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In this web site usability case study, two methods of participative inquiry are used to align a development team's objectives with their users' needs and to promote the team awareness of the benefit of qualitative usability analysis.
The U.S. ASTER Science Team is currently engaged in numerous ASTER related activities, many of them jointly with our Japanese colleagues. These include vicarious instrument calibration, algorithm development and validation for higher level data products, assistance to ERSDAC for scheduling activities (primarily for U.S. users), assistance to data users other than Science Team members, and science applications of ASTER data, notably in the areas of glacial monitoring, volcanic monitoring, heat balance determinations, geologic mapping, and cloud studies.
This position paper describes an approach to building spoken dialogue systems for environments containing multiple human speakers and hearers, and multiple robotic speakers and hearers. We address the issue, for robotic hearers, of whether the speech they hear is intended for them, or more likely to be intended for some other hearer. We will describe data collected during a series of experiments involving teams of multiple human and robots (and other software participants), and some preliminary results for distinguishing robot-directed speech from human-directed speech. The domain of these experiments is Mars-analogue planetary exploration. These Mars-analogue field studies involve two subjects in simulated planetary space suits doing geological exploration with the help of 1-2 robots, supporting software agents, a habitat communicator and links to a remote science team. The two subjects are performing a task (geological exploration) which requires them to speak with each other while also speaking with their assistants. The technique used here is to use a probabilistic context-free grammar language model in the speech recognizer that is trained on prior robot-directed speech. Intuitively, the recognizer will give higher confidence to an utterance if it is similar to utterances that have been directed to the robot in the past.
A partnership between the NASA Ames Research Center and the NASA Dryden Flight Research Center (DFRC) explored the ability of small unmanned aircraft to support forest fire fighting using teaming behavior. The Networked UAV Teams project flight tested mission planning algorithms for multi-UAV cooperative transit, area search, and waypoint time-of-arrival that might someday allow the early detection of developing forest fires and support the gathering of images and atmospheric samples to help improve predictions of the future behavior of established fires.
On February 1, 2003 the Space Shuttle Columbia, returning to Earth with a crew of seven astronauts, disintegrated along a track extending from California to Louisiana. Observers on the ground filmed breakup of the spacecraft. Debris fell along a 567 statute mile track from Littlefield, Texas to Fort Polk, Louisiana; the largest ever recorded debris field. At the time of the accident the National Aeronautics and Space Administration (NASA) flight surgeon on-duty at the Mission Control Center (MCC) in Houston, Texas initiated the medical contingency response. The DOD surgeon at Patrick Air Force Base was notified, NASA medical personnel were recalled and the services of Armed Forces Institute of Pathology (AFIP) were requested. Subsequent to the accident the NASA flight surgeons that had supported the crew on orbit now provided medical support to the crewmember s families. Federal Emergency Management Agency (FEMA), the National Transportation Safety Board (NTSB), the Federal Bureau of Investigation (FBI) and numerous other federal, state and local agencies along with the citizens of Texas and Louisiana responded to the disaster. Search and recovery was managed from a Disaster Field Office (DFO) established in Lufkin, Texas. Mishap Investigation Team (MIT) medical operations were managed from Barksdale Air Force Base, Louisiana. Accident investigation teams (Columbia Accident Investigation Task Force (CAITF) and Columbia Accident Investigation Board (CAIB)) appointed immediately after the disaster included current and former authorities in space medicine. In August 2003, the CAIB concluded its investigation and released its findings in a report published in February 2004.
Human-Agent collaboration is increasingly important. Not only do high-profile activities such as NASA missions to Mars intend to employ such teams, but our everyday activities involving interaction with computational devices falls into this category. In many of these scenarios, we are expected to trust that the agents will do what we expect and that the agents and humans will work together as expected. But how can we be sure? In this paper, we bring together previous work on the verification of multi-agent systems with work on the modelling of human-agent teamwork. Specifically, we target human-robot teamwork. This paper provides an outline of the way we are using formal verification techniques in order to analyse such collaborative activities. A particular application is the analysis of human-robot teams intended for use in future space exploration.
The International Space Station Materials and Processes (ISS M&P) team has multiple material samples on MISSE 6, 7 and 8 to observe Low Earth Orbit (LEO) environmental effects on Space Station materials. Optical properties, thickness/mass loss, surface elemental analysis, visual and microscopic analysis for surface change are some of the techniques employed in this investigation. The ISS M&P team has participated in previous MISSE activities in order to better characterize the LEO effects on Space Station materials. This investigation will further this effort. Results for the following MISSE 6 samples materials will be presented: a comparison of anodize and chemical conversion coatings on various aluminum alloys, electroless nickel; AZ93 white ceramic thermal control coating with and without Teflon; Hyzod(TM) polycarbonate used to temporarily protect ISS windows; Russian quartz window material; reformulated Teflon (TM) coated Beta Cloth (Teflon TM without perfluorooctanoic acid (PFOA)) and a Dutch version of beta cloth. Discussion for current and future MISSE materials experiments will be presented. MISSE 7 samples are: deionized water sealed anodized aluminum Photofoil(TM); indium tin oxide (ITO)- coated Kapton(TM) used as thermo-optical surfaces; mechanically scribed tin-plated beryllium-copper samples for "tin pest" growth ( alpha/Beta transformation); Crew Exploration Vehicle (CEV) parachute soft goods. MISSE 8 sample: exposed "scrim cloth" (fiberglass weave) from the ISS solar array wing material, Davlyn fiberglass sleeve material, Permacel and Intertape protective tapes, and ITO-coated Kapton.
Embry Riddle Aeronautical University's Daytona Beach Campus Lunabotics Team took the opportunity to share the love of space, engineering and technology through the educational outreach portion of the competition. Through visits to elementary schools and high schools, and through support of science fairs and robotics competitions, younger generations were introduced to space, engineering and robotics. This report documents the outreach activities of team Aether.
HEFT was a NASA-wide team that performed analyses of architectures for human exploration beyond LEO, evaluating technical, programmatic, and budgetary issues to support decisions at the highest level of the agency in HSF planning. HEFT Phase I (April - September, 2010) and Phase II (September - December, 2010) examined a broad set of Human Exploration of Near Earth Objects (NEOs) Design Reference Missions (DRMs), evaluating such factors as elements, performance, technologies, schedule, and cost. At end of HEFT Phase 1, an architecture concept known as DRM 4a represented the best available option for a full capability NEO mission. Within DRM4a, the habitation system was provided by Deep Space Habitat (DSH), Multi-Mission Space Exploration Vehicle (MMSEV), and Crew Transfer Vehicle (CTV) pressurized elements. HEFT Phase 2 extended DRM4a, resulting in DRM4b. Scrubbed element-level functionality assumptions and mission Concepts of Operations. Habitation Team developed more detailed concepts of the DSH and the DSH/MMSEV/CTV Conops, including functionality and accommodations, mass & volume estimates, technology requirements, and DDT&E costs. DRM 5 represented an effort to reduce cost by scaling back on technologies and eliminating the need for the development of an MMSEV.
NASA people are passionate about their work. NASA's missions are exciting to learners of all ages. And since its creation in 1958, NASA's people have been passionate about sharing their inspiring discoveries, research and exploration with students and educators. In May 2010, NASA administration chartered an Education Design Team composed of 12 members chosen from the Office of Education, NASA's Mission Directorates and Centers for their depth of knowledge and education expertise, and directed them to evaluate the Agency's program in the context of current trends in education. By improving NASA's educational offerings, he was confident that the Agency can play a leading role in inspiring student interest in science, technology, engineering and mathematics (STEM) as few other organizations can. Through its unique workforce, facilities, research and innovations, NASA can expand its efforts to engage underserved and underrepresented communities in science and mathematics. Through the Agency's STEM education efforts and science and exploration missions, NASA can help the United States successfully compete, prosper and be secure in the 21st century global community. After several months of intense effort, including meeting with education experts; reviewing Administration policies, congressional direction and education research; and seeking input from those passionate about education at NASA, the Education Design Team made six recommendations to improve the impact of NASA's Education Program: (1) Focus the NASA Education Program to improve its impact on areas of greatest national need (2) Identify and strategically manage NASA Education partnerships (3) Participate in National and State STEM Education policy discussions (4) Establish a structure to allow the Office of Education, Centers and Mission Directorates to implement a strategically integrated portfolio (5) Expand the charter of the Education Coordinating Committee to enable deliberate Education Program design (6) Improve communication to inspire learners
Human Exploration Framework Team (HEFT) was formulated to create a decision framework for human space exploration that drives out the knowledge, capabilities and infrastructure NASA needs to send people to explore multiple destinations in the Solar System in an efficient, sustainable way. The specific goal is to generate an initial architecture that can evolve into a long term, enterprise-wide architecture that is the basis for a robust human space flight enterprise. This paper will discuss the initial HEFT activity which focused on starting up the cross-agency team, getting it functioning, developing a comprehensive development and analysis process and conducting multiple iterations of the process. The outcome of this process will be discussed including initial analysis of capabilities and missions for at least two decades, keeping Mars as the ultimate destination. Details are provided on strategies that span a broad technical and programmatic trade space, are analyzed against design reference missions and evaluated against a broad set of figures of merit including affordability, operational complexity, and technical and programmatic risk.
The Goddard DISC has generated products derived from AIRS/AMSU-A observations, starting from September 2002 when the AIRS instrument became stable, using the AIRS Science Team Version-5 retrieval algorithm. The AIRS Science Team Version-6 retrieval algorithm will be finalized in September 2011. This paper describes some of the significant improvements contained in the Version-6 retrieval algorithm, compared to that used in Version-5, with an emphasis on the improvement of atmospheric temperature profiles, ocean and land surface skin temperatures, and ocean and land surface spectral emissivities. AIRS contains 2378 spectral channels covering portions of the spectral region 650 cm(sup -1) (15.38 micrometers) - 2665 cm(sup -1) (3.752 micrometers). These spectral regions contain significant absorption features from two CO2 absorption bands, the 15 micrometers (longwave) CO2 band, and the 4.3 micrometers (shortwave) CO2 absorption band. There are also two atmospheric window regions, the 12 micrometer - 8 micrometer (longwave) window, and the 4.17 micrometer - 3.75 micrometer (shortwave) window. Historically, determination of surface and atmospheric temperatures from satellite observations was performed using primarily observations in the longwave window and CO2 absorption regions. According to cloud clearing theory, more accurate soundings of both surface skin and atmospheric temperatures can be obtained under partial cloud cover conditions if one uses observations in longwave channels to determine coefficients which generate cloud cleared radiances R(sup ^)(sub i) for all channels, and uses R(sup ^)(sub i) only from shortwave channels in the determination of surface and atmospheric temperatures. This procedure is now being used in the AIRS Version-6 Retrieval Algorithm. Results are presented for both daytime and nighttime conditions showing improved Version-6 surface and atmospheric soundings under partial cloud cover.
This document describes some of the histor y and uses of simulation systems and processes for the training and evaluation of Launch Processing, Mission Control, and Mission Management teams. It documents some of the types of simulations that are used at Kennedy Space Center (KSC) today and that could be utilized (and possibly enhanced) for future launch vehicles. This article is intended to provide an initial baseline for further research into simulation for launch team training in the near future.
NASA's Human Space Flight Architecture Team (HAT) is a multi-disciplinary, cross-agency study team that conducts strategic analysis of integrated development approaches for human and robotic space exploration architectures. During each analysis cycle, HAT iterates and refines the definition of design reference missions (DRMs), which inform the definition of a set of integrated capabilities required to explore multiple destinations. An important capability identified in this capability-driven approach is habitation, which is necessary for crewmembers to live and work effectively during long duration transits to and operations at exploration destinations beyond Low Earth Orbit (LEO). This capability is captured by an element referred to as the Deep Space Habitat (DSH), which provides all equipment and resources for the functions required to support crew safety, health, and work including: life support, food preparation, waste management, sleep quarters, and housekeeping.The purpose of this paper is to describe the design of the DSH capable of supporting crew during exploration missions. First, the paper describes the functionality required in a DSH to support the HAT defined exploration missions, the parameters affecting its design, and the assumptions used in the sizing of the habitat. Then, the process used for arriving at parametric sizing estimates to support additional HAT analyses is detailed. Finally, results from the HAT Cycle C DSH sizing are presented followed by a brief description of the remaining design trades and technological advancements necessary to enable the exploration habitation capability.
AIRS/AMSU is the state of the art infrared and microwave atmospheric sounding system flying aboard EOS Aqua. The Goddard DISC has analyzed AIRS/AMSU observations, covering the period September 2002 until the present, using the AIRS Science Team Version-S retrieval algorithm. These products have been used by many researchers to make significant advances in both climate and weather applications. The AIRS Science Team Version-6 Retrieval, which will become operation in mid-20l2, contains many significant theoretical and practical improvements compared to Version-5 which should further enhance the utility of AIRS products for both climate and weather applications. In particular, major changes have been made with regard to the algOrithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the retrieval procedure; 3) compute Outgoing Longwave Radiation; and 4) determine Quality Control. This paper will describe these advances found in the AIRS Version-6 retrieval algorithm and demonstrate the improvement of AIRS Version-6 products compared to those obtained using Version-5,
Team X is a concurrent engineering team for rapid design and analysis of space mission concepts. It was developed in 1995 by JPL to reduce study time and cost. More than 1100 studies have been completed It is institutionally endorsed and it has been emulated by many institutions. In Concurrent Engineering (i.e., Parallel) diverse specialists work in real time, in the same place, with shared data, to yield an integrated design
AIRS was launched on EOS Aqua in May 2002, together with AMSU-A and HSB (which subsequently failed early in the mission), to form a next generation polar orbiting infrared and microwave atmospheric sounding system. AIRS/AMSU had two primary objectives. The first objective was to provide real-time data products available for use by the operational Numerical Weather Prediction Centers in a data assimilation mode to improve the skill of their subsequent forecasts. The second objective was to provide accurate unbiased sounding products with good spatial coverage that are used to generate stable multi-year climate data sets to study the earth's interannual variability, climate processes, and possibly long-term trends. AIRS/AMSU data for all time periods are now being processed using the state of the art AIRS Science Team Version-6 retrieval methodology. The Suomi-NPP mission was launched in October 2011 as part of a sequence of Low Earth Orbiting satellite missions under the "Joint Polar Satellite System" (JPSS). NPP carries CrIS and ATMS, which are advanced infra-red and microwave atmospheric sounders that were designed as follow-ons to the AIRS and AMSU instruments. The main objective of this work is to assess whether CrIS/ATMS will be an adequate replacement for AIRS/AMSU from the perspective of the generation of accurate and consistent long term climate data records, or if improved instruments should be developed for future flight. It is critical for CrIS/ATMS to be processed using an algorithm similar to, or at least comparable to, AIRS Version-6 before such an assessment can be made. We have been conducting research to optimize products derived from CrIS/ATMS observations using a scientific approach analogous to the AIRS Version-6 retrieval algorithm. Our latest research uses Version-5.70 of the CrIS/ATMS retrieval algorithm, which is otherwise analogous to AIRS Version-6, but does not yet contain the benefit of use of a Neural-Net first guess start-up system which significantly improved results of AIRS Version-6. Version-5.70 CrIS/ATMS temperature profile and surface skin temperature retrievals are of very good quality, and are better than AIRS Version-5 retrievals, but are still significantly poorer than those of AIRS Version-6. CrIS/ATMS retrievals should improve when a Neural-Net start-up system is ready for use. We also examined CrIS/ATMS retrievals generated by NOAA using their NUCAPS retrieval algorithm, which is based on earlier versions of the AIRS Science Team retrieval algorithms. We show that the NUCAPS algorithm as currently configured is not well suited for climate monitoring purposes.
The AIRS Science Team Version-6 AIRS/AMSU retrieval algorithm is now operational at the Goddard DISC. AIRS Version-6 level-2 products are generated near real-time at the Goddard DISC and all level-2 and level-3 products are available starting from September 2002. This paper describes some of the significant improvements in retrieval methodology contained in the Version-6 retrieval algorithm compared to that previously used in Version-5. In particular, the AIRS Science Team made major improvements with regard to the algorithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the cloud clearing and retrieval procedures; and 3) derive error estimates and use them for Quality Control. Significant improvements have also been made in the generation of cloud parameters. In addition to the basic AIRS/AMSU mode, Version-6 also operates in an AIRS Only (AO) mode which produces results almost as good as those of the full AIRS/AMSU mode. This paper also demonstrates the improvements of some AIRS Version-6 and Version-6 AO products compared to those obtained using Version-5.