{"id":"https://openalex.org/W4416750450","doi":"https://doi.org/10.1109/iros60139.2025.11246907","title":"Safety-Guided RRT*: Hyperoctant Sampling-based Path Planning with SDF-based Robotic Representation","display_name":"Safety-Guided RRT*: Hyperoctant Sampling-based Path Planning with SDF-based Robotic Representation","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416750450","doi":"https://doi.org/10.1109/iros60139.2025.11246907"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11246907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101508984","display_name":"Yangmin Xie","orcid":"https://orcid.org/0000-0002-6517-2917"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yangmin Xie","raw_affiliation_strings":["Shanghai University,Shanghai Key Laboratory of Intelligent Manufacturing and Robotics,Shanghai,China,200444"],"affiliations":[{"raw_affiliation_string":"Shanghai University,Shanghai Key Laboratory of Intelligent Manufacturing and Robotics,Shanghai,China,200444","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108329987","display_name":"Yuqiao Zhong","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqiao Zhong","raw_affiliation_strings":["Shanghai University,School of Mechatronic Engineering and Automation,Shanghai,China,200444"],"affiliations":[{"raw_affiliation_string":"Shanghai University,School of Mechatronic Engineering and Automation,Shanghai,China,200444","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102190187","display_name":"Hang Shi","orcid":"https://orcid.org/0000-0002-3966-0431"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Shi","raw_affiliation_strings":["Shanghai University,School of Mechatronic Engineering and Automation,Shanghai,China,200444"],"affiliations":[{"raw_affiliation_string":"Shanghai University,School of Mechatronic Engineering and Automation,Shanghai,China,200444","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059579886","display_name":"Yusheng Yang","orcid":"https://orcid.org/0000-0001-6762-4158"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yusheng Yang","raw_affiliation_strings":["Shanghai University,Shanghai Key Laboratory of Intelligent Manufacturing and Robotics,Shanghai,China,200444"],"affiliations":[{"raw_affiliation_string":"Shanghai University,Shanghai Key Laboratory of Intelligent Manufacturing and Robotics,Shanghai,China,200444","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101508984"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37132469,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1892","last_page":"1898"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9847999811172485,"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":0.9847999811172485,"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":0.007300000172108412,"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/T10879","display_name":"Robotic Locomotion and Control","score":0.0010999999940395355,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/motion-planning","display_name":"Motion planning","score":0.8253999948501587},{"id":"https://openalex.org/keywords/safer","display_name":"SAFER","score":0.6898000240325928},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.5953999757766724},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5928999781608582},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5690000057220459},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5295000076293945},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.527400016784668},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.504800021648407},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4805999994277954}],"concepts":[{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.8253999948501587},{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.6898000240325928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6028000116348267},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.5953999757766724},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5928999781608582},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5690000057220459},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5295000076293945},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.527400016784668},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.504800021648407},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4805999994277954},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.4636000096797943},{"id":"https://openalex.org/C2776839635","wikidata":"https://www.wikidata.org/wiki/Q14942679","display_name":"Random tree","level":4,"score":0.45750001072883606},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.39419999718666077},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3808000087738037},{"id":"https://openalex.org/C129045301","wikidata":"https://www.wikidata.org/wiki/Q7144654","display_name":"Path length","level":2,"score":0.3776000142097473},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.3605000078678131},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.35429999232292175},{"id":"https://openalex.org/C199668693","wikidata":"https://www.wikidata.org/wiki/Q1550329","display_name":"Collision detection","level":3,"score":0.3379000127315521},{"id":"https://openalex.org/C158485040","wikidata":"https://www.wikidata.org/wiki/Q4778119","display_name":"Any-angle path planning","level":4,"score":0.33550000190734863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33219999074935913},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3294000029563904},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.2953000068664551},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2831999957561493},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.27970001101493835},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2759999930858612},{"id":"https://openalex.org/C2778803389","wikidata":"https://www.wikidata.org/wiki/Q7246866","display_name":"Probabilistic roadmap","level":4,"score":0.2694999873638153},{"id":"https://openalex.org/C197855036","wikidata":"https://www.wikidata.org/wiki/Q380172","display_name":"Binary tree","level":2,"score":0.2581999897956848}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11246907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1971086298","https://openalex.org/W1976930960","https://openalex.org/W2034801091","https://openalex.org/W2042613867","https://openalex.org/W2161819990","https://openalex.org/W2546332551","https://openalex.org/W2950938745","https://openalex.org/W2962678727","https://openalex.org/W3011208732","https://openalex.org/W3018656899","https://openalex.org/W3034118413","https://openalex.org/W3081301530","https://openalex.org/W3114544725","https://openalex.org/W3149798409","https://openalex.org/W3160747345","https://openalex.org/W4200063339","https://openalex.org/W4206617872","https://openalex.org/W4226503583","https://openalex.org/W4310038675","https://openalex.org/W4313058225","https://openalex.org/W4320922072","https://openalex.org/W4327956071","https://openalex.org/W4367839715","https://openalex.org/W4401416446"],"related_works":[],"abstract_inverted_index":{"Sampling-based":[0],"path":[1,118],"planning":[2,15,64,119],"algorithms,":[3],"such":[4],"as":[5],"Rapidly-exploring":[6],"Random":[7],"Tree":[8],"(RRT),":[9],"are":[10,57],"widely":[11],"used":[12],"for":[13],"motion":[14],"in":[16,25,45,54,68,162],"high":[17],"degree-of-freedom":[18],"robotic":[19],"systems":[20],"due":[21],"to":[22,60,103],"their":[23],"efficiency":[24],"exploring":[26],"high-dimensional":[27],"spaces.":[28],"However,":[29],"traditional":[30],"methods":[31],"rely":[32],"on":[33,90],"binary":[34],"collision":[35,47,155],"detection,":[36],"which":[37,83],"only":[38,158],"determines":[39],"whether":[40],"a":[41,46,85,96,159],"sampled":[42],"configuration":[43],"is":[44],"without":[48],"quantifying":[49],"its":[50],"safety,":[51],"often":[52],"resulting":[53],"trajectories":[55,125],"that":[56,137],"overly":[58],"close":[59],"obstacles":[61],"and":[62,107,133,146,153],"reducing":[63,154],"success":[65,120,151],"rates,":[66],"especially":[67],"complex":[69],"environments":[70],"with":[71,95,126,157],"narrow":[72],"passages.":[73],"To":[74],"address":[75],"this":[76],"issue,":[77],"we":[78],"propose":[79],"Safety-Guided":[80],"RRT*":[81],"(SG-RRT*),":[82],"integrates":[84],"quantitative":[86],"safety":[87],"metric":[88],"based":[89],"signed":[91],"distance":[92],"functions":[93],"(SDFs)":[94],"hyperoctant":[97],"sampling":[98],"strategy,":[99],"enabling":[100],"the":[101],"planner":[102],"prioritize":[104],"safer":[105,124],"configurations":[106],"steer":[108],"tree":[109],"expansion":[110],"toward":[111],"collision-free":[112],"regions.":[113],"This":[114],"approach":[115],"significantly":[116],"improves":[117],"rates":[121,152],"while":[122],"generating":[123],"greater":[127],"clearance":[128],"from":[129],"obstacles.":[130],"Extensive":[131],"simulations":[132],"real-world":[134],"experiments":[135],"demonstrate":[136],"SG-RRT*":[138],"outperforms":[139],"state-of-the-art":[140],"methods,":[141],"including":[142],"RRT*,":[143],"Informed-RRT*,":[144],"TRRT,":[145],"Bi-TRRT,":[147],"by":[148],"achieving":[149],"higher":[150],"risks,":[156],"slight":[160],"increase":[161],"trajectory":[163],"length.":[164]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-28T00:00:00"}
