc votes. Hazard avoidance, steering bias, and Field D* votes are merged and the rover is driven a preset distance along the arc with the highest vote. Then new images are acquired and the process as described is repeated until the goal is reached. This new technology allows the rovers to autonomously navigate around much more complex obstacle arrangements than was previously possible. In addition, this improved autonomy enables longer traverses per Sol (a day on Mars), and can make planning drives easier for operators on Earth.

Stentz, Anthony↗
NASA NTRS1994

Small image laser range finder for planetary rover

A variety of technical subjects need to be solved before planetary rover navigation could be a part of future missions. The sensors which will perceive terrain environment around the rover will require critical development efforts. The image laser range finder (ILRF) discussed here is one of the candidate sensors because of its advantage in providing range data required for its navigation. The authors developed a new compact-sized ILRF which is a quarter of the size of conventional ones. Instead of the current two directional scanning system which is comprised of nodding and polygon mirrors, the new ILRF is equipped with the new concept of a direct polygon mirror driving system, which successfully made its size compact to accommodate the design requirements. The paper reports on the design concept and preliminary technical specifications established in the current development phase.

Wakabayashi, Yasufumi↗
NASA NTRS1979

Autonomy in space navigation

The potential development of autonomous onboard navigation systems for future space missions is discussed. Motivations for autonomy in the near-earth satellite program and in deep-space navigation are examined, emphasizing lower mission-operation costs for the first, and reduction of ground-system complexity as well as encounter accuracy for the latter. Uses of navigation parameters by the Information Adaptive System, including sensor-pointing computation and image correction, are noted, as are the accuracy parameters of the NAVSTAR Global Positioning System. The role of autonomous onboard navigation in contact exploration of Neptune's and Uranus's satellites as well as in such extreme-high-velocity encounters as those with retrograde comets is investigated. The Automated Optical Navigation program is described

Jordan, J. F.↗
NASA NTRS1973

Digital processing of stereoscopic image pairs.

The problem under consideration is concerned with scene analysis during robot navigation on the surface of Mars. In this mode, the world model of the robot must be continuously updated to include sightings of new obstacles and scientific samples. In order to describe the content of a particular scene, it is first necessary to segment it into known objects. One technique for accomplishing this segmentation is by analyzing the pair of images produced by the stereoscopic cameras mounted on the robot. A heuristic method is presented for determining the range for each point in the two-dimensional scene under consideration. The method is conceptually based on a comparison of corresponding points in the left and right images of the stereo pair. However, various heuristics which are adaptive in nature are used to make the algorithm both efficient and accurate. Examples are given of the use of this so-called range picture for the purpose of scene segmentation.

Levine, M. D.↗
NASA NTRS1981

Deep space navigation systems and operations

The history of the deep space navigation system developed by NASA is outlined. Its application to Mariner, Viking and Pioneer missions is reviewed. Voyager navigation results for Jupiter and Saturn are commented on and velocity correction in relation to fuel expenditure and computer time are discussed. The navigation requirements of the Gahleo and Venus orbiting imaging radar (VOIR) missions are assessed. The measurement and data processing systems are described.

Jordan, J. F.↗
NASA NTRS1999

STS-96 FD Highlights and Crew Activities Report: Flight Day 09

On this ninth day of the STS-96 Discovery mission, the flight crew, Commander Kent V. Rominger, Pilot Rick D. Husband, and Mission Specialists Ellen Ochoa, Tamara E. Jernigan, Daniel T. Barry, Julie Payette, and Valery Ivanovich Tokarev are seen as they prepare to depart from the International Space Station. After the undocking of the spacecraft, Husband navigated the spacecraft around the International Space Station. Images of the crew removing centerline cameras, tracking the solar arrays and beautiful panoramic views of the Station above the Earth are seen.

Source record↗
NASA NTRS2002

Bioinspired engineering of exploration systems for NASA and DoD

A new approach called bioinspired engineering of exploration systems (BEES) and its value for solving pressing NASA and DoD needs are described. Insects (for example honeybees and dragonflies) cope remarkably well with their world, despite possessing a brain containing less than 0.01% as many neurons as the human brain. Although most insects have immobile eyes with fixed focus optics and lack stereo vision, they use a number of ingenious, computationally simple strategies for perceiving their world in three dimensions and navigating successfully within it. We are distilling selected insect-inspired strategies to obtain novel solutions for navigation, hazard avoidance, altitude hold, stable flight, terrain following, and gentle deployment of payload. Such functionality provides potential solutions for future autonomous robotic space and planetary explorers. A BEES approach to developing lightweight low-power autonomous flight systems should be useful for flight control of such biomorphic flyers for both NASA and DoD needs. Recent biological studies of mammalian retinas confirm that representations of multiple features of the visual world are systematically parsed and processed in parallel. Features are mapped to a stack of cellular strata within the retina. Each of these representations can be efficiently modeled in semiconductor cellular nonlinear network (CNN) chips. We describe recent breakthroughs in exploring the feasibility of the unique blending of insect strategies of navigation with mammalian visual search, pattern recognition, and image understanding into hybrid biomorphic flyers for future planetary and terrestrial applications. We describe a few future mission scenarios for Mars exploration, uniquely enabled by these newly developed biomorphic flyers.

Space Flight↗
NASA NTRS2010

Crater Identification Algorithm for the Lost in Low Lunar Orbit Scenario

Recent emphasis by NASA on returning astronauts to the Moon has placed attention on the subject of lunar surface feature tracking. Although many algorithms have been proposed for lunar surface feature tracking navigation, much less attention has been paid to the issue of navigational state initialization from lunar craters in a lost in low lunar orbit (LLO) scenario. That is, a scenario in which lunar surface feature tracking must begin, but current navigation state knowledge is either unavailable or too poor to initiate a tracking algorithm. The situation is analogous to the lost in space scenario for star trackers. A new crater identification algorithm is developed herein that allows for navigation state initialization from as few as one image of the lunar surface with no a priori state knowledge. The algorithm takes as inputs the locations and diameters of craters that have been detected in an image, and uses the information to match the craters to entries in the USGS lunar crater catalog via non-dimensional crater triangle parameters. Due to the large number of uncataloged craters that exist on the lunar surface, a probability-based check was developed to reject false identifications. The algorithm was tested on craters detected in four revolutions of Apollo 16 LLO images, and shown to perform well.

Hanak, Chad↗
NASA NTRS2016

Characterization of Stereo Vision Performance for Roving at the Lunar Poles

Surface rover operations at the polar regions of airless bodies, particularly the Moon, are of particular interest to future NASA science missions such as Resource Prospector (RP). Polar optical conditions present challenges to conventional imaging techniques, with repercussions to driving, safeguarding and science. High dynamic range, long cast shadows, opposition and white out conditions are all significant factors in appearance. RP is currently undertaking an effort to characterize stereo vision performance in polar conditions through physical laboratory experimentation with regolith simulants, obstacle distributions and oblique lighting.

Sensor Characterization↗
NASA NTRSDate not supplied

The Comet Astrobiology Exploration Sample Return (CAESAR) Mission

The Comet Astrobiology Exploration Sample Return (CAESAR) mission will acquire and return to Earth for laboratory analysis a minimum of 80 grams of surface material from the nucleus of comet 67P/Chur-yumov-Gerasimenko (67P). CAESAR will characterize the surface region sampled, preserve the collected sample in a pristine state, and return evolved volatiles by capturing them in a separate gas reservoir. NASA Goddard Space Flight Center provides project management, systems engineering, safety and mission assurance, contamination control, mission operations, and many other important functions. Northrop Grumman Space Systems will build the spacecraft, based on Dawn mission heritage, which like CAESAR, uses solar electric propulsion. CAESAR was selected by for Phase A study in the New Frontiers 4 Competition and will be proposed to New Frontiers 5.Collection of a sample from the surface of comet 67P is facilitated by a set of cameras that together provide images to support sample site selection, perform optical navigation, and document the sample before, during, and after col-lection. The sample is collected at the end of an arm during a 5-second touch-and-go (TAG) maneuver with the Sample Acquisition System (SAS)designed by Honeybee Robotics for the surface properties of comet 67P observed by the Rosetta mission. After sample collection, and while the sample is still cold (< -80°C), the TAG Arm inserts the sample container into the Sample Containment System (SCS) mounted inside the Sample Return Capsule (SRC). The SCS is sealed, preventing the sample from escaping into space. The sample is slowly warmed inside the SCS to enable sublimation of volatiles, which are collected in the Gas Containment System (GCS), a passively cooled gas reservoir. Separating the volatiles from the solid sample protects the solid sample from alteration. Once all sublimated H2O is transferred to the GCS, the GCS is sealed to capture the volatile sit contains, and the SCS is vented to space to maintain the solid sample under vacuum. The SCS vent is closed before Earth entry to prevent atmospheric contamination. Detailed laboratory analyses of the sample from 67P will trace the history of volatile reservoirs, delineate the chemical pathways that led from simple interstellar species to complex molecules, constrain the evolution of the comet, and evaluate the role of comets in delivering water and prebiotic organics to the early Earth. CAESAR will achieve these goals by carrying out coordinated sample analyses that will link macroscopic properties of the comet with microscale mineralogy, chemistry, and isotopic studies of volatiles and solids. Most of the sample (≥75%) will be set aside for analyses by generations of scientists using continually advancing tools and methods, yielding an enduring scientific treasure that only sample return can provide. This presentation will review development conducted during NF4 Phase A and discuss the NF5 mission concept.

A G Hayes↗
NASA NTRSDate not supplied

An Integrated Software Architecture for Solar Cruiser Mission Design and Navigation

Solar Cruiser is a solar sailing mission, riding as a secondary payload to the Interstellar Mapping and Acceleration Probe (IMAP) mission, slated to launch in February of 2025. The Solar Cruiser vehicle will generate thrust via a complex, low-thrust solar sail. The extreme low-thrust nature of the solar sail will leave Solar Cruiser highly sensitive to external environmental effects (such as solar radiation pressure and high-order gravitational perturbations) throughout the entirety of flight. Because of this, preliminary operational optimization routines must be intricately tied to high-order predictive propagation models to ensure the greatest possible confidence in mission success. The Solar Cruiser Mission Design and Navigation (MDNav) team has designed a software tool suite, employing the latest in software containerization technology, to accomplish this task; allowing for seamless development across several users and operating systems. Combining JPL’s Monte toolkit with high-performance optimizers written by the University of Alabama, the proposed architecture allows for instant verification of optimized trajectories within the same development environment that the optimization takes place, removing the need for mission designers and navigators to switch between tools. The MDNav suite image deployment process is separated from the development and operational scripts to be used in flight, which allows for maintaining a low-footprint version control profile without unnecessary file bloating. This paper discusses the historical differences between previous iterations of the Solar Cruiser MDNav tool suite and the current iteration, planned operational interfaces of the tool with other software and subsystems, and the planned path forward in maintaining containerization services for the software throughout the lifetime of Solar Cruiser.

optimization↗
NASA NTRSDate not supplied

On-Orbit Cross Calibration Between the Osiris-Rex Orbiting Laser Altimeter and Navigation Camera

Accurate shape models of small bodies provide both science value and resources for precision relative navigation. One instrument commonly used for generating shape models is the laser altimeter. Laser altimeters require accurate intrinsic and extrinsic calibration knowledge to produce accurate shape models. Here, we describe a method used for updating the intrinsic and extrinsic calibration parameters of the laser altimeter onboard the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) spacecraft, OLA (OSIRISREx Laser Altimeter). We perform the calibration update by comparing the OLA scans with monocular camera images of the asteroid surface captured by the primary navigation camera.

Andrew J. Liounis↗
NASA NTRS2012

Mars Science Laboratory Engineering Cameras

NASA's Mars Science Laboratory (MSL) Rover, which launched to Mars in 2011, is equipped with a set of 12 engineering cameras. These cameras are build-to-print copies of the Mars Exploration Rover (MER) cameras, which were sent to Mars in 2003. The engineering cameras weigh less than 300 grams each and use less than 3 W of power. Images returned from the engineering cameras are used to navigate the rover on the Martian surface, deploy the rover robotic arm, and ingest samples into the rover sample processing system. The navigation cameras (Navcams) are mounted to a pan/tilt mast and have a 45-degree square field of view (FOV) with a pixel scale of 0.82 mrad/pixel. The hazard avoidance cameras (Haz - cams) are body-mounted to the rover chassis in the front and rear of the vehicle and have a 124-degree square FOV with a pixel scale of 2.1 mrad/pixel. All of the cameras utilize a frame-transfer CCD (charge-coupled device) with a 1024x1024 imaging region and red/near IR bandpass filters centered at 650 nm. The MSL engineering cameras are grouped into two sets of six: one set of cameras is connected to rover computer A and the other set is connected to rover computer B. The MSL rover carries 8 Hazcams and 4 Navcams.

Maki, Justin N.↗
NASA NTRS1997

Neural Network Based Sensory Fusion for Landmark Detection

NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.

Kumbla, Kishan -K.↗
DOE OSTI2026

Extremized nonlinear and linearized responses in soft metamaterials enabled by gradient-based design and grayscale digital light processing

In this study, we develop a gradient-based design approach that exploits grayscale digital light processing (DLP) 3D printing for extremizing the nonlinear and linearized response of soft metamaterials — materials that harness engineered geometric instabilities to undergo large and programmable changes in configuration. Grayscale DLP approaches modulate local mechanical properties at the pixel scale by tuning the light intensity within a single grayscale image, unlocking an exceptionally large design space. To effectively navigate this space, we develop smooth mappings between local light intensity values and global quantities of interest that characterize the behavior of soft metamaterials. Enabling these smooth mappings are robust and differentiable nonlinear finite element simulations powered by a trust region solver. A PDE-constrained optimization problem is then solved to invert these mappings and produce light intensity distributions that endow the printed part with varying stiffness and flexibility in distinctive regions. It is shown that optimizing the distribution of soft and stiff phases throughout a metamaterial structure results in markedly different buckling and self-contact configurations to drive extremized nonlinear compression and linearized vibration responses. Optimized light intensity distributions are translated to grayscale images and directly used to print soft metamaterial samples, showing remarkable agreement between the buckling and self-contact response in simulated and measured deformed configurations.

Additive manufacturing↗
NASA NTRSDate not supplied

Improving Sim-to-Real Transfer in Vision-Based Robot Navigation Via Instance-Level GAN-Based Data Augmentation

Achieving robust vision-based robotic tasks requires large amounts of data, which are often difficult to obtain in real-world scenarios. Simulators and synthetic data offer a cost-effective alternative, but the visual gap between simulation and reality hinders the performance of models when deployed in real-world environments. In this paper, we present a data augmentation pipeline that integrates a foundation model (Segment Anything Model) with an unsupervised image-to-image translation model (CycleGAN) for instance-level domain transfer from simulation to reality. This pipeline enables the generation of realistic labeled data from synthetic images for training supervised machine learning models in vision-based navigation tasks. We evaluate our approach on real-world data for ego-vehicle pose estimation, a critical autonomous navigation task involving the prediction of cross-track position and heading angle relative to road center line markings. The results of our tests show that our GAN-based data augmentation pipeline significantly outperforms models trained solely on simulation data or on data processed with standard image augmentation methods for sim-to-real transfer, enhancing model robustness and generalizability in real-world scenarios. Our method provides a scalable and flexible data augmentation tool for leveraging large synthetic datasets to enhance vision-based robotic navigation tasks.

artificial intelligence↗
NASA NTRS1990

Ephemerides of the major Neptunian satellites determined from earth-based astrometric and Voyager imaging observations

The Voyager project used Neptunian satellite ephemerides to support both navigation and acquisition of scientific data. The development of postencounter ephemerides for the satellites Triton, Nereid, and 1989N1 is discussed. Primary results are the final set of model parameters which generate orbits that best fit both the earth-based satellite observations and data acquired by Voyager. The ephemerides are compared with those generated preencounter, and the accuracy of the final ephemerides is assessed. Mean orbital elements are also provided as a geometrical representation for the satellite orbits.

Jacobson, R. A.↗
NASA NTRS2017

Optical-Based Kinematic Positioning for Deep-Space Navigation

NASA’s Deep Space 1 mission demonstrated that a spacecraft can be navigated autonomously during deep-space cruise operations using only images of distant asteroids as measurements. This paper derives an approximation of the position estimate accuracy that can be achieved with this technique based on the assumption of multiple, simultaneous line-of-sight measurements. This achievable accuracy is computed for locations across the solar system, which can be used to estimate cruise navigation performance as a function of spacecraft trajectory. It is shown that a on-board optical navigation system can achieve kinematic position estimate accuracies of better than 100 km throughout the inner solar system with a highperformance camera and from many hundred to several thousand kilometers with a low-end camera. Beyond the main-asteroid belt, the feasibilty of this approach suffers due to lack of targets. A case-study implementation of this approach for the upcoming InSight mission to Mars is also presented.

Bhaskaran, Shyam↗