{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/44930"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/44930","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Development of astronaut reorientation methods : a computational and experimental study","abstract":"Past spaceflight missions have shown that astronauts adapt their motor-control strategies to the microgravity environment. Even though astronauts undergo hundreds of training hours, the strategies for locomotion and orientation are not specifically prescribed. The majority of an astronaut's motion-control strategies are developed underwater. While underwater training can be beneficial in certain aspects, such as learning which orientations an astronaut will encounter and becoming familiar with task timelines, it is not effective for self-learned motor-control strategies. Further, the development of unfamiliar tasks, such as reorienting without external forces, will most likely not occur naturally. Self-rotations -- human-body rotations without external torques -- are not only helpful for reducing adaptation time, but can be a crucial safety countermeasure during extravehicular activity. In this thesis, computational and experimental methods are developed to create and analyze astronaut reorientation methods. The computational development of control methods for human motion planning offers a novel way to provide astronauts with maneuvers that are difficult to obtain experimentally in Earth gravity (1-G). Control of human-body dynamics can be posed as a motion-planning problem for which many different solution methods exist. This research considers two different frameworks -- quantized control and optimal control. The quantized control method permits the development of complete maneuvers that are appropriate for humans to perform in high-stress situations by defining a set of specific finite-time trajectories called motion primitives. The implementation of an optimal control method allows for the refinement and further understanding of maneuver characteristics with an emphasis on how the central nervous system controls motion.","abstract_html":"Past spaceflight missions have shown that astronauts adapt their motor-control strategies to the microgravity environment. Even though astronauts undergo hundreds of training hours, the strategies for locomotion and orientation are not specifically prescribed. The majority of an astronaut's motion-control strategies are developed underwater. While underwater training can be beneficial in certain aspects, such as learning which orientations an astronaut will encounter and becoming familiar with task timelines, it is not effective for self-learned motor-control strategies. Further, the development of unfamiliar tasks, such as reorienting without external forces, will most likely not occur naturally. Self-rotations -- human-body rotations without external torques -- are not only helpful for reducing adaptation time, but can be a crucial safety countermeasure during extravehicular activity. In this thesis, computational and experimental methods are developed to create and analyze astronaut reorientation methods. The computational development of control methods for human motion planning offers a novel way to provide astronauts with maneuvers that are difficult to obtain experimentally in Earth gravity (1-G). Control of human-body dynamics can be posed as a motion-planning problem for which many different solution methods exist. This research considers two different frameworks -- quantized control and optimal control. The quantized control method permits the development of complete maneuvers that are appropriate for humans to perform in high-stress situations by defining a set of specific finite-time trajectories called motion primitives. The implementation of an optimal control method allows for the refinement and further understanding of maneuver characteristics with an emphasis on how the central nervous system controls motion.","abstract_has_math":false,"creators":["Stirling, Leia Abigail"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.","school":null,"contributors":[],"advisors":["Karen Willcox."],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008","date_published":"2008","updated_at":"2026-07-22T22:21:49Z","subjects":["Aeronautics and Astronautics."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/44930","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Karen Willcox."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. 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They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/44930"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2008.","This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.","Includes bibliographical references (p. 143-150)."]},{"key":"dc:description.abstract","label":"Abstract","values":["Past spaceflight missions have shown that astronauts adapt their motor-control strategies to the microgravity environment. Even though astronauts undergo hundreds of training hours, the strategies for locomotion and orientation are not specifically prescribed. The majority of an astronaut's motion-control strategies are developed underwater. While underwater training can be beneficial in certain aspects, such as learning which orientations an astronaut will encounter and becoming familiar with task timelines, it is not effective for self-learned motor-control strategies. Further, the development of unfamiliar tasks, such as reorienting without external forces, will most likely not occur naturally. Self-rotations -- human-body rotations without external torques -- are not only helpful for reducing adaptation time, but can be a crucial safety countermeasure during extravehicular activity. In this thesis, computational and experimental methods are developed to create and analyze astronaut reorientation methods. The computational development of control methods for human motion planning offers a novel way to provide astronauts with maneuvers that are difficult to obtain experimentally in Earth gravity (1-G). Control of human-body dynamics can be posed as a motion-planning problem for which many different solution methods exist. This research considers two different frameworks -- quantized control and optimal control. The quantized control method permits the development of complete maneuvers that are appropriate for humans to perform in high-stress situations by defining a set of specific finite-time trajectories called motion primitives. The implementation of an optimal control method allows for the refinement and further understanding of maneuver characteristics with an emphasis on how the central nervous system controls motion.","(cont.) Human rotation experiments provide further insight into the complexity of self-rotation techniques and a way to study the effects of training in a rigorous and realistic manner."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Development of astronaut reorientation methods : a computational and experimental study"]}]}],"canonical_facts":{"dc:contributor.advisor":["Karen Willcox."],"dc:contributor.department":["Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics."],"dc:contributor.other":["Massachusetts Institute of Technology. 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While underwater training can be beneficial in certain aspects, such as learning which orientations an astronaut will encounter and becoming familiar with task timelines, it is not effective for self-learned motor-control strategies. Further, the development of unfamiliar tasks, such as reorienting without external forces, will most likely not occur naturally. Self-rotations -- human-body rotations without external torques -- are not only helpful for reducing adaptation time, but can be a crucial safety countermeasure during extravehicular activity. In this thesis, computational and experimental methods are developed to create and analyze astronaut reorientation methods. The computational development of control methods for human motion planning offers a novel way to provide astronauts with maneuvers that are difficult to obtain experimentally in Earth gravity (1-G). Control of human-body dynamics can be posed as a motion-planning problem for which many different solution methods exist. This research considers two different frameworks -- quantized control and optimal control. The quantized control method permits the development of complete maneuvers that are appropriate for humans to perform in high-stress situations by defining a set of specific finite-time trajectories called motion primitives. The implementation of an optimal control method allows for the refinement and further understanding of maneuver characteristics with an emphasis on how the central nervous system controls motion.","(cont.) Human rotation experiments provide further insight into the complexity of self-rotation techniques and a way to study the effects of training in a rigorous and realistic manner."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/44930"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Aeronautics and Astronautics."],"dc:title":["Development of astronaut reorientation methods : a computational and experimental study"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:49Z"}