{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/106270"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/106270","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Localization for teams of autonomous ground vehicles","abstract":"This thesis presents the progress of work toward creating a localization engine for a fleet of autonomous ground robots using ultra-wideband (UWB) beacons in concert with the robots’ on-board IMUs and encoders. The error observed from the uncorrected UWB ranges was quantified for line-of-sight conditions, and a calibration procedure was developed and applied for UWB range correction. Four localization approaches were implemented and tested on a ground robot in an outdoor environment. Dead reckoning was used as a localization baseline. An extended Kalman filter (EKF) using the manufacturer firmware’s calculated positions for the measurement input was implemented and resulted in a final pose error of 29 cm. A second EKF using calibrated ranges and least squares estimation (LSE) for state measurement was implemented and resulted in a final pose error of 26 cm. A third Kalman filter, using an experimental extension of a mesh relaxation technique for position estimate, was tested but found not to track the position of the robot well. Discussion of implementation experience and recommendations for future work are provided.","abstract_html":"This thesis presents the progress of work toward creating a localization engine for a fleet of autonomous ground robots using ultra-wideband (UWB) beacons in concert with the robots’ on-board IMUs and encoders. The error observed from the uncorrected UWB ranges was quantified for line-of-sight conditions, and a calibration procedure was developed and applied for UWB range correction. Four localization approaches were implemented and tested on a ground robot in an outdoor environment. Dead reckoning was used as a localization baseline. An extended Kalman filter (EKF) using the manufacturer firmware’s calculated positions for the measurement input was implemented and resulted in a final pose error of 29 cm. A second EKF using calibrated ranges and least squares estimation (LSE) for state measurement was implemented and resulted in a final pose error of 26 cm. A third Kalman filter, using an experimental extension of a mesh relaxation technique for position estimate, was tested but found not to track the position of the robot well. Discussion of implementation experience and recommendations for future work are provided.","abstract_has_math":false,"creators":["Keiller, James"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Norris, William R.","Driggs-Campbell, Katherine R"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-03-02T21:58:30Z","date_published":"2020-03-02T21:58:30Z","updated_at":"2026-07-22T22:24:45Z","subjects":["ultra-wideband","localization","robotics","thesis"],"languages":["en"],"rights":["Copyright 2019 James Keiller"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/106270","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Norris, William R.","Driggs-Campbell, Katherine R"]},{"key":"dc:creator","label":"Author","values":["Keiller, James"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-03-02T21:58:30Z","2019-12-09","2019-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"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":["ultra-wideband","localization","robotics","thesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 James Keiller"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/106270"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This thesis presents the progress of work toward creating a localization engine for a fleet of autonomous ground robots using ultra-wideband (UWB) beacons in concert with the robots’ on-board IMUs and encoders. The error observed from the uncorrected UWB ranges was quantified for line-of-sight conditions, and a calibration procedure was developed and applied for UWB range correction. Four localization approaches were implemented and tested on a ground robot in an outdoor environment. Dead reckoning was used as a localization baseline. An extended Kalman filter (EKF) using the manufacturer firmware’s calculated positions for the measurement input was implemented and resulted in a final pose error of 29 cm. A second EKF using calibrated ranges and least squares estimation (LSE) for state measurement was implemented and resulted in a final pose error of 26 cm. A third Kalman filter, using an experimental extension of a mesh relaxation technique for position estimate, was tested but found not to track the position of the robot well. Discussion of implementation experience and recommendations for future work are provided.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-02-28 without embargo terms","The student, James Keiller, accepted the attached license on 2019-12-09 at 14:05.","The student, James Keiller, submitted this Thesis for approval on 2019-12-09 at 14:13.","This Thesis was approved for publication on 2019-12-09 at 16:30.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14763 on 2020-02-28 at 17:16:21","Made available in DSpace on 2020-03-02T21:58:30Z (GMT). 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Four localization approaches were implemented and tested on a ground robot in an outdoor environment. Dead reckoning was used as a localization baseline. An extended Kalman filter (EKF) using the manufacturer firmware’s calculated positions for the measurement input was implemented and resulted in a final pose error of 29 cm. A second EKF using calibrated ranges and least squares estimation (LSE) for state measurement was implemented and resulted in a final pose error of 26 cm. A third Kalman filter, using an experimental extension of a mesh relaxation technique for position estimate, was tested but found not to track the position of the robot well. Discussion of implementation experience and recommendations for future work are provided.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-02-28 without embargo terms","The student, James Keiller, accepted the attached license on 2019-12-09 at 14:05.","The student, James Keiller, submitted this Thesis for approval on 2019-12-09 at 14:13.","This Thesis was approved for publication on 2019-12-09 at 16:30.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14763 on 2020-02-28 at 17:16:21","Made available in DSpace on 2020-03-02T21:58:30Z (GMT). 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