{"id":"https://openalex.org/W7165803340","doi":"https://doi.org/10.48550/arxiv.2606.24631","title":"Optimization-based Safe Trajectory Planning for Autonomous Ground Vehicle in Multi-Floor Scenarios","display_name":"Optimization-based Safe Trajectory Planning for Autonomous Ground Vehicle in Multi-Floor Scenarios","publication_year":2026,"publication_date":"2026-06-23","ids":{"openalex":"https://openalex.org/W7165803340","doi":"https://doi.org/10.48550/arxiv.2606.24631"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.24631","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24631","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"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.2606.24631","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128659801","display_name":"Zishang Xiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiang, Zishang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000502578","display_name":"Runda Zhang","orcid":"https://orcid.org/0009-0000-3782-356X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Runda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024866488","display_name":"Runqi Chai","orcid":"https://orcid.org/0000-0003-4083-8863"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chai, Runqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139265179","display_name":"Kaiyuan Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Kaiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070349528","display_name":"Senchun Chai","orcid":"https://orcid.org/0000-0003-1910-1795"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chai, Senchun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139256144","display_name":"Yuanqing Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia, Yuanqing","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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.8928999900817871,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.8928999900817871,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.031099999323487282,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10524","display_name":"Traffic control and management","score":0.0215000007301569,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/trajectory","display_name":"Trajectory","score":0.7717999815940857},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.6922000050544739},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6255999803543091},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.6172999739646912},{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.5791000127792358},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5633999705314636},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5087000131607056}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7717999815940857},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.6922000050544739},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6255999803543091},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.6172999739646912},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.5791000127792358},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5633999705314636},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5406000018119812},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5087000131607056},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.40709999203681946},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.35910001397132874},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.35109999775886536},{"id":"https://openalex.org/C18465707","wikidata":"https://www.wikidata.org/wiki/Q5001797","display_name":"Business system planning","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C173246807","wikidata":"https://www.wikidata.org/wiki/Q7833062","display_name":"Trajectory optimization","level":3,"score":0.3249000012874603},{"id":"https://openalex.org/C2776548393","wikidata":"https://www.wikidata.org/wiki/Q2031473","display_name":"Unmanned ground vehicle","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2863999903202057},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.28450000286102295},{"id":"https://openalex.org/C2989549987","wikidata":"https://www.wikidata.org/wiki/Q350882","display_name":"Route planning","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C24881265","wikidata":"https://www.wikidata.org/wiki/Q757267","display_name":"Voronoi diagram","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2632000148296356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25859999656677246},{"id":"https://openalex.org/C191489605","wikidata":"https://www.wikidata.org/wiki/Q6043021","display_name":"Integrated business planning","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.24631","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24631","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.24631","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24631","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.7071003913879395,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,34,50,83],"development":[1],"of":[2,19,37,131],"trajectory":[3,27,47,84,124],"planning":[4,28,43,48,52,62,85,98],"strategies":[5],"for":[6,31,80,107,119],"autonomous":[7],"ground":[8],"vehicles":[9],"(AGVs)":[10],"represents":[11],"a":[12,26,55,60,95,112],"prevailing":[13],"research":[14],"interest":[15],"within":[16],"the":[17,41,46,77,127,132],"domain":[18],"intelligent":[20],"transportation":[21],"systems.":[22],"This":[23],"paper":[24],"introduces":[25],"framework":[29,35,99,134],"tailored":[30],"multi-floor":[32],"scenarios.":[33],"consists":[36],"two":[38],"main":[39],"modules:":[40],"task":[42,51,61],"module":[44,53,86],"and":[45,70,94,129],"module.":[49],"involves":[54],"strategic":[56],"selection":[57],"phase,":[58],"where":[59],"strategy":[63],"based":[64],"on":[65],"generalized":[66],"voronoi":[67],"diagrams":[68],"(GVD)":[69],"multi-objective":[71],"algorithms":[72],"is":[73,100,117],"proposed":[74,133],"to":[75,90,102],"select":[76],"floor":[78],"exits":[79],"each":[81],"floor.":[82],"utilizes":[87],"optimization-based":[88],"methods":[89],"generate":[91],"high-quality":[92],"trajectories,":[93],"warm-started":[96],"hierarchical":[97],"designed":[101,118],"ensure":[103],"rapid":[104],"convergence.":[105],"Additionally,":[106],"handling":[108],"complex":[109],"obstacle":[110,121],"constraints,":[111],"correlation":[113],"constraint":[114],"calculation":[115],"method":[116],"reducing":[120],"constraints":[122],"in":[123],"planning.":[125],"Finally,":[126],"feasibility":[128],"effectiveness":[130],"are":[135],"verified":[136],"through":[137],"simulations.":[138]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-25T00:00:00"}
