Search Results

Remotely operating complex robotic mechanisms in unstructured natural environments is difficult at best. When the communications time delay is large, as for a Mars exploration rover operated from Earth, the difficulties become enormous. Conventional approaches, such as rate control of the rover actuators, are too inefficient and risky. The Intelligent Mechanisms Laboratory at the NASA Ames Research Center has developed over the past four years an architecture for operating science exploration robots in the presence of large communications time delays. The operator interface of this system is called the Virtual Environment Vehicle Interface (VEVI), and draws heavily on Virtual Environment (or Virtual Reality) technology. This paper describes the current operational version of VEVI, which we refer to as version 2.0. In this paper we will describe the VEVI design philosophy and implementation, and will describe some past examples of its use in field science exploration missions.

The General Purpose Work Station (GPWS) is a laboratory multi-use facility, as demonstrated during the Spacelab Life Sciences 1 (SLS-1) flight. The unit provided particulate containment under varying conditions, served as an effective work space for manipulating live animals, e.g., rats, served as a containment facility for fixatives, and was proposed for use to conduct in-flight maintenance during connector pin repair. The cabinet has a front door large enough to allow installation of a full-size microscope in-flight and is outfitted with a side window to allow delivery of items into the cabinet without exposure to the spacelab atmosphere. Additional support subsystems include inside cabinet mounting, surgical glove fine manipulations capability, and alternating or direct current power supply for experiment equipment, as will be demonstrated during Spacelab J.

Predicting and testing for hover performance, both in and out of ground effect, and transition performance, from jet- to wing-borne flight and back, for vertical/short takeoff and landing (V/STOL) configurations can be a difficult task. Large-scale testing of these configurations can provide for a better representation of the flow physics than small-scale testing. This paper will discuss some of the advantages in testing at large-scale and some test techniques and issues involved with testing large-scale STOVL models. The two premier test facilities for testing large- to full-scale STOVL configurations are the Outdoor Aerodynamic Research Facility (OARF) and the 80- by 120-Foot Wind Tunnel of the National Full-Scale Aerodynamics Complex (NFAC). Other items of discussion will include force and moment measurements, jet efflux decay, wall effects, tunnel flow breakdown, strut interference, and flow visualization options.

NASA and the FAA conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding of high ice water content (HIWC) and develop onboard weather radar processing techniques to detect regions of HIWC ahead of an aircraft to enable tactical avoidance of the potentially hazardous conditions. Both HIWC RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory equipped with a Honeywell RDR-4000 weather radar and in-situ microphysical instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results. The first campaign was conducted in August 2015 with a base of operations in Ft. Lauderdale, Florida.

Biomolecules exhibit specific binding and high affinity for their ligands. These properties can be exploited to produce sensitive, specific, real-time sensors for analytes that cannot be readily monitored by other methods. Several technologies for environmental monitoring using proteins are currently being developed. We discuss specific challenges to practical application of a family of protein-based sensors derived from bacterial periplasmic binding proteins. We also present recent work to address these challenges.

The paper describes an approach to the integration of qualitative and quantitative modeling techniques for advanced life support (ALS) systems. Developing reliable control strategies that scale up to fully integrated life support systems requires augmenting quantitative models and control algorithms with the abstractions provided by qualitative, symbolic models and their associated high-level control strategies. This will allow for effective management of the combinatorics due to the integration of a large number of ALS subsystems. By focusing control actions at different levels of detail and reactivity we can use faster, simpler responses at the lowest level and predictive but complex responses at the higher levels of abstraction. In particular, methods from model-based planning and scheduling can provide effective resource management over long time periods.

In the cockpit of NASA's next generation spacecraft, most vehicle command will be performed via electronic interfaces instead of hard cockpit switches. Checklists will be also displayed and completed on electronic procedure viewers rather than on paper. Transitioning to electronic cockpit interfaces opens up opportunities for more automated assistance, including automated root-cause diagnosis capability. The paper reports an empirical study evaluating two potential concepts for fault management interfaces incorporating two different levels of automation. The operator performance benefits produced by automation were assessed. Also, some design recommendations for spacecraft fault management interfaces are discussed.

This paper offers a concept for a regenerable, low-power system for purifying exhaust from a solid waste processor. The innovations in the concept include the use of a closed-loop regeneration cycle for the adsorber, which prevents contaminants from reaching the breathable air before they are destroyed, and the use of a humidity-swing desorption cycle, which uses less power than a thermal desorption cycle and requires no venting of air and water to space vacuum or planetary atmosphere. The process would also serve well as a trace contaminant control system for the air in the closed environment. A systems-level design is presented that shows how both the exhaust and air purification tasks could be performed by one processor. Data measured with a fixed-bed apparatus demonstrate the effects of the humidity swing on regeneration of the adsorbent.

This paper discussed how data mining techniques could give advantage to the robot in navigation, in terms of speed. The input of our navigation system is the sensory information collected by the robot's equipped landmark sensor and infra-red sensor, the process of the system is the proposed data mining technique, and the output of the system is the execution of the moving direction in a 2D Martian environment. The results demonstrate efficient goal-oriented navigation using data mining techniques.

The On-line Project Information System (OPIS) is a LAMP-based (Linux, Apache, MySQL, PHP) system being developed at NASA Ames Research Center to improve Agency information transfer and data availability, largely for improvement of system analysis and engineering. The tool will enable users to investigate NASA technology development efforts, connect with experts, and access technology development data. OPIS is currently being developed for NASA's Exploration Life Support (ELS) Project. Within OPIS, NASA ELS Managers assign projects to Principal Investigators (PI), track responsible individuals and institutions, and designate reporting assignments. Each PI populates a “Project Page” with a project overview, team member information, files, citations, and images. PI's may also delegate on-line report viewing and editing privileges to specific team members. Users can browse or search for project and member information.

Scheduled arriving aircraft demand may exceed airport arrival capacity when there is abnormal weather at an airport. In such situations, Federal Aviation Administration (FAA) institutes ground-delay programs (GDP) to delay flights before they depart from their originating airports. Efficient GDP planning depends on the accuracy of prediction of airport capacity and demand in the presence of uncertainties in weather forecast. This paper presents a study of the impact of dynamic airport surface weather on GDPs. Using the National Traffic Management Log, effect of weather conditions on the characteristics of GDP events at selected busy airports is investigated. Two machine learning methods are used to generate models that map the airport operational conditions and weather information to issued GDP parameters and results of validation tests are described.

When the demand for either a region of airspace or an airport approaches or exceeds the available capacity, miles-in-trail (MIT) restrictions are the most frequently issued traffic management initiatives (TMIs) that are used to mitigate these imbalances. Miles-in-trail operations require aircraft in a traffic stream to meet a specific inter-aircraft separation in exchange for maintaining a safe and orderly flow within the stream. This stream of aircraft can be departing an airport, over a common fix, through a sector, on a specific route or arriving at an airport. This study begins by providing a high-level overview of the distribution and causes of arrival MIT restrictions for the top ten airports in the United States. This is followed by an in-depth analysis of the frequency, duration and cause of MIT restrictions impacting the Hartsfield-Jackson Atlanta International Airport (ATL) from 2009 through 2011.

A processing system has been developed to meet increasing demands for detailed noise measurement of aircraft in wind tunnels. Phased arrays enable spatial and amplitude measurements of acoustic sources, including low signal-to-noise sources not measurable by conventional measurement techniques. The Microphone Array Phased Processing System (MAPPS) provides processing and visualization of acoustic array measurements made in wind tunnels. The system uses networked parallel computers to provide noise maps at selected frequencies in a near real-time testing environment. The system has been successfully used in two subsonic, hard-walled wind tunnels, the NASA Ames 7- by 10-Foot Wind Tunnel and the NASA Ames 12-Foot Wind Tunnel. Low level airframe noise that can not be measured with traditional techniques was measured in both tests.

Accurate root zone moisture control in microgravity plant growth systems is problematic. With gravity, excess water drains along a vertical gradient, and water recovery is easily accomplished. In microgravity, the distribution of water is less predictable and can easily lead to flooding, as well as anoxia. Microgravity water delivery systems range from solidified agar, water-saturated foams, soils and hydroponics soil surrogates including matrix-free porous tube delivery systems. Surface tension and wetting along the root substrate provides the means for adequate and uniform water distribution. Reliable active soil moisture sensors for an automated microgravity water delivery system currently do not exist. Surrogate parameters such as water delivery pressure have been less successful.

The Plant Generic BioProcessing Apparatus (PGBA), a plant growth facility developed for commercial space biotechnology research, has flown successfully on 3 spaceflight missions for 4, 10 and 16 days. The environmental control systems of this plant growth chamber (28 liter/0.075 m2) provide atmospheric, thermal, and humidity control, as well as lighting and nutrient supply. Typical performance profiles of water transpiration and dehumidification, carbon dioxide absorption (photosynthesis) and respiration rates in the PGBA unit (on orbit and ground) are presented. Data were collected on single and mixed crops. Design options and considerations for the different sub-systems are compared with those of similar hardware.

This paper describes the initial results of applying two machine-learning-based unsupervised anomaly detection algorithms, Orca and GritBot, to data from two rocket propulsion testbeds. The first testbed uses historical data from the Space Shuttle Main Engine. The second testbed uses data from an experimental rocket engine test stand located at NASA Stennis Space Center. The paper describes four candidate anomalies detected by the two algorithms.

This paper describes a multi-disciplinary damage detection methodology that can aid in detecting and diagnosing a damage in a given structural system, not limited to the example of a rotating gear presented here. Damage detection is performed on the gear stress data corresponding to the steady state conditions. The normal and damage data are generated by a finite-difference solution of elastodynamic equations of velocity and stress in generalized coordinates1. The elastodynamic solution provides a knowledge of the stress distribution over the gear such as locations of stress extrema, which in turn can lead to an optimal placement of appropriate sensors over the gear to detect a potential damage. The damage detection is performed by a multi-function optimization that incorporates Tikhonov kernel regularization reinforced by an added Laplacian regularization term as used in semi-supervised machine learning. Damage is mimicked by reducing the rigidity of one of the gear teeth.

This paper presents a novel health monitoring and fault adaptive control architecture for an unmanned hexrotor helicopter. The technologies developed to achieve the described level of robust fault contingency management include; 1.) A Particle Swarm Optimization (PSO) routine for maximizing the “built-in” fault tolerance that the closed loop flight control system affords, 2.) A two-stage Kalman filter scheme for real-time identification of faults that are masked by control system compensation, and 3.) A reconfigurable control allocation method which compensates for large degradations of the six main motor/rotor assemblies. The fault adaptive control system presented herein has strong robustness against small faults without the need for controller reconfiguration, and strong tolerance of large faults through adaptive accommodation of the fault source and severity.

During 1995, we tested instruments and attempted a seed-to-seed experiment with Super-Dwarf wheat in the Russian Space Station Mir. Utah instrumentation included four IR gas analyzers (CO2 and H2O vapor, calculate photosynthesis, respiration, and transpiration) and sensors for air and leaf (IR) temperatures, O2, pressure, and substrate moisture (16 probes). Shortly after planting on August 14, three of six fluorescent lamp sets failed; another failed later. Plastic bags, necessary to measure gas exchange, were removed. Hence, gases were measured only in the cabin atmosphere. Other failures led to manual watering, control of lights, and data transmission. The 57 plants were sampled five times plus final harvest at 90 d. Samples and some equipment (including hard drives) were returned to earth on STS-74 (Nov. 20). Plants were disoriented and completely vegetative. Maintaining substrate moisture was challenging, but the moisture probes functioned well.

We examine the requirements for on-board aircraft sensor systems that would allow pilots to “see through” poor weather, especially fog, and land and rollout aircraft under conditions that currently cause flight cancellations and airport closures. Three visual aspects of landing and rollout are distinguished: guidance, hazard detection and hazard recognition. The visual features which support the tasks are discussed. Three broad categories of sensor technology are examined: passive millimeter wave (PMMW), imaging radar, and passive infrared (IR). PMMW and imaging radar exhibit good weather penetration, but poor spatial and temporal resolution. Imaging radar exhibits good weather penetration, but typically relies on a flat-earth assumption which can lead to interpretive errors. PMMW systems have a narrow field of view. IR has poorer weather penetration but good spatial resolution.