{"id":"https://openalex.org/W7156815461","doi":"https://doi.org/10.48550/arxiv.2604.24628","title":"Real-time windrow detection from onboard tractor sensors for automated following","display_name":"Real-time windrow detection from onboard tractor sensors for automated following","publication_year":2026,"publication_date":"2026-04-27","ids":{"openalex":"https://openalex.org/W7156815461","doi":"https://doi.org/10.48550/arxiv.2604.24628"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.24628","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24628","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.24628","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116937899","display_name":"Lorenz Gunreben","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gunreben, Lorenz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125534133","display_name":"Nico Heider","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heider, Nico","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091253849","display_name":"Sebastian Z\u00fcrner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Z\u00fcrner, Sebastian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056583651","display_name":"Martin Schieck","orcid":"https://orcid.org/0000-0002-5257-9646"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schieck, Martin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5029017321","display_name":"Bogdan Franczyk","orcid":"https://orcid.org/0000-0002-5740-2946"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Franczyk, Bogdan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.2766999900341034,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.2766999900341034,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11978","display_name":"Soil Mechanics and Vehicle Dynamics","score":0.09520000219345093,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12729","display_name":"Tree Root and Stability Studies","score":0.09229999780654907,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.8219000101089478},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5195000171661377},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4900999963283539},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.43369999527931213},{"id":"https://openalex.org/keywords/gnss-applications","display_name":"GNSS applications","score":0.4059999883174896},{"id":"https://openalex.org/keywords/stereopsis","display_name":"Stereopsis","score":0.4056999981403351},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4009999930858612},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.3853999972343445}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8219000101089478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5429999828338623},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5195000171661377},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4900999963283539},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4878999888896942},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4602000117301941},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.43369999527931213},{"id":"https://openalex.org/C14279187","wikidata":"https://www.wikidata.org/wiki/Q5514012","display_name":"GNSS applications","level":3,"score":0.4059999883174896},{"id":"https://openalex.org/C68537008","wikidata":"https://www.wikidata.org/wiki/Q247932","display_name":"Stereopsis","level":2,"score":0.4056999981403351},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4009999930858612},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.3853999972343445},{"id":"https://openalex.org/C2780427559","wikidata":"https://www.wikidata.org/wiki/Q39495","display_name":"Tractor","level":2,"score":0.3833000063896179},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3723999857902527},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34200000762939453},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.32919999957084656},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3043000102043152},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3003000020980835},{"id":"https://openalex.org/C35861506","wikidata":"https://www.wikidata.org/wiki/Q17141434","display_name":"Stereo cameras","level":3,"score":0.2971999943256378},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C3018397939","wikidata":"https://www.wikidata.org/wiki/Q3644502","display_name":"Open source","level":3,"score":0.2572999894618988},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.24628","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24628","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.24628","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24628","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8518787622451782,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Proprietary":[0],"design":[1],"in":[2,11],"commercial":[3],"windrow-detection":[4],"systems":[5],"restricts":[6],"transparency":[7],"and":[8,24,82,114],"limits":[9],"progress":[10],"open":[12],"autonomous":[13,119],"forage-harvesting":[14,120],"research.":[15],"We":[16],"present":[17],"a":[18,61,107],"multi-modal":[19],"dataset":[20,34],"combining":[21],"stereo":[22,81,95],"vision":[23],"LiDAR":[25,83,99],"from":[26],"tractor-mounted":[27],"sensors":[28,96],"during":[29],"real":[30],"baling":[31],"operations.":[32],"The":[33],"includes":[35],"synchronized":[36],"sensor":[37],"data":[38,52],"with":[39,50],"GNSS":[40],"trajectories,":[41],"partly":[42],"released":[43],"as":[44],"ROS2":[45],"Humble":[46],"bags":[47],"on":[48,54,68],"Zenodo,":[49],"additional":[51],"available":[53],"request.":[55],"Using":[56],"this":[57],"dataset,":[58],"we":[59],"implement":[60],"real-time":[62],"(>20":[63],"Hz)":[64],"centroid-based":[65],"windrow-following":[66],"method":[67],"an":[69],"NVIDIA":[70],"Jetson":[71],"AGX":[72],"Orin.":[73],"Across":[74],"the":[75],"critical":[76],"4-10":[77],"m":[78],"guidance":[79],"range,":[80],"depth":[84],"measurements":[85],"show":[86],"strong":[87],"agreement":[88],"(0.965":[89],"+/-":[90],"0.021),":[91],"indicating":[92],"that":[93],"low-cost":[94],"can":[97],"approach":[98],"performance.":[100],"Our":[101],"open-source":[102],"ROS":[103],"2":[104],"pipeline":[105],"provides":[106],"reproducible":[108],"benchmark":[109],"for":[110],"GPS-free":[111],"windrow":[112],"detection":[113],"supports":[115],"development":[116],"of":[117],"practical":[118],"systems.":[121],"Dataset:":[122],"https://zenodo.org/records/17486318":[123]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-29T00:00:00"}