{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/101383"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/101383","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Full season navigation and control of ultra-compact autonomous ag-bot in GPS denied environment","abstract":"This thesis describes perception and an autonomous navigation system for an ultra-lightweight ground robot in agricultural fields. The system is designed for reliable navigation under cluttered canopies using only a 2-D Hokuyo UST-10LX LiDAR and an RTK GPS as the primary sensors for navigation. Its purpose is to ensure that the robot can navigate through rows of crops without damaging the plants in narrow row-based and high-leaf-cover semi-structured crop plantations, such as corn (Zea mays), sorghum (Sorghum bicolor) and soybean (Glycine max). The fundamental contributions of this work are a GPS-INS based reliable localization system for the robot and a LiDAR-based navigation algorithm capable of rejecting outlying measurements in the point-cloud due to plants in adjacent rows, low-hanging leaf cover, or weeds. Finally, this work describes a behavior-based navigation architecture that enables the system to autonomously traverse a breeding field throughout the planting season.","abstract_html":"This thesis describes perception and an autonomous navigation system for an ultra-lightweight ground robot in agricultural fields. The system is designed for reliable navigation under cluttered canopies using only a 2-D Hokuyo UST-10LX LiDAR and an RTK GPS as the primary sensors for navigation. Its purpose is to ensure that the robot can navigate through rows of crops without damaging the plants in narrow row-based and high-leaf-cover semi-structured crop plantations, such as corn (Zea mays), sorghum (Sorghum bicolor) and soybean (Glycine max). The fundamental contributions of this work are a GPS-INS based reliable localization system for the robot and a LiDAR-based navigation algorithm capable of rejecting outlying measurements in the point-cloud due to plants in adjacent rows, low-hanging leaf cover, or weeds. Finally, this work describes a behavior-based navigation architecture that enables the system to autonomously traverse a breeding field throughout the planting season.","abstract_has_math":false,"creators":["Chawla, Karan"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Aerospace Engineering","degree_department":null,"school":null,"contributors":["Chowdhary, Girish"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-09-04T20:47:32Z","date_published":"2018-09-04T20:47:32Z","updated_at":"2026-07-22T22:24:40Z","subjects":["autonomous-navigation","gps-denied","ag-robot","perception","under-canopy","3D-printed-robot","ground-robot","GPS-INS","state-estimation"],"languages":["en"],"rights":["Copyright 2018 Karan Chawla"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/101383","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Chowdhary, Girish"]},{"key":"dc:creator","label":"Author","values":["Chawla, Karan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-09-04T20:47:32Z","2020-09-05T09:15:09Z","2018-04-27","2018-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Aerospace Engineering"]},{"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":["autonomous-navigation","gps-denied","ag-robot","perception","under-canopy","3D-printed-robot","ground-robot","GPS-INS","state-estimation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2018 Karan Chawla"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/101383"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This thesis describes perception and an autonomous navigation system for an ultra-lightweight ground robot in agricultural fields. The system is designed for reliable navigation under cluttered canopies using only a 2-D Hokuyo UST-10LX LiDAR and an RTK GPS as the primary sensors for navigation. Its purpose is to ensure that the robot can navigate through rows of crops without damaging the plants in narrow row-based and high-leaf-cover semi-structured crop plantations, such as corn (Zea mays), sorghum (Sorghum bicolor) and soybean (Glycine max). The fundamental contributions of this work are a GPS-INS based reliable localization system for the robot and a LiDAR-based navigation algorithm capable of rejecting outlying measurements in the point-cloud due to plants in adjacent rows, low-hanging leaf cover, or weeds. Finally, this work describes a behavior-based navigation architecture that enables the system to autonomously traverse a breeding field throughout the planting season.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2020-05-01","The student, Karan Chawla, accepted the attached license on 2018-04-27 at 12:05.","The student, Karan Chawla, submitted this Thesis for approval on 2018-04-27 at 12:18.","This Thesis was approved for publication on 2018-04-27 at 13:38.","DSpace SAF Submission Ingestion Package generated from Vireo submission #12540 on 2018-08-31 at 17:30:35","Made available in DSpace on 2018-09-04T20:47:32Z (GMT). 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The system is designed for reliable navigation under cluttered canopies using only a 2-D Hokuyo UST-10LX LiDAR and an RTK GPS as the primary sensors for navigation. Its purpose is to ensure that the robot can navigate through rows of crops without damaging the plants in narrow row-based and high-leaf-cover semi-structured crop plantations, such as corn (Zea mays), sorghum (Sorghum bicolor) and soybean (Glycine max). The fundamental contributions of this work are a GPS-INS based reliable localization system for the robot and a LiDAR-based navigation algorithm capable of rejecting outlying measurements in the point-cloud due to plants in adjacent rows, low-hanging leaf cover, or weeds. Finally, this work describes a behavior-based navigation architecture that enables the system to autonomously traverse a breeding field throughout the planting season.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2020-05-01","The student, Karan Chawla, accepted the attached license on 2018-04-27 at 12:05.","The student, Karan Chawla, submitted this Thesis for approval on 2018-04-27 at 12:18.","This Thesis was approved for publication on 2018-04-27 at 13:38.","DSpace SAF Submission Ingestion Package generated from Vireo submission #12540 on 2018-08-31 at 17:30:35","Made available in DSpace on 2018-09-04T20:47:32Z (GMT). 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