Evaluation of a Surface Exploration Traverse Analysis and Navigation Tool
Name
Newman_Evaluation of a surface.pdf
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471.71 KB
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Adobe PDF
Checksum (MD5)
0211fc14324a5580a7aefc08ff5100cd
Author(s)
Gilkey, Andrea L.
Galvan, Raquel Christine
Johnson, Aaron William
Kobrick, Ryan L.
Hoffman, Jeffrey A.
Melo, Paulo L.
Newman, Dava
Date Issued
July 2011
Journal
Proceedings of the 41st International Conference on Environmental Systems
Publisher
American Institute of Aeronautics and Astronautics
Citation
Gilkey, Andrea, Ryan Kobrick, Raquel Galvan, Aaron Johnson, Jeffrey Hoffman, Dava Newman, and Paulo Melo. “Evaluation of a Surface Exploration Traverse Analysis and Navigation Tool.” In 41st International Conference on Environmental Systems, Portland, Oregon. American Institute of Aeronautics and Astronautics, 2011.
Version
Author's final manuscript
Abstract
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.
MIT Department
MIT-Portugal Program
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.2514/6.2011-5181
