{"id":{"repo_id":"unr","oai_identifier":"oai:scholarwolf.unr.edu:11714/388"},"canonical_url":"https://search.dev.ndltd.org/etd/unr/oai:scholarwolf.unr.edu:11714/388","repository":{"repo_id":"unr","name":"University of Nevada - Reno","base_url":"https://scholarwolf.unr.edu/server/oai/request"},"display":{"title":"Dynamic Obstacle Avoidance on a Self-balancing Robot Platform","abstract":"Autonomous tasks are increasingly becoming part of our everyday life, whether in a factory floor where robotic manipulators manufacture goods, or when cars acquire the capability of parking themselves. These tasks often involve a human operator that has some high level control over the system. This can lead to situations where the human operator believes that the system is safe, when this might not be the case. This is why robust control algorithms need to be implemented that provide safety guarantees when a mechanical device is teleoperated by a human user. These algorithms can intervene when an unsafe choice is made to protect the operator and the system itself. The challenge that this work specifically focuses upon is dynamic obstacle avoidance by a robotic unit that is guided by a human user. Dynamic obstacles are objects that move in the environment independently from the robot and can potentially raise safety concerns for the robotic platform. In order to detect these obstacles in the environment, sensor data along with some probabilities need to be utilized to infer the magnitude and direction of an object's speed. This project is primarily concerned with this estimation and methods to do this accurately.","abstract_html":"Autonomous tasks are increasingly becoming part of our everyday life, whether in a factory floor where robotic manipulators manufacture goods, or when cars acquire the capability of parking themselves. These tasks often involve a human operator that has some high level control over the system. This can lead to situations where the human operator believes that the system is safe, when this might not be the case. This is why robust control algorithms need to be implemented that provide safety guarantees when a mechanical device is teleoperated by a human user. These algorithms can intervene when an unsafe choice is made to protect the operator and the system itself. The challenge that this work specifically focuses upon is dynamic obstacle avoidance by a robotic unit that is guided by a human user. Dynamic obstacles are objects that move in the environment independently from the robot and can potentially raise safety concerns for the robotic platform. In order to detect these obstacles in the environment, sensor data along with some probabilities need to be utilized to infer the magnitude and direction of an object's speed. This project is primarily concerned with this estimation and methods to do this accurately.","abstract_has_math":false,"creators":["Littlefield, Zakary"],"institution":"University of Nevada, Reno","degree_name":"Computer Science","degree_level":"Honors Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Bekris, Kostas E."],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011","date_published":"2011","updated_at":"2026-07-27T21:47:03Z","subjects":[],"languages":["en_US"],"rights":["In Copyright(All Rights Reserved)"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11714/388","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Bekris, Kostas E."]},{"key":"dc:creator","label":"Author","values":["Littlefield, Zakary"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-01-24T23:08:52Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-01-24T23:08:52Z"]},{"key":"dc:date.issued","label":"Date","values":["2011"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Honors Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Computer Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Nevada, Reno"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright(All Rights Reserved)"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11714/388"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The University of Nevada, Reno Libraries will promptly respond to removal requests related to content that violates intellectual property laws, data protections, or has been uploaded without creator consent. Takedown notices should be directed to our ScholarWolf team (scholarwolf@library.unr.edu) with information about the object, including its full URL and the nature of your complaint."]},{"key":"dc:description.abstract","label":"Abstract","values":["Autonomous tasks are increasingly becoming part of our everyday life, whether in a factory floor where robotic manipulators manufacture goods, or when cars acquire the capability of parking themselves. These tasks often involve a human operator that has some high level control over the system. This can lead to situations where the human operator believes that the system is safe, when this might not be the case. This is why robust control algorithms need to be implemented that provide safety guarantees when a mechanical device is teleoperated by a human user. These algorithms can intervene when an unsafe choice is made to protect the operator and the system itself. The challenge that this work specifically focuses upon is dynamic obstacle avoidance by a robotic unit that is guided by a human user. Dynamic obstacles are objects that move in the environment independently from the robot and can potentially raise safety concerns for the robotic platform. In order to detect these obstacles in the environment, sensor data along with some probabilities need to be utilized to infer the magnitude and direction of an object's speed. This project is primarily concerned with this estimation and methods to do this accurately."]},{"key":"dc:format","label":"Dc Format","values":["PDF"]},{"key":"dc:title","label":"Title","values":["Dynamic Obstacle Avoidance on a Self-balancing Robot Platform"]}]}],"canonical_facts":{"dc:contributor.advisor":["Bekris, Kostas E."],"dc:creator":["Littlefield, Zakary"],"dc:date.accessioned":["2017-01-24T23:08:52Z"],"dc:date.available":["2017-01-24T23:08:52Z"],"dc:date.issued":["2011"],"dc:description":["The University of Nevada, Reno Libraries will promptly respond to removal requests related to content that violates intellectual property laws, data protections, or has been uploaded without creator consent. Takedown notices should be directed to our ScholarWolf team (scholarwolf@library.unr.edu) with information about the object, including its full URL and the nature of your complaint."],"dc:description.abstract":["Autonomous tasks are increasingly becoming part of our everyday life, whether in a factory floor where robotic manipulators manufacture goods, or when cars acquire the capability of parking themselves. These tasks often involve a human operator that has some high level control over the system. This can lead to situations where the human operator believes that the system is safe, when this might not be the case. This is why robust control algorithms need to be implemented that provide safety guarantees when a mechanical device is teleoperated by a human user. These algorithms can intervene when an unsafe choice is made to protect the operator and the system itself. The challenge that this work specifically focuses upon is dynamic obstacle avoidance by a robotic unit that is guided by a human user. Dynamic obstacles are objects that move in the environment independently from the robot and can potentially raise safety concerns for the robotic platform. In order to detect these obstacles in the environment, sensor data along with some probabilities need to be utilized to infer the magnitude and direction of an object's speed. This project is primarily concerned with this estimation and methods to do this accurately."],"dc:format":["PDF"],"dc:identifier.uri":["http://hdl.handle.net/11714/388"],"dc:language.iso":["en_US"],"dc:rights":["In Copyright(All Rights Reserved)"],"dc:title":["Dynamic Obstacle Avoidance on a Self-balancing Robot Platform"],"dc:type":["Thesis"],"thesis:degree_level":["Honors Thesis"],"thesis:degree_name":["Computer Science"],"thesis:institution_name":["University of Nevada, Reno"]},"updated_at":"2026-07-27T21:47:03Z"}