{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/108401"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/108401","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Development of Real Time Self Driving Software for Wheeled Robot with UI based Navigation","abstract":"Autonomous Vehicles are complex modular systems with various inter-dependent safety critical modules, the failure of which leads to failure of the overall system. The Localization system, which estimates the pose of the vehicle in the global coordinate frame with respect to a map, has a drift in error, when operated only based on data from proprioceptive sensors. Current solutions to the problem are computationally heavy SLAM algorithms. An alternate system is proposed in the thesis which eliminates the drift by resetting the global coordinate frame to the local frame at every motion planning update. The system replaces the mission planner with a user interface(UI) onto which the User provides local navigation inputs, thus eliminating the need for maintenance of a Global frame. The User Input is considered in the decision framework of the behavioral planner, which selects a safe and legal maneuver for the vehicle to follow. The path and trajectory planners generate a trajectory to accomplish the maneuver and the controller follows the trajectory until the next motion planning update. A prototype of the system has been built on a wheeled robot and tested for the feasibility of continuous operation in Autonomous Vehicles.","abstract_html":"Autonomous Vehicles are complex modular systems with various inter-dependent safety critical modules, the failure of which leads to failure of the overall system. The Localization system, which estimates the pose of the vehicle in the global coordinate frame with respect to a map, has a drift in error, when operated only based on data from proprioceptive sensors. Current solutions to the problem are computationally heavy SLAM algorithms. An alternate system is proposed in the thesis which eliminates the drift by resetting the global coordinate frame to the local frame at every motion planning update. The system replaces the mission planner with a user interface(UI) onto which the User provides local navigation inputs, thus eliminating the need for maintenance of a Global frame. The User Input is considered in the decision framework of the behavioral planner, which selects a safe and legal maneuver for the vehicle to follow. The path and trajectory planners generate a trajectory to accomplish the maneuver and the controller follows the trajectory until the next motion planning update. A prototype of the system has been built on a wheeled robot and tested for the feasibility of continuous operation in Autonomous Vehicles.","abstract_has_math":false,"creators":["Keshavamurthi, Karthik Balaji"],"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":["Taheri, Saied"],"committee_members":["Ferris, John B.","Sandu, Corina"],"year":2020,"date_issued":"2020-08-26","date_published":"2020-08-26","updated_at":"2026-07-22T22:19:21Z","subjects":["SLAM","Localization","Motion Planning","Perception","Autonomous Vehicles"],"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:27325"],"render_values":[{"text":"vt_gsexam:27325","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/108401","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Taheri, Saied"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Ferris, John B.","Sandu, Corina"]},{"key":"dc:contributor.department","label":"Department","values":["Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Keshavamurthi, Karthik Balaji"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-02-18T07:00:07Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-02-18T07:00:07Z"]},{"key":"dc:date.issued","label":"Date","values":["2020-08-26"]},{"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":["SLAM","Localization","Motion Planning","Perception","Autonomous Vehicles"]}]},{"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:27325"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/108401"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Autonomous Vehicles are complex modular systems with various inter-dependent safety critical modules, the failure of which leads to failure of the overall system. The Localization system, which estimates the pose of the vehicle in the global coordinate frame with respect to a map, has a drift in error, when operated only based on data from proprioceptive sensors. Current solutions to the problem are computationally heavy SLAM algorithms. An alternate system is proposed in the thesis which eliminates the drift by resetting the global coordinate frame to the local frame at every motion planning update. The system replaces the mission planner with a user interface(UI) onto which the User provides local navigation inputs, thus eliminating the need for maintenance of a Global frame. The User Input is considered in the decision framework of the behavioral planner, which selects a safe and legal maneuver for the vehicle to follow. The path and trajectory planners generate a trajectory to accomplish the maneuver and the controller follows the trajectory until the next motion planning update. A prototype of the system has been built on a wheeled robot and tested for the feasibility of continuous operation in Autonomous Vehicles."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["Autonomous Vehicles are complex modular systems with various inter-dependent safety critical modules, the failure of which leads to failure of the overall system. One such module is the Localization system, that is responsible for estimating the pose of the vehicle in the global coordinate frame, with respect to a map. Based on the pose, the vehicle navigates to the goal waypoints, which are points in the global coordinate frame specified in the map by the route or mission planner of the planning module. The Localization system, however, consists of a drift in position error, due to poor GPS signals and high noise in the inertial sensors. This has been tackled by applying computationally heavy Simultaneous Localization and Mapping based methods, which identify landmarks in the environment at every time step and correct the vehicle position, based on the relative change in position of landmarks. An alternate solution is proposed in this thesis, which delegates navigation to the passenger. This system replaces the mission planner from the planning module with a User Interface onto which the passenger provides local Navigation input, which is followed by the vehicle. The system resets the global coordinate frame to the vehicle frame at every motion planning update, thus eliminating the error accumulated between the two updates. The system is also designed to perform default actions in the absence of user Navigation commands, to reduce the number of commands to be provided by the passenger in the journey towards the goal. A prototype of the system is built and tested for feasibility."]},{"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":["Development of Real Time Self Driving Software for Wheeled Robot with UI based Navigation"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Taheri, Saied"],"dc:contributor.committeemember":["Ferris, John B.","Sandu, Corina"],"dc:contributor.department":["Mechanical Engineering"],"dc:creator":["Keshavamurthi, Karthik Balaji"],"dc:date.accessioned":["2022-02-18T07:00:07Z"],"dc:date.available":["2022-02-18T07:00:07Z"],"dc:date.issued":["2020-08-26"],"dc:description.abstract":["Autonomous Vehicles are complex modular systems with various inter-dependent safety critical modules, the failure of which leads to failure of the overall system. The Localization system, which estimates the pose of the vehicle in the global coordinate frame with respect to a map, has a drift in error, when operated only based on data from proprioceptive sensors. Current solutions to the problem are computationally heavy SLAM algorithms. An alternate system is proposed in the thesis which eliminates the drift by resetting the global coordinate frame to the local frame at every motion planning update. The system replaces the mission planner with a user interface(UI) onto which the User provides local navigation inputs, thus eliminating the need for maintenance of a Global frame. The User Input is considered in the decision framework of the behavioral planner, which selects a safe and legal maneuver for the vehicle to follow. The path and trajectory planners generate a trajectory to accomplish the maneuver and the controller follows the trajectory until the next motion planning update. A prototype of the system has been built on a wheeled robot and tested for the feasibility of continuous operation in Autonomous Vehicles."],"dc:description.abstractgeneral":["Autonomous Vehicles are complex modular systems with various inter-dependent safety critical modules, the failure of which leads to failure of the overall system. One such module is the Localization system, that is responsible for estimating the pose of the vehicle in the global coordinate frame, with respect to a map. Based on the pose, the vehicle navigates to the goal waypoints, which are points in the global coordinate frame specified in the map by the route or mission planner of the planning module. The Localization system, however, consists of a drift in position error, due to poor GPS signals and high noise in the inertial sensors. This has been tackled by applying computationally heavy Simultaneous Localization and Mapping based methods, which identify landmarks in the environment at every time step and correct the vehicle position, based on the relative change in position of landmarks. An alternate solution is proposed in this thesis, which delegates navigation to the passenger. This system replaces the mission planner from the planning module with a User Interface onto which the passenger provides local Navigation input, which is followed by the vehicle. The system resets the global coordinate frame to the vehicle frame at every motion planning update, thus eliminating the error accumulated between the two updates. The system is also designed to perform default actions in the absence of user Navigation commands, to reduce the number of commands to be provided by the passenger in the journey towards the goal. A prototype of the system is built and tested for feasibility."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:27325"],"dc:identifier.uri":["http://hdl.handle.net/10919/108401"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["SLAM","Localization","Motion Planning","Perception","Autonomous Vehicles"],"dc:title":["Development of Real Time Self Driving Software for Wheeled Robot with UI based Navigation"],"dc:type":["Thesis"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:21Z"}