{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/99349"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/99349","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Design and control of a compact aerial manipulation system with a Delta-type parallel robot","abstract":"This thesis presents the design, modeling, and control of a quadcopter equipped with a Delta-type parallel manipulator. Such systems present demanding challenges in both control theory and task planning, which are addressed with novel mechanical features, modern flight controllers, and optimal trajectory generation. They are primarily designed for versatile indoor pick-and-place tasks where the characteristics of the proposed solution introduce useful kinematic properties. We explore these traits to address critical deficiencies found in previous approaches. First, we introduce and discuss the mechanical design of the coupled system. Second, we derive the kinematics and dynamic relationships between all bodies. Third, we develop the flight controller, where baseline, feedforward, and adaptive components are combined and used in unison with an optimal trajectory generation algorithm. Finally, we present simulation results which reflect the feasibility of the concepts.","abstract_html":"This thesis presents the design, modeling, and control of a quadcopter equipped with a Delta-type parallel manipulator. Such systems present demanding challenges in both control theory and task planning, which are addressed with novel mechanical features, modern flight controllers, and optimal trajectory generation. They are primarily designed for versatile indoor pick-and-place tasks where the characteristics of the proposed solution introduce useful kinematic properties. We explore these traits to address critical deficiencies found in previous approaches. First, we introduce and discuss the mechanical design of the coupled system. Second, we derive the kinematics and dynamic relationships between all bodies. Third, we develop the flight controller, where baseline, feedforward, and adaptive components are combined and used in unison with an optimal trajectory generation algorithm. Finally, we present simulation results which reflect the feasibility of the concepts.","abstract_has_math":false,"creators":["Barsi Haberfeld, Gabriel"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Mechanical Engineering","degree_department":null,"school":null,"contributors":["Hovakimyan, Naira"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-03-13T15:48:47Z","date_published":"2018-03-13T15:48:47Z","updated_at":"2026-07-22T22:24:37Z","subjects":["Robotics","Dynamics","Quadrotor","Robust adaptive control","Optimal trajectory generation"],"languages":["en"],"rights":["Copyright 2017 Gabriel Barsi Haberfeld"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/99349","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hovakimyan, Naira"]},{"key":"dc:creator","label":"Author","values":["Barsi Haberfeld, Gabriel"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-03-13T15:48:47Z","2017-12-05","2017-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Robotics","Dynamics","Quadrotor","Robust adaptive control","Optimal trajectory generation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2017 Gabriel Barsi Haberfeld"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/99349"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This thesis presents the design, modeling, and control of a quadcopter equipped with a Delta-type parallel manipulator. Such systems present demanding challenges in both control theory and task planning, which are addressed with novel mechanical features, modern flight controllers, and optimal trajectory generation. They are primarily designed for versatile indoor pick-and-place tasks where the characteristics of the proposed solution introduce useful kinematic properties. We explore these traits to address critical deficiencies found in previous approaches. First, we introduce and discuss the mechanical design of the coupled system. Second, we derive the kinematics and dynamic relationships between all bodies. Third, we develop the flight controller, where baseline, feedforward, and adaptive components are combined and used in unison with an optimal trajectory generation algorithm. Finally, we present simulation results which reflect the feasibility of the concepts.","Submission original under an indefinite embargo labeled 'Open Access'. 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They are primarily designed for versatile indoor pick-and-place tasks where the characteristics of the proposed solution introduce useful kinematic properties. We explore these traits to address critical deficiencies found in previous approaches. First, we introduce and discuss the mechanical design of the coupled system. Second, we derive the kinematics and dynamic relationships between all bodies. Third, we develop the flight controller, where baseline, feedforward, and adaptive components are combined and used in unison with an optimal trajectory generation algorithm. Finally, we present simulation results which reflect the feasibility of the concepts.","Submission original under an indefinite embargo labeled 'Open Access'. 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