Evaluation of a Surface Exploration Traverse Analysis and Navigation Tool

SEXTANT is an extravehicular activity (EVA) mission planner tool developed in MATLAB, which computes the most efficient path between waypoints across a planetary surface. The traverse efficiency can be optimized around path distance, time, or explorer energy consumption. The user can select waypoints and the time spent at each, and can visualize a 3D map of the optimal path. Once the optimal path is generated, the thermal load on suited astronauts or solar power generation of rovers is displayed, along with the total traverse time and distance traveled. A field study was conducted at the Mars Desert Research Station (MDRS) in Utah to see if there was a statistical difference between the SEXTANT-determined energy consumption, time, or distance of EVA traverses and the actual output values. Actual traverse time was significantly longer than SEXTANT-predicted EVA traverse time (n=6, p<0.01), traverse distance was not significantly different than SEXTANT-predicted distance, and explorer energy consumption was significantly greater than SEXTANT-predicted energy consumption (n=5, p<0.01). A second study was done to see if mission re-planning, or contingency planning, was faster and less work when using SEXTANT in the habitat or in the field using an iPad. Time and workload measurements were collected for each subject under both conditions. Contingency planning in the habitat was not significantly different than contingency planning in the field. There was no significant workload difference when contingency planning in either location, however there was a trend that suggested contingency planning was faster in the habitat (n=3, p=0.07). Every subject commented that it was a hassle to carry the mission planner in the field and it was difficult to see the screen in the sunlight. To determine if gloves were a factor in the difference between mission re-planning time, subjects were asked to plan a contingency indoors with and without gloves. Performance and workload were not significantly different when re-planning with and without the gloves. The SEXTANT mission planner will continue to be improved according to the results and the recommendations of subjects in this study.United States. National Aeronautics and Space Administration (NASA Astrobiology Institute)Massachusetts Space Grant Consortiu

Panorama - a software maintenance tool

Much of the effort in software maintenance is spent on finding relevant information and on program comprehension. Of the several challenges encountered during this process, some are: a) inadequate documentation, b) the developer doing the maintenance activity may not be the one who actually developed it and may be unfamiliar with the application domain (in addition to the unfamiliar code), c) information overload, and d) the relevant code may be scattered across multiple files of different types making it harder to find. Existing documentation in the form of Javadoc is inadequate in providing a global view of the working of the software. Panorama, a java based Eclipse plug-in, was developed to facilitate maintenance activities by providing mechanisms to document and to view expert knowledge and relevant code in the form of a concern. Some features of Panorama are: a code tracing feature that allows the expert to quickly find (so he can document it) lines of code executed in carrying out a function, a concern management feature that allows the expert to create and organize concern information in a hierarchical manner, a concern visualization and context management feature that helps the maintainer to handle information overload by allowing him to switch between contexts, an enhanced user-interface that helps the maintainer to easily navigate between relevant contexts and codes. Panorama also provides a Javadoc -like documentation of cross-cutting concerns that supplement existing Javadoc documentation to provide comprehensive information about the software. In a case study done to validate the usefulness of our tool, Panorama was used to document the SAVER software (a VB.NET based fairly large GIS software with 26,704 executable lines of code that is being actively used by the Iowa Department of Transportation to analyze automobile crashes over a period of time). SAVER has been undergoing continual bug-fixes and enhancement activities - and preliminary studies indicate that the supplementary documentation provided by Panorama has proven beneficial

Sextant: Visualizing time-evolving linked geospatial data

The linked open data cloud is constantly evolving as datasets get continuously updated with newer versions. As a result, representing, querying, and visualizing the temporal dimension of linked data is crucial. This is especially important for geospatial datasets that form the backbone of large scale open data publication efforts in many sectors of the economy (e.g., the public sector, the Earth Observation sector). Although there has been some work on the representation and querying of linked geospatial data that change over time, to the best of our knowledge, there is currently no tool that offers spatio-temporal visualization of such data. This is in contrast with the existence of many tools for the visualization of the temporal evolution of geospatial data in the GIS area. In this article, we present Sextant, a Web-based system for the visualization and exploration of time-evolving linked geospatial data and the creation, sharing, and collaborative editing of “temporally-enriched” thematic maps which are produced by combining different sources of such data. We present the architecture of Sextant, give examples of its use and present applications in which we have deployed it

An Integrated Traverse Planner and Analysis Tool for Planetary Exploration

Future planetary explorations will require surface traverses of unprecedented frequency, length, and duration. As a result, there is need for exploration support tools to maximize productivity, scientific return, and safety. The Massachusetts Institute of Technology is currently developing such a system, called the Surface Exploration Traverse Analysis and Navigation Tool (SEXTANT). The goal of this system is twofold: to allow for realistic simulations of traverses in order to assist with hardware design, and to give astronauts an aid that will allow for more autonomy in traverse planning and re-planning. SEXTANT is a MATLAB-based tool that incorporates a lunar elevation model created from data from the Lunar Orbiter Laser Altimeter instrument aboard the Lunar Reconnaissance Orbiter spacecraft. To assist in traverse planning, SEXTANT determines the most efficient path across a planetary surface for astronauts or transportation rovers between user-specified Activity Points. The path efficiency is derived from any number of metrics: the traverse distance, traverse time, or the explorer’s energy consumption. The generated path, display of traverse obstacles, and selection of Activity Points are visualized in a 3D mapping interface. After a traverse has been planned, SEXTANT is capable of computing the most efficient path back home, or “walkback”, from any point along the traverse – an important capability for emergency operations. SEXTANT also has the ability to determine shadowed and sunlit areas along a lunar traverse. This data is used to compute the thermal load on suited astronauts and the solar power generation capacity of rovers over the entire traverse. These both relate directly to the explorer’s consumables, which place strict constraints on the traverse. This paper concludes by presenting three example traverses, detailing how SEXTANT can be used to plan and modify paths for both explorer types.Massachusetts Institute of Technology (Donald W. Douglas Fellowship)National Space Biomedical Research Institute (Grant HFP00003

Conceptual design for Mobile Geological Laboratory position and heading fix system

Conceptual design of position fixing system for Mobile Geological Laboratory in Lunar Mobile Laboratory simulatio

Application of advanced technology to space automation

Automated operations in space provide the key to optimized mission design and data acquisition at minimum cost for the future. The results of this study strongly accentuate this statement and should provide further incentive for immediate development of specific automtion technology as defined herein. Essential automation technology requirements were identified for future programs. The study was undertaken to address the future role of automation in the space program, the potential benefits to be derived, and the technology efforts that should be directed toward obtaining these benefits

Metabolic Cost of Traverses on Future Planetary Extra Vehicular Activities

La despesa energètica per metabolisme (Metabolic Rate, MR) és una magnitud fonamental en els passejos espacials. La predicció de la despesa energètica durant una travessia futura en condicions específiques de velocitat, pendent, gravetat i vestit espacial pot proporcionar informació valuosa sobre la quantitat de consumibles necessaris (principalment oxigen i aigua), la ruta més adequada per assolir els objectius de la missió, a l'igual que obtenir informació sobre la càrrega de treball, la fatiga acumulada i les possibles lesions. En aquest projecte, vaig fer una descripció general dels mètodes i models existents desenvolupats per estudiar el cost energètic per desplaçar-se a peu, així com els resultats biomèdics de les missions Apol·lo i el desenvolupament actual de vestits espacials per a futures missions. Vaig explorar la possibilitat d'utilitzar mètodes predictius basats en aprenentatge màquina per determinar MR com una forma de millorar els models actuals tant per a les activitats extravehiculars (EVA) com per als recorreguts de la Terra. També vaig fer un prototip de l'eina predictiva i la vaig provar amb dades simulades. L'eina pot integrar-se en una altra aplicació o usar-se com una API per HTTP.El gasto energético por metabolismo (Metabolic Rate, MR) es una magnitud fundamental en los paseos espaciales. La predicción del gasto energético durante una travesía futura en condiciones específicas de velocidad, pendiente, gravedad y traje espacial puede proporcionar información valiosa sobre la cantidad de consumibles necesarios (principalmente oxígeno y agua), la ruta más adecuada para lograr los objetivos de la misión, al igual que obtener información sobre la carga de trabajo, la fatiga acumulada y las posibles lesiones. En este proyecto, hice una descripción general de los métodos y modelos existentes desarrollados para estudiar el coste energético para desplazarse a pie, así como los resultados biomédicos de las misiones Apolo y el desarrollo actual de trajes espaciales para futuras misiones. Exploré la posibilidad de utilizar métodos predictivos basados en aprendizaje máquina para determinar MR como una forma de mejorar los modelos actuales tanto para las actividades extravehiculares (EVA) como para los recorridos de la Tierra. También hice un prototipo de la herramienta predictiva y la probé con datos simulados. La herramienta puede integrarse en otra aplicación o usarse como una API por HTTP.Metabolic Rate (MR) is a fundamental magnitude during surface exploration traverses. Predicting energy expenditure during an upcoming traverse under specific conditions of speed, slope, gravity and suit characteristics can provide valuable information about the supply of consumables needed (i.e. oxygen and water), the most appropriate path to accomplish the exploration objectives, as well as information about workload, fatigue, and potential injuries. In this project I did an overview of the existing methods and models developed to study metabolic rate of traverse, as well as the biomedical results of Apollo Missions and the current state of the art in the development of spacesuits. I considered the use of machine learning predicting methods to determine MR as a way of improving current models for both Extravehicular Activities (EVAs) and Earth traverses. I also made a prototype of a MR predictive tool and tested it with simulated data. The tool can be integrated into another app or used as a HTTP Application Programing Interface (API).Outgoin

Managing big, linked, and open earth-observation data: Using the TELEIOS/LEO software stack

Big Earth-observation (EO) data that are made freely available by space agencies come from various archives. Therefore, users trying to develop an application need to search within these archives, discover the needed data, and integrate them into their application. In this article, we argue that if EO data are published using the linked data paradigm, then the data discovery, data integration, and development of applications becomes easier. We present the life cycle of big, linked, and open EO data and show how to support their various stages using the software stack developed by the European Union (EU) research projects TELEIOS and the Linked Open EO Data for Precision Farming (LEO). We also show how this stack of tools can be used to implement an operational wildfire-monitoring service

The MELODIES project: integrating diverse data using Linked Data and cloud computing

We present an overview of the MELODIES project, which is developing new data-intensive environmental services based on data from Earth Observation satellites, government databases, national and European agencies and more. We focus here on the capabilities and benefits of the project’s “technical platform”, which applies cloud computing and Linked Data technologies to enable the development of these services, providing flexibility and scalability