{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/25335"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/25335","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Methods and Applications of Controlling Biomimetic Robotic Hands","abstract":"Vast improvements in robotics and wireless communication have made teleoperated robots significantly more prevalent in industry, defense, and research. To help bridge the gap for these robots in the workplace, there has been a tremendous increase in research toward the development of biomimetic robotic hands that can simulate human operators. However, current methods of control are limited in scope and do not adequately represent human muscle memory and skills. The vision of this thesis is to provide a pathway for overcoming these limitations and open an opportunity for development and implementation of a cost effective methodology towards controlling a robotic hand. The first chapter describes the experiments conducted using Flexpoint bend sensors in conjunction with a simple voltage divider to generate a cost-effective data glove that is significantly less expensive than the commercially available alternatives. The data glove was able to provide sensitivity of less than 0.1 degrees. The second chapter describes the molding process for embedding pressure sensors in silicone skin and data acquisition from them to control the robotic hand. The third chapter describes a method for parsing and observing the information from the data glove and translating the relevant control variables to the robotic hand. The fourth chapter focuses on the feasibility of the brain computer interfaces (BCI) and successfully demonstrates the implementation of a simple brain computer interface in controlling a robotic hand.","abstract_html":"Vast improvements in robotics and wireless communication have made teleoperated robots significantly more prevalent in industry, defense, and research. To help bridge the gap for these robots in the workplace, there has been a tremendous increase in research toward the development of biomimetic robotic hands that can simulate human operators. However, current methods of control are limited in scope and do not adequately represent human muscle memory and skills. The vision of this thesis is to provide a pathway for overcoming these limitations and open an opportunity for development and implementation of a cost effective methodology towards controlling a robotic hand. The first chapter describes the experiments conducted using Flexpoint bend sensors in conjunction with a simple voltage divider to generate a cost-effective data glove that is significantly less expensive than the commercially available alternatives. The data glove was able to provide sensitivity of less than 0.1 degrees. The second chapter describes the molding process for embedding pressure sensors in silicone skin and data acquisition from them to control the robotic hand. The third chapter describes a method for parsing and observing the information from the data glove and translating the relevant control variables to the robotic hand. The fourth chapter focuses on the feasibility of the brain computer interfaces (BCI) and successfully demonstrates the implementation of a simple brain computer interface in controlling a robotic hand.","abstract_has_math":false,"creators":["Paluszek, Matthew Alan"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Mechanical Engineering","degree_department":"Mechanical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Priya, Shashank"],"committee_members":["Wicks, Alfred L.","Kurdila, Andrew J."],"year":2014,"date_issued":"2014-02-06","date_published":"2014-02-06","updated_at":"2026-07-22T22:19:39Z","subjects":["humanoid robotics","data glove","brain computer interface","strain sensor","force sensor"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:1990"],"render_values":[{"text":"vt_gsexam:1990","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/25335","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Priya, Shashank"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Wicks, Alfred L.","Kurdila, Andrew J."]},{"key":"dc:contributor.department","label":"Department","values":["Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Paluszek, Matthew Alan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-02-07T09:00:29Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-02-07T09:00:29Z"]},{"key":"dc:date.issued","label":"Date","values":["2014-02-06"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["humanoid robotics","data glove","brain computer interface","strain sensor","force sensor"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:1990"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/25335"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Vast improvements in robotics and wireless communication have made teleoperated robots significantly more prevalent in industry, defense, and research. To help bridge the gap for these robots in the workplace, there has been a tremendous increase in research toward the development of biomimetic robotic hands that can simulate human operators. However, current methods of control are limited in scope and do not adequately represent human muscle memory and skills. The vision of this thesis is to provide a pathway for overcoming these limitations and open an opportunity for development and implementation of a cost effective methodology towards controlling a robotic hand. The first chapter describes the experiments conducted using Flexpoint bend sensors in conjunction with a simple voltage divider to generate a cost-effective data glove that is significantly less expensive than the commercially available alternatives. The data glove was able to provide sensitivity of less than 0.1 degrees. The second chapter describes the molding process for embedding pressure sensors in silicone skin and data acquisition from them to control the robotic hand. The third chapter describes a method for parsing and observing the information from the data glove and translating the relevant control variables to the robotic hand. The fourth chapter focuses on the feasibility of the brain computer interfaces (BCI) and successfully demonstrates the implementation of a simple brain computer interface in controlling a robotic hand."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Methods and Applications of Controlling Biomimetic Robotic Hands"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Priya, Shashank"],"dc:contributor.committeemember":["Wicks, Alfred L.","Kurdila, Andrew J."],"dc:contributor.department":["Mechanical Engineering"],"dc:creator":["Paluszek, Matthew Alan"],"dc:date.accessioned":["2014-02-07T09:00:29Z"],"dc:date.available":["2014-02-07T09:00:29Z"],"dc:date.issued":["2014-02-06"],"dc:description.abstract":["Vast improvements in robotics and wireless communication have made teleoperated robots significantly more prevalent in industry, defense, and research. 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The second chapter describes the molding process for embedding pressure sensors in silicone skin and data acquisition from them to control the robotic hand. The third chapter describes a method for parsing and observing the information from the data glove and translating the relevant control variables to the robotic hand. 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