This thesis presents a method for generating an optimized path through a given track. The path is generated by choosing waypoints throughout the track then iteratively optimizing the position of these waypoints. The waypoints are then connected by optimized paths represented by curvature polynomials. The end result is a path through the track represented as a spline of curvature polynomials. This method is applied to multiple simulated tracks and the results are presented. By generating and representing the paths in the continuous domain, the method has improved computational efficiency from many of the discrete methods used to generate an optimal path through a track. Also, when using a path to guide an autonomous vehicle, paths represented in the continuous domain can allow for better tracking and control than discrete counterparts. As autonomous systems become more integral to our society, increased computational efficiency, tracking, and control are important areas of improvement.
","abstract_html":"<p>This thesis presents a method for generating an optimized path through a given track. The path is generated by choosing waypoints throughout the track then iteratively optimizing the position of these waypoints. The waypoints are then connected by optimized paths represented by curvature polynomials. The end result is a path through the track represented as a spline of curvature polynomials. This method is applied to multiple simulated tracks and the results are presented. By generating and representing the paths in the continuous domain, the method has improved computational efficiency from many of the discrete methods used to generate an optimal path through a track. Also, when using a path to guide an autonomous vehicle, paths represented in the continuous domain can allow for better tracking and control than discrete counterparts. As autonomous systems become more integral to our society, increased computational efficiency, tracking, and control are important areas of improvement.</p>","abstract_has_math":false,"creators":["Friedl, Tyler"],"institution":null,"degree_name":"M.S.","degree_level":"Masters Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Kyoung-Dae Kim, Ph.D.","Margareta Stefanovic","Vijaya Narapareddy"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-01-01T08:00:00Z","date_published":"2017-01-01T08:00:00Z","updated_at":"2026-07-24T02:02:19Z","subjects":["Autonomous vehicles","Constrained optimization","Non-linear optimization","Optimal control","Optimal path generation","Trajectory generation","Other Electrical and Computer Engineering","Robotics"],"languages":["en"],"rights":["Copyright is held by the author. User is responsible for all copyright compliance.
"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.du.edu/etd/1370","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kyoung-Dae Kim, Ph.D.","Margareta Stefanovic","Vijaya Narapareddy"]},{"key":"dc:creator","label":"Author","values":["Friedl, Tyler"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-04-03T07:00:00Z"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Autonomous vehicles","Constrained optimization","Non-linear optimization","Optimal control","Optimal path generation","Trajectory generation","Other Electrical and Computer Engineering","Robotics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright is held by the author. User is responsible for all copyright compliance.
"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.du.edu/etd/1370"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis presents a method for generating an optimized path through a given track. The path is generated by choosing waypoints throughout the track then iteratively optimizing the position of these waypoints. The waypoints are then connected by optimized paths represented by curvature polynomials. The end result is a path through the track represented as a spline of curvature polynomials. This method is applied to multiple simulated tracks and the results are presented. By generating and representing the paths in the continuous domain, the method has improved computational efficiency from many of the discrete methods used to generate an optimal path through a track. Also, when using a path to guide an autonomous vehicle, paths represented in the continuous domain can allow for better tracking and control than discrete counterparts. As autonomous systems become more integral to our society, increased computational efficiency, tracking, and control are important areas of improvement.
"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Optimized Trajectory Generation for Car-Like Robots on a Closed Loop Track"]}]}],"canonical_facts":{"dc:contributor":["Kyoung-Dae Kim, Ph.D.","Margareta Stefanovic","Vijaya Narapareddy"],"dc:creator":["Friedl, Tyler"],"dc:date.available":["2018-04-03T07:00:00Z"],"dc:description.abstract":["This thesis presents a method for generating an optimized path through a given track. The path is generated by choosing waypoints throughout the track then iteratively optimizing the position of these waypoints. The waypoints are then connected by optimized paths represented by curvature polynomials. The end result is a path through the track represented as a spline of curvature polynomials. This method is applied to multiple simulated tracks and the results are presented. By generating and representing the paths in the continuous domain, the method has improved computational efficiency from many of the discrete methods used to generate an optimal path through a track. Also, when using a path to guide an autonomous vehicle, paths represented in the continuous domain can allow for better tracking and control than discrete counterparts. As autonomous systems become more integral to our society, increased computational efficiency, tracking, and control are important areas of improvement.
"],"dc:format":["application/pdf"],"dc:identifier":["https://digitalcommons.du.edu/etd/1370"],"dc:language":["en"],"dc:rights":["Copyright is held by the author. User is responsible for all copyright compliance.
"],"dc:subject":["Autonomous vehicles","Constrained optimization","Non-linear optimization","Optimal control","Optimal path generation","Trajectory generation","Other Electrical and Computer Engineering","Robotics"],"dc:title":["Optimized Trajectory Generation for Car-Like Robots on a Closed Loop Track"],"thesis:degree_level":["Masters Thesis"],"thesis:degree_name":["M.S."]},"updated_at":"2026-07-24T02:02:19Z"}