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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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35 records · Page 2

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NASA NTRS1994

Improved All-Terrain Suspension System

Redesigned suspension system for all-terrain vehicle exhibits enhanced ability to negotiate sand and rocks. Improved six-wheel suspension system includes only two links on each side. Bogie tends to pull rear wheels with it as it climbs. Designed for rover vehicle for exploration of Mars, also has potential application in off-road vehicles, military scout vehicles, robotic emergency vehicles, and toys. Predecessors of suspension system described in "Articulated Suspension Without Springs" (NPO-17354), "Four-Wheel Vehicle Suspension System" (NPO-17407), and "High-Clearance Six-Wheel Suspension" (NPO-17821).

Bickler, Donald B.↗

NASA NTRS2004

Granular Materials and Risks in ISRU

Working with soil, sand, powders, ores, cement and sintered bricks, excavating, grading construction sites, driving off-road, transporting granules in chutes and pipes, sifting gravel, separating solids from gases, and using hoppers are so routine that it seems straightforward to execute these operations on the Moon and Mars as we do on Earth. We discuss how little these processes are understood and point out the nature of trial-and-error practices that are used in today s massive over-design. Nevertheless, such designs have a high failure rate. Implementation and extensive incremental scaling up of industrial processes are routine because of the inadequate predictive tools for design. We present a number of pragmatic scenarios where granular materials play a role, the risks involved, what some of the basic issues are, and what understanding is needed to greatly reduce the risks. This talk will focus on a particular class of granular flow issues, those that pertain to dense materials, their physics, and the failure problems associated with them. In particular, key issues where basic predictability is lacking include stability of soils for the support of vehicles and facilities, ability to control the flow of dense materials (jamming and flooding/unjamming at the wrong time), the ability to predict stress profiles (hence create reliable designs) for containers such as bunkers or silos. In particular, stress fluctuations, which are not accounted for in standard granular design models, can be very large as granular materials flows, and one result is frequent catastrophic failure of granular devices.

Behringer, Robert P.↗

NASA NTRS2004

Granular Materials and Risks In ISRU

Working with soil, sand, powders, ores, cement and sintered bricks, excavating, grading construction sites, driving off-road, transporting granules in chutes and pipes, sifting gravel, separating solids from gases, and using hoppers are so routine that it seems straightforward to execute these operations on the Moon and Mars as we do on Earth. We discuss how little these processes are understood and point out the nature of trial-and-error practices that are used in today's massive over-design. Nevertheless, such designs have a high failure rate. Implementation and extensive incremental scaling up of industrial processes are routine because of the inadequate predictive tools for design. We present a number of pragmatic scenarios where granular materials play a role, the risks involved, what some of the basic issues are, and what understanding is needed to greatly reduce the risks. This talk will focus on a particular class of granular flow issues, those that pertain to dense materials, their physics, and the failure problems associated with them. In particular, key issues where basic predictability is lacking include stability of soils for the support of vehicles and facilities, ability to control the flow of dense materials (jamming and flooding/unjamming at the wrong time), the ability to predict stress profiles (hence create reliable designs) for containers such as bunkers or silos. In particular, stress fluctuations, which are not accounted for in standard granular design models, can be very large as granular materials flows, and one result is frequent catastrophic failure of granular devices.

Behringer, Robert P.↗

NASA NTRS2004

Granular Materials and the Risks They Pose for Success on the Moon and Mars

Wilkinson, R. Allen↗

NASA NTRS2003

Obstacle detection in foliage with ladar and radar

Autonomous off-road navigation is central to several important applications of unmanned ground vehicles. This requires the ability to detect obstacles in vegetation. We examine the prospects for doing so with scanning ladar and with a linear array of 2.2 GHz micro-impulse radar transceivers. For ladar, we summarize our work to date on algorithms for detecting obstacles in tall grass with single-axis ladar, then present a simple probabilistic model of the distance into tall grass that ladar-based obstacle detection is possible.

ladar↗

NASA NTRS2005

Learning for autonomous navigation

robotics↗

NASA NTRS2005

Learning for autonomous navigation : extrapolating from underfoot to the far field

Autonomous off-road navigation of robotic ground vehicles has important applications on Earth and in space exploration. Progress in this domain has been retarded by the limited lookahead range of 3-D sensors and by the difficulty of preprogramming systems to understand the traversability of the wide variety of terrain they can encounter. Enabling robots to learn from experience may alleviate both of these problems. We define two paradigms for this, learning from 3-D geometry and learning from proprioception, and describe initial instantiations of them we have developed under DARPA and NASA programs. Field test results show promise for learning traversability of vegetated terrain, learning to extend the lookahead range of the vision system, and learning how slip varies with slope.

autonomous robots↗

NASA NTRS2007

Learning and Prediction of Slip from Visual Information

This paper presents an approach for slip prediction from a distance for wheeled ground robots using visual information as input. Large amounts of slippage which can occur on certain surfaces, such as sandy slopes, will negatively affect rover mobility. Therefore, obtaining information about slip before entering such terrain can be very useful for better planning and avoiding these areas. To address this problem, terrain appearance and geometry information about map cells are correlated to the slip measured by the rover while traversing each cell. This relationship is learned from previous experience, so slip can be predicted remotely from visual information only. The proposed method consists of terrain type recognition and nonlinear regression modeling. The method has been implemented and tested offline on several off-road terrains including: soil, sand, gravel, and woodchips. The final slip prediction error is about 20%. The system is intended for improved navigation on steep slopes and rough terrain for Mars rovers.

rover↗

NASA NTRS2008

Terrain-Adaptive Navigation Architecture

A navigation system designed for a Mars rover has been designed to deal with rough terrain and/or potential slip when evaluating and executing paths. The system also can be used for any off-road, autonomous vehicles. The system enables vehicles to autonomously navigate different terrain challenges including dry river channel systems, putative shorelines, and gullies emanating from canyon walls. Several of the technologies within this innovation increase the navigation system s capabilities compared to earlier rover navigation algorithms.

Helmick, Daniel M.↗

NASA NTRS2008

Study of the Correlation between the Performances of Lunar Vehicle Wheels Predicted by the Nepean Wheeled Vehicle Performance Model and Test Data

This paper describes the results of a study of the correlation between the performances of wheels for lunar vehicles predicted using the Nepean wheeled vehicle performance model (NWVPM), developed under the auspices of Vehicle Systems Development Corporation, Ottawa, Canada, and the corresponding test data presented in Performance evaluation of wheels for lunar vehicles , Technical Report M-70-2, prepared for George C. Marshall Space Flight Center, National Aeronautics and Space Administration (NASA), USA, by the US Army Engineer Waterways Experiment Station (WES). The NWVPM was originally developed for design and performance evaluation of terrestrial off-road wheeled vehicles. The purpose of this study is to assess the potential of the NWVPM for evaluating wheel candidates for the new generation of extra-terrestrial vehicles. Two versions of a wire-mesh wheel and a hoop-spring wheel, which were considered as candidates for lunar roving vehicles for the NASA Apollo program in the late 1960s, together with a pneumatic wheel were examined in this study. The tractive performances of these wheels and of a 464 test vehicle with the pneumatic wheels on air-dry sand were predicted using the NWVPM and compared with the corresponding test data obtained under Earth s gravity and previously documented in the above-named report. While test data on wheel or vehicle performances obtained under Earth s gravity may not necessarily be representative of those on extra-terrestrial bodies, because of the differences in gravity and in environmental conditions, such as atmospheric pressure, it is still a valid approach to use test data obtained under Earth s gravity to evaluate the predictive capability of the NWVPM and its potential applications to predicting wheel or wheeled rover performances on extra-terrestrial bodies. Results of this study show that, using the ratio (P20/W) of the drawbar pull to normal load at 20 per cent slip as a performance indicator, there is a reasonable correlation between the predictions and experimental data. This indicates that the NWVPM has the potential as an engineering tool for evaluating wheel candidates for a future generation of extra-terrestrial vehicles, provided that appropriate input data are available.

Wong, J. Y.↗

NASA NTRS2009

Self-Supervised Learning of Terrain Traversability from Proprioceptive Sensors

Robust and reliable autonomous navigation in unstructured, off-road terrain is a critical element in making unmanned ground vehicles a reality. Existing approaches tend to rely on evaluating the traversability of terrain based on fixed parameters obtained via testing in specific environments. This results in a system that handles the terrain well that it trained in, but is unable to process terrain outside its test parameters. An adaptive system does not take the place of training, but supplements it. Whereas training imprints certain environments, an adaptive system would imprint terrain elements and the interactions amongst them, and allow the vehicle to build a map of local elements using proprioceptive sensors. Such sensors can include velocity, wheel slippage, bumper hits, and accelerometers. Data obtained by the sensors can be compared to observations from ranging sensors such as cameras and LADAR (laser detection and ranging) in order to adapt to any kind of terrain. In this way, it could sample its surroundings not only to create a map of clear space, but also of what kind of space it is and its composition. By having a set of building blocks consisting of terrain features, a vehicle can adapt to terrain that it has never seen before, and thus be robust to a changing environment. New observations could be added to its library, enabling it to infer terrain types that it wasn't trained on. This would be very useful in alien environments, where many of the physical features are known, but some are not. For example, a seemingly flat, hard plain could actually be soft sand, and the vehicle would sense the sand and avoid it automatically.

Bajracharya, Max↗

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.↗

NASA NTRS2011

Unmanned Ground Vehicle Perception Using Thermal Infrared Cameras

The ability to perform off-road autonomous navigation at any time of day or night is a requirement for some unmanned ground vehicle (UGV) programs. Because there are times when it is desirable for military UGVs to operate without emitting strong, detectable electromagnetic signals, a passive only terrain perception mode of operation is also often a requirement. Thermal infrared (TIR) cameras can be used to provide day and night passive terrain perception. TIR cameras have a detector sensitive to either mid-wave infrared (MWIR) radiation (3-5?m) or long-wave infrared (LWIR) radiation (8-12?m). With the recent emergence of high-quality uncooled LWIR cameras, TIR cameras have become viable passive perception options for some UGV programs. The Jet Propulsion Laboratory (JPL) has used a stereo pair of TIR cameras under several UGV programs to perform stereo ranging, terrain mapping, tree-trunk detection, pedestrian detection, negative obstacle detection, and water detection based on object reflections. In addition, we have evaluated stereo range data at a variety of UGV speeds, evaluated dual-band TIR classification of soil, vegetation, and rock terrain types, analyzed 24 hour water and 12 hour mud TIR imagery, and analyzed TIR imagery for hazard detection through smoke. Since TIR cameras do not currently provide the resolution available from megapixel color cameras, a UGV's daytime safe speed is often reduced when using TIR instead of color cameras. In this paper, we summarize the UGV terrain perception work JPL has performed with TIR cameras over the last decade and describe a calibration target developed by General Dynamics Robotic Systems (GDRS) for TIR cameras and other sensors.

terrain classification↗

NASA NTRS2014

Signal Processing Methods for Removing the Effects of Whole Body Vibration upon Speech

Humans may be exposed to whole-body vibration in environments where clear speech communications are crucial, particularly during the launch phases of space flight and in high-performance aircraft. Prior research has shown that high levels of vibration cause a decrease in speech intelligibility. However, the effects of whole-body vibration upon speech are not well understood, and no attempt has been made to restore speech distorted by whole-body vibration. In this paper, a model for speech under whole-body vibration is proposed and a method to remove its effect is described. The method described reduces the perceptual effects of vibration, yields higher ASR accuracy scores, and may significantly improve intelligibility. Possible applications include incorporation within communication systems to improve radio-communication systems in environments such a spaceflight, aviation, or off-road vehicle operations.

human response to vibration↗

NASA NTRS2013

Real-Time and High-Fidelity Simulation Environment for Autonomous Ground Vehicle Dynamics

This paper reports on a collaborative project between U.S. Army TARDEC and Jet Propulsion Laboratory (JPL) to develop a unmanned ground vehicle (UGV) simulation model using the ROAMS vehicle modeling framework. Besides modeling the physical suspension of the vehicle, the sensing and navigation of the HMMWV vehicle are simulated. Using models of urban and off-road environments, the HMMWV simulation was tested in several ways, including navigation in an urban environment with obstacle avoidance and the performance of a lane change maneuver.

vehicle sensing↗

NASA NTRS2017

Effect of Angle of Attack on Slope Climbing Performance

Ascending steep slopes is often a very difficult challenge for off-road vehicles, whether on Earth or on extraterrestrial bodies. This challenge is even greater if the surface consists of loose granular soil that does not provide much shear strength. This study investigated how the path at which a vehicle traverses a slope, specifically the angle that it is commanded to drive relative to the base of the hill (the angle of attack), can affect its performance. A vehicle was driven in loose sand at slope angles up to 15 degrees and angles of attack ranging from 10 to 90 degrees. A novel photogrammetry technique was implemented to both track vehicle motion and create a three-dimensional profile of the terrain. This allowed for true wheel sinkage measurements. The study showed that though low angles of attack result in lower wheel slip and sinkage, the efficiency of the vehicles uphill motion increased at higher angles of attack. For slopes up to 15 degrees, a 90 degree angle of attack provided the greatest likelihood of successful ascent.

wheel↗

NASA NTRSDate not supplied

Multi-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS) Datasets Released by NASA GES DISC and Their Applications for Air Quality

Nitrogen dioxide (NO2), a pervasive air pollutant, comes from vehicles, power plants, industrial emissions, and off-road sources such as construction or lawn and gardening equipment. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) curates many remote sensing datasets with NO2 retrievals, which have been utilized for air quality research and applications. The remotely-sensed datasets include those generated by the Ozone Monitoring Instrument (OMI) on the Aura satellite, the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S5P), and the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the Suomi National Polar-orbiting Partnership (S- NPP). In collaboration with the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Multi-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS) project, the GES DISC recently released MINDS datasets. The NASA MEaSUREs MINDS project aims to develop long-term NO2 global data records by adapting a consistent retrieval algorithm to multiple instrument measurements. Long-term data records will be achieved by applying consistent retrieval approaches to multiple satellite instruments, including OMI (2004 - ); the Global Ozone Monitoring Experiment (GOME, 1995-2011) onboard the second European Remote Sensing satellite (ERS-2); the Scanning Imaging Spectrometer for Atmospheric Cartography (SCIAMACHY, 2002-2012) onboard the ENVIronmental SATellite (ENVISAT); GOME-2 on the Meteorological Operational satellites (MetOp-A and MetOp-B, 2006 - ); and TROPOMI onboard the Copernicus S5P (2017 - ). The long-term record (1995 to present) of MINDS datasets makes them very useful for air quality trend studies. Some MINDS datasets with high spatial resolution of only a few kilometers can be used for air quality research and applications at regional scales. In this presentation, we will introduce all of the MINDS products and services, and demonstrate use cases of MINDS data for studying air quality. We will also present a few other NO2 datasets acquired from NASA’s Health and Air Quality Applied Sciences Team (HAQAST), to be archived and distributed by the GES DISC, and highlight some of their applications for air quality and health.

Feng Ding↗