{"id":{"repo_id":"texas","oai_identifier":"oai:repositories.lib.utexas.edu:2152/31978"},"canonical_url":"https://search.dev.ndltd.org/etd/texas/oai:repositories.lib.utexas.edu:2152/31978","repository":{"repo_id":"texas","name":"University of Texas","base_url":"https://repositories.lib.utexas.edu/server/oai/request"},"display":{"title":"Industrial automation and control in hazardous nuclear environments","abstract":"This report discusses the design and implementation of an automated system for use in geometrically-constrained, hazardous glovebox environments. This system’s purpose is to reduce a hemispherical plutonium pit into smaller pieces that fit inside of a crucible. The size reduction of plutonium pits supports stockpile stewardship efforts by the United States Department of Energy. The automation of this process increases the safety of radiation workers by handling radioactive nuclear material. This decreases glovebox worker dose and exposure to tools, sharps, and fines. This effort examines the hardware and software framework developed to support the use of a Port Deployed Manipulator (PDM) for a contact task. This research effort uses a 7 Degree-of-Freedom (DOF) PDM and a micropunch to reduce hemispherical pit surrogates. Formulation of the material reduction execution algorithm involved addressing a variety of topics related to industrial automation: 1. Collision detection and object recognition based on user-specified parameters. 2. Joint torque monitoring 3. Online motion planning for contact tasks 4. Object-in-hand industrial manufacturing 5. Grasping and handling of nuclear material 6. Software compliance via robust nonlinear control methods A high-bandwidth collision detection algorithm involving joint torque monitoring was developed to increase robot safety during operation. The motion planning algorithm developed for this effort takes variable geometric properties to be used with a range of hemishells. The algorithm’s feasibility was validated on a hardware test bed in a laboratory setting. Hardware cold tests conclude that mechanical compliance is sufficient for task completion. However, software compliance would increase performance, ef- ficiency, and safety during task execution. Two different nonlinear force control laws (feedback linearization and sliding mode control) that minimize object shear forces were developed using a simplified material reduction simulation. It is recommended that glovebox automation research continue to increase worker safety throughout the DOE complex.","abstract_html":"This report discusses the design and implementation of an automated system for use in geometrically-constrained, hazardous glovebox environments. This system’s purpose is to reduce a hemispherical plutonium pit into smaller pieces that fit inside of a crucible. The size reduction of plutonium pits supports stockpile stewardship efforts by the United States Department of Energy. The automation of this process increases the safety of radiation workers by handling radioactive nuclear material. This decreases glovebox worker dose and exposure to tools, sharps, and fines. This effort examines the hardware and software framework developed to support the use of a Port Deployed Manipulator (PDM) for a contact task. This research effort uses a 7 Degree-of-Freedom (DOF) PDM and a micropunch to reduce hemispherical pit surrogates. Formulation of the material reduction execution algorithm involved addressing a variety of topics related to industrial automation: 1. Collision detection and object recognition based on user-specified parameters. 2. Joint torque monitoring 3. Online motion planning for contact tasks 4. Object-in-hand industrial manufacturing 5. Grasping and handling of nuclear material 6. Software compliance via robust nonlinear control methods A high-bandwidth collision detection algorithm involving joint torque monitoring was developed to increase robot safety during operation. The motion planning algorithm developed for this effort takes variable geometric properties to be used with a range of hemishells. The algorithm’s feasibility was validated on a hardware test bed in a laboratory setting. Hardware cold tests conclude that mechanical compliance is sufficient for task completion. However, software compliance would increase performance, ef- ficiency, and safety during task execution. Two different nonlinear force control laws (feedback linearization and sliding mode control) that minimize object shear forces were developed using a simplified material reduction simulation. It is recommended that glovebox automation research continue to increase worker safety throughout the DOE complex.","abstract_has_math":false,"creators":["Peterson, Clinton II Dean"],"institution":"The University of Texas at Austin","degree_name":"Master of Science in Engineering","degree_level":"Masters","degree_discipline":"Mechanical Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Landsberger, Sheldon","Pryor, Mitchell Wayne"],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-05","date_published":"2015-05","updated_at":"2026-07-24T05:01:18Z","subjects":["Industrial","Automation","Robotics","Nuclear"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["doi:10.15781/T25P75"],"render_values":[{"text":"doi:10.15781/T25P75","href":"https://doi.org/10.15781/T25P75","code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2152/31978","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Landsberger, Sheldon","Pryor, Mitchell Wayne"]},{"key":"dc:creator","label":"Author","values":["Peterson, Clinton II Dean"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-10-26T20:39:40Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2015-10-26T20:39:40Z"]},{"key":"dc:date.issued","label":"Date","values":["2015-05"]},{"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 in Engineering"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Texas at Austin"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Industrial","Automation","Robotics","Nuclear"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["doi:10.15781/T25P75"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/2152/31978"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["text"]},{"key":"dc:description.abstract","label":"Abstract","values":["This report discusses the design and implementation of an automated system for use in geometrically-constrained, hazardous glovebox environments. This system’s purpose is to reduce a hemispherical plutonium pit into smaller pieces that fit inside of a crucible. The size reduction of plutonium pits supports stockpile stewardship efforts by the United States Department of Energy. The automation of this process increases the safety of radiation workers by handling radioactive nuclear material. This decreases glovebox worker dose and exposure to tools, sharps, and fines. This effort examines the hardware and software framework developed to support the use of a Port Deployed Manipulator (PDM) for a contact task. This research effort uses a 7 Degree-of-Freedom (DOF) PDM and a micropunch to reduce hemispherical pit surrogates. Formulation of the material reduction execution algorithm involved addressing a variety of topics related to industrial automation: 1. Collision detection and object recognition based on user-specified parameters. 2. Joint torque monitoring 3. Online motion planning for contact tasks 4. Object-in-hand industrial manufacturing 5. Grasping and handling of nuclear material 6. Software compliance via robust nonlinear control methods A high-bandwidth collision detection algorithm involving joint torque monitoring was developed to increase robot safety during operation. The motion planning algorithm developed for this effort takes variable geometric properties to be used with a range of hemishells. The algorithm’s feasibility was validated on a hardware test bed in a laboratory setting. Hardware cold tests conclude that mechanical compliance is sufficient for task completion. However, software compliance would increase performance, ef- ficiency, and safety during task execution. Two different nonlinear force control laws (feedback linearization and sliding mode control) that minimize object shear forces were developed using a simplified material reduction simulation. It is recommended that glovebox automation research continue to increase worker safety throughout the DOE complex."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Industrial automation and control in hazardous nuclear environments"]}]}],"canonical_facts":{"dc:contributor.advisor":["Landsberger, Sheldon","Pryor, Mitchell Wayne"],"dc:creator":["Peterson, Clinton II Dean"],"dc:date.accessioned":["2015-10-26T20:39:40Z"],"dc:date.available":["2015-10-26T20:39:40Z"],"dc:date.issued":["2015-05"],"dc:description":["text"],"dc:description.abstract":["This report discusses the design and implementation of an automated system for use in geometrically-constrained, hazardous glovebox environments. This system’s purpose is to reduce a hemispherical plutonium pit into smaller pieces that fit inside of a crucible. The size reduction of plutonium pits supports stockpile stewardship efforts by the United States Department of Energy. The automation of this process increases the safety of radiation workers by handling radioactive nuclear material. This decreases glovebox worker dose and exposure to tools, sharps, and fines. This effort examines the hardware and software framework developed to support the use of a Port Deployed Manipulator (PDM) for a contact task. This research effort uses a 7 Degree-of-Freedom (DOF) PDM and a micropunch to reduce hemispherical pit surrogates. Formulation of the material reduction execution algorithm involved addressing a variety of topics related to industrial automation: 1. Collision detection and object recognition based on user-specified parameters. 2. Joint torque monitoring 3. Online motion planning for contact tasks 4. Object-in-hand industrial manufacturing 5. Grasping and handling of nuclear material 6. Software compliance via robust nonlinear control methods A high-bandwidth collision detection algorithm involving joint torque monitoring was developed to increase robot safety during operation. The motion planning algorithm developed for this effort takes variable geometric properties to be used with a range of hemishells. The algorithm’s feasibility was validated on a hardware test bed in a laboratory setting. Hardware cold tests conclude that mechanical compliance is sufficient for task completion. However, software compliance would increase performance, ef- ficiency, and safety during task execution. Two different nonlinear force control laws (feedback linearization and sliding mode control) that minimize object shear forces were developed using a simplified material reduction simulation. It is recommended that glovebox automation research continue to increase worker safety throughout the DOE complex."],"dc:format.mimetype":["application/pdf"],"dc:identifier":["doi:10.15781/T25P75"],"dc:identifier.uri":["http://hdl.handle.net/2152/31978"],"dc:language.iso":["en"],"dc:subject":["Industrial","Automation","Robotics","Nuclear"],"dc:title":["Industrial automation and control in hazardous nuclear environments"],"dc:type":["Thesis"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["Masters"],"thesis:degree_name":["Master of Science in Engineering"],"thesis:institution_name":["The University of Texas at Austin"]},"updated_at":"2026-07-24T05:01:18Z"}