{"id":{"repo_id":"unr","oai_identifier":"oai:scholarwolf.unr.edu:11714/7690"},"canonical_url":"https://search.dev.ndltd.org/etd/unr/oai:scholarwolf.unr.edu:11714/7690","repository":{"repo_id":"unr","name":"University of Nevada - Reno","base_url":"https://scholarwolf.unr.edu/server/oai/request"},"display":{"title":"Loosely coupled LiDAR-Visual/Thermal-Inertial Odometry and Mapping","abstract":"This thesis presents a loosely coupled LiDAR-Visual/Thermal-Inertial odometry and mapping method that uses factor graphs. Our approach jointly optimizes relative pose constraints provided by a LiDAR scan-to-scan alignment method and a Visual/Thermal-Inertial method with preintegrated IMU constraints. An optimized relative pose prior is provided to a LiDAR scan-to-map alignment method to finally output the odometry of the system as well as globally registered pointclouds. A set of evaluation studies is presented showing the outperformance of our approach against the LiDAR only odometry and mapping method in a tunnel environment and the field-verification in an autonomous mission in an underground mine.","abstract_html":"This thesis presents a loosely coupled LiDAR-Visual/Thermal-Inertial odometry and mapping method that uses factor graphs. Our approach jointly optimizes relative pose constraints provided by a LiDAR scan-to-scan alignment method and a Visual/Thermal-Inertial method with preintegrated IMU constraints. An optimized relative pose prior is provided to a LiDAR scan-to-map alignment method to finally output the odometry of the system as well as globally registered pointclouds. A set of evaluation studies is presented showing the outperformance of our approach against the LiDAR only odometry and mapping method in a tunnel environment and the field-verification in an autonomous mission in an underground mine.","abstract_has_math":false,"creators":["Khedekar, Nikhil Vijay"],"institution":null,"degree_name":null,"degree_level":"Master's Degree","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Alexis, Konstantinos"],"committee_chairs":[],"committee_members":["Scaramuzza, Davide","Papachristos, Christos","Panorska, Anna"],"year":2020,"date_issued":"2020","date_published":"2020","updated_at":"2026-07-27T21:47:47Z","subjects":[],"languages":[],"rights":["Creative Commons Attribution 4.0 United States"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11714/7690","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Alexis, Konstantinos"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Scaramuzza, Davide","Papachristos, Christos","Panorska, Anna"]},{"key":"dc:creator","label":"Author","values":["Khedekar, Nikhil Vijay"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2021-01-07T02:08:12Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2021-01-07T02:08:12Z"]},{"key":"dc:date.issued","label":"Date","values":["2020"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Master's Degree"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Creative Commons Attribution 4.0 United States"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11714/7690"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis presents a loosely coupled LiDAR-Visual/Thermal-Inertial odometry and mapping method that uses factor graphs. Our approach jointly optimizes relative pose constraints provided by a LiDAR scan-to-scan alignment method and a Visual/Thermal-Inertial method with preintegrated IMU constraints. An optimized relative pose prior is provided to a LiDAR scan-to-map alignment method to finally output the odometry of the system as well as globally registered pointclouds. A set of evaluation studies is presented showing the outperformance of our approach against the LiDAR only odometry and mapping method in a tunnel environment and the field-verification in an autonomous mission in an underground mine."]},{"key":"dc:format","label":"Dc Format","values":["PDF"]},{"key":"dc:title","label":"Title","values":["Loosely coupled LiDAR-Visual/Thermal-Inertial Odometry and Mapping"]}]}],"canonical_facts":{"dc:contributor.advisor":["Alexis, Konstantinos"],"dc:contributor.committeemember":["Scaramuzza, Davide","Papachristos, Christos","Panorska, Anna"],"dc:creator":["Khedekar, Nikhil Vijay"],"dc:date.accessioned":["2021-01-07T02:08:12Z"],"dc:date.available":["2021-01-07T02:08:12Z"],"dc:date.issued":["2020"],"dc:description.abstract":["This thesis presents a loosely coupled LiDAR-Visual/Thermal-Inertial odometry and mapping method that uses factor graphs. Our approach jointly optimizes relative pose constraints provided by a LiDAR scan-to-scan alignment method and a Visual/Thermal-Inertial method with preintegrated IMU constraints. An optimized relative pose prior is provided to a LiDAR scan-to-map alignment method to finally output the odometry of the system as well as globally registered pointclouds. A set of evaluation studies is presented showing the outperformance of our approach against the LiDAR only odometry and mapping method in a tunnel environment and the field-verification in an autonomous mission in an underground mine."],"dc:format":["PDF"],"dc:identifier.uri":["http://hdl.handle.net/11714/7690"],"dc:rights":["Creative Commons Attribution 4.0 United States"],"dc:title":["Loosely coupled LiDAR-Visual/Thermal-Inertial Odometry and Mapping"],"dc:type":["Thesis"],"thesis:degree_level":["Master's Degree"]},"updated_at":"2026-07-27T21:47:47Z"}