{"id":"https://openalex.org/W7157263352","doi":"https://doi.org/10.48550/arxiv.2604.23648","title":"Safe Navigation in Unknown and Cluttered Environments via Direction-Aware Convex Free-Region Generation","display_name":"Safe Navigation in Unknown and Cluttered Environments via Direction-Aware Convex Free-Region Generation","publication_year":2026,"publication_date":"2026-04-26","ids":{"openalex":"https://openalex.org/W7157263352","doi":"https://doi.org/10.48550/arxiv.2604.23648"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.23648","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23648","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":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.2604.23648","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134790914","display_name":"Zhicheng Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Zhicheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134797790","display_name":"Yongjian Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yongjian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134808013","display_name":"Kai Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Kai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134810568","display_name":"Yulin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yulin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134801517","display_name":"Fan Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Fan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134810253","display_name":"Jun Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Jun","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":0.9401999711990356,"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":0.9401999711990356,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.02800000086426735,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.006300000008195639,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6347000002861023},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.630299985408783},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.46299999952316284},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.4453999996185303},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.4350000023841858},{"id":"https://openalex.org/keywords/tree-traversal","display_name":"Tree traversal","score":0.41749998927116394},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.39340001344680786},{"id":"https://openalex.org/keywords/robot-kinematics","display_name":"Robot kinematics","score":0.3684999942779541}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7042999863624573},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6347000002861023},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.630299985408783},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6177999973297119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6080999970436096},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.46299999952316284},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.4453999996185303},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.4350000023841858},{"id":"https://openalex.org/C140745168","wikidata":"https://www.wikidata.org/wiki/Q1210082","display_name":"Tree traversal","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.39340001344680786},{"id":"https://openalex.org/C74222875","wikidata":"https://www.wikidata.org/wiki/Q16000312","display_name":"Robot kinematics","level":4,"score":0.3684999942779541},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3659999966621399},{"id":"https://openalex.org/C26990112","wikidata":"https://www.wikidata.org/wiki/Q6887224","display_name":"Mobile robot navigation","level":5,"score":0.3537999987602234},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.35089999437332153},{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.320499986410141},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C2781302577","wikidata":"https://www.wikidata.org/wiki/Q209","display_name":"Rectangle","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.257099986076355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.23648","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23648","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":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.2604.23648","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23648","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Convex":[0],"free":[1,151,179],"regions":[2,27,43,152,180],"provide":[3],"a":[4,68,102,159,198,202],"structured":[5],"and":[6,17,49,111,118,137,146,153,186,194,201,207],"optimization-friendly":[7],"representation":[8],"of":[9,210],"collision-free":[10,26,88,121,189],"space":[11],"for":[12],"robot":[13,47,91,112,200],"navigation":[14,103,171],"in":[15,62,158,168],"unknown":[16],"cluttered":[18,35,169],"environments.":[19],"However,":[20],"existing":[21],"methods":[22],"typically":[23],"enlarge":[24],"local":[25,147],"mainly":[28],"according":[29],"to":[30,41,162],"surrounding":[31],"obstacle":[32],"geometry.":[33],"In":[34],"environments,":[36],"such":[37,67],"strategies":[38],"may":[39],"fail":[40],"generate":[42],"that":[44,105,174],"both":[45],"accommodate":[46],"geometry":[48,92,113],"preserve":[50],"traversable":[51],"extension":[52],"along":[53],"candidate":[54,108,154],"motion":[55,73,89,109,122],"directions,":[56],"thereby":[57],"limiting":[58],"downstream":[59,184],"traversal,":[60],"especially":[61],"narrow":[63],"passages.":[64],"Even":[65],"when":[66,90],"region":[69],"is":[70,93],"available,":[71],"safe":[72],"generation":[74],"remains":[75],"challenging,":[76],"because":[77],"safety":[78,144],"checking":[79],"at":[80,219],"discretized":[81],"trajectory":[82,125,138],"samples":[83],"does":[84],"not":[85],"guarantee":[86],"continuously":[87,120],"modeled":[94],"explicitly.":[95],"To":[96],"address":[97],"these":[98],"issues,":[99],"we":[100],"propose":[101],"framework":[104,131],"jointly":[106],"incorporates":[107],"directions":[110],"into":[114],"convex":[115],"free-region":[116],"generation,":[117,139],"achieves":[119],"through":[123],"continuous-safe":[124],"generation.":[126],"Within":[127],"each":[128],"region,":[129],"the":[130,175,205,211],"performs":[132],"geometry-aware":[133],"target":[134],"pose":[135],"selection":[136],"together":[140],"with":[141,183],"Lipschitz-based":[142],"continuous":[143],"certification":[145],"refinement.":[148],"The":[149,213],"resulting":[150],"motions":[155],"are":[156],"maintained":[157],"region-based":[160],"graph":[161],"support":[163],"incremental":[164],"planning.":[165],"Quantitative":[166],"results":[167],"2D":[170],"scenarios":[172],"show":[173],"proposed":[176],"method":[177],"generates":[178],"better":[181],"aligned":[182],"traversal":[185],"enables":[187],"reliable":[188],"navigation,":[190],"while":[191],"additional":[192],"3D":[193],"real-world":[195],"experiments":[196],"on":[197],"quadrupedal":[199],"UAV":[203],"demonstrate":[204],"extensibility":[206],"practical":[208],"applicability":[209],"framework.":[212],"open-source":[214],"project":[215],"can":[216],"be":[217],"found":[218],"https://github.com/ZhichengSong6/FRGraph.":[220]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-29T00:00:00"}