{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/86050"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/86050","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Development of a Low-Cost Navigation System for Autonomous Off -Road Vehicles","abstract":"To evaluate this low-cost navigation system and associated fusion algorithms, validation tests are performed using an experimental system that is designed to acquire real-time data and to perform data fusion. These tests take place at three test sites that include flat and uneven terrain, with or without obstacles. The evaluation results show that this system can achieve positioning accuracy in the range of 0.1 m to 0.5 m with an update rate of 50 Hz. The PVA model-based fusion algorithm can effectively bridge the signal interruption during a GPS signal outage of 30 s. The error model-based fusion algorithm can provide the signals at 50 Hz using the 1 Hz update rate of the complementary Kalman filter.","abstract_html":"To evaluate this low-cost navigation system and associated fusion algorithms, validation tests are performed using an experimental system that is designed to acquire real-time data and to perform data fusion. These tests take place at three test sites that include flat and uneven terrain, with or without obstacles. The evaluation results show that this system can achieve positioning accuracy in the range of 0.1 m to 0.5 m with an update rate of 50 Hz. The PVA model-based fusion algorithm can effectively bridge the signal interruption during a GPS signal outage of 30 s. The error model-based fusion algorithm can provide the signals at 50 Hz using the 1 Hz update rate of the complementary Kalman filter.","abstract_has_math":false,"creators":["Guo, Linsong"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Agricultural Engineering","degree_department":null,"school":null,"contributors":["Zhang, Qin"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-28T14:53:45Z","date_published":"2015-09-28T14:53:45Z","updated_at":"2026-07-22T22:26:26Z","subjects":["Artificial Intelligence"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3086070"],"render_values":[{"text":"(MiAaPQ)AAI3086070","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/86050","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhang, Qin"]},{"key":"dc:creator","label":"Author","values":["Guo, Linsong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-28T14:53:45Z","10000-01-01","2003"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Artificial Intelligence"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/86050","(MiAaPQ)AAI3086070"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["To evaluate this low-cost navigation system and associated fusion algorithms, validation tests are performed using an experimental system that is designed to acquire real-time data and to perform data fusion. These tests take place at three test sites that include flat and uneven terrain, with or without obstacles. The evaluation results show that this system can achieve positioning accuracy in the range of 0.1 m to 0.5 m with an update rate of 50 Hz. The PVA model-based fusion algorithm can effectively bridge the signal interruption during a GPS signal outage of 30 s. The error model-based fusion algorithm can provide the signals at 50 Hz using the 1 Hz update rate of the complementary Kalman filter.","Made available in DSpace on 2015-09-28T14:53:45Z (GMT). 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