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Neville Hogan. Nah, Moses C. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering 2020-09-03T17:47:53Z 2020-09-03T17:47:53Z 2020 2020 https://hdl.handle.net/1721.1/127121 1191836862 Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, May, 2020 Cataloged from the official PDF of thesis. Includes bibliographical references (pages 127-133). Human dexterity far exceeds that of modern robots, despite a much slower neuromuscular system. Understanding how this is accomplished may lead to improved robot control. The slow neuromuscular system of humans implies that prediction based on some form of internal model plays a prominent role. However, the nature of the model itself remains unclear. To address this problem, we focused on one of the most complex and exotic tools humans can manipulate -- a whip. We tested (in simulation) whether a distant target could be reached with a whip using a (small) number of dynamic primitives, whose parameters could be learned through optimization. This approach was able to manage the complexity of an (extremely) high degree-of-freedom system and discovered the optimal parameters of the upper-limb movement that achieved the task. A detailed model of the whip dynamics was not needed for this approach, which thereby significantly relieved the computational burden of task representation and performance optimization. These results support our hypothesis that composing control using dynamic motor primitives may be a strategy which humans use to enable their remarkable dexterity. A similar approach may contribute to improved robot control.. by Moses C. Nah. S.M. S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering 133 pages eng Massachusetts Institute of Technology MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582 Mechanical Engineering. Dynamic primitives facilitate manipulating a whip Thesis application/pdf 2020-09-03T17:47:52Z Publication Master MechE unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="d09ccbec-a556-4139-8009-4432ca6e1e19"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Dynamic primitives facilitate manipulating a whip</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2020</PublicationDate> <Authors> <Author> <DisplayName>Nah, Moses C.</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Mechanical Engineering.</Keyword> <Abstract>Human dexterity far exceeds that of modern robots, despite a much slower neuromuscular system. Understanding how this is accomplished may lead to improved robot control. The slow neuromuscular system of humans implies that prediction based on some form of internal model plays a prominent role. However, the nature of the model itself remains unclear. To address this problem, we focused on one of the most complex and exotic tools humans can manipulate -- a whip. We tested (in simulation) whether a distant target could be reached with a whip using a (small) number of dynamic primitives, whose parameters could be learned through optimization. This approach was able to manage the complexity of an (extremely) high degree-of-freedom system and discovered the optimal parameters of the upper-limb movement that achieved the task. A detailed model of the whip dynamics was not needed for this approach, which thereby significantly relieved the computational burden of task representation and performance optimization. These results support our hypothesis that composing control using dynamic motor primitives may be a strategy which humans use to enable their remarkable dexterity. A similar approach may contribute to improved robot control..</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>