{"id":"https://openalex.org/W4415821103","doi":"https://doi.org/10.1109/access.2025.3628212","title":"Fusion-Guided Framework: Improving Sampling Performance via Potential Fields and Terrain Density","display_name":"Fusion-Guided Framework: Improving Sampling Performance via Potential Fields and Terrain Density","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415821103","doi":"https://doi.org/10.1109/access.2025.3628212"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3628212","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3628212","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3628212","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057942437","display_name":"Hai-Sheng Zhao","orcid":"https://orcid.org/0009-0000-8338-8511"},"institutions":[{"id":"https://openalex.org/I87547150","display_name":"Southern Illinois University Edwardsville","ror":"https://ror.org/04cqs5j56","country_code":"US","type":"education","lineage":["https://openalex.org/I2801502357","https://openalex.org/I87547150"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haibo Zhao","raw_affiliation_strings":["Southern Illinois University Edwardsville, Edwardsville, IL, USA"],"raw_orcid":"https://orcid.org/0009-0000-8338-8511","affiliations":[{"raw_affiliation_string":"Southern Illinois University Edwardsville, Edwardsville, IL, USA","institution_ids":["https://openalex.org/I87547150"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yuchen Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I87547150","display_name":"Southern Illinois University Edwardsville","ror":"https://ror.org/04cqs5j56","country_code":"US","type":"education","lineage":["https://openalex.org/I2801502357","https://openalex.org/I87547150"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuchen Xia","raw_affiliation_strings":["Southern Illinois University Edwardsville, Edwardsville, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern Illinois University Edwardsville, Edwardsville, IL, USA","institution_ids":["https://openalex.org/I87547150"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87547150"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28810985,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"189242","last_page":"189254"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9057999849319458,"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":0.9057999849319458,"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":0.04490000009536743,"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.005100000184029341,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.7615000009536743},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.6456000208854675},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.5839999914169312},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.5774000287055969},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5507000088691711},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5246999859809875},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.51419997215271},{"id":"https://openalex.org/keywords/slice-sampling","display_name":"Slice sampling","score":0.498199999332428},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.4975000023841858},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.45100000500679016}],"concepts":[{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.7615000009536743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6789000034332275},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.6456000208854675},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.5839999914169312},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.5774000287055969},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5507000088691711},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5246999859809875},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.51419997215271},{"id":"https://openalex.org/C170593435","wikidata":"https://www.wikidata.org/wiki/Q4128565","display_name":"Slice sampling","level":4,"score":0.498199999332428},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.4975000023841858},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46700000762939453},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.45339998602867126},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.45100000500679016},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4465000033378601},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.38929998874664307},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C2778803389","wikidata":"https://www.wikidata.org/wiki/Q7246866","display_name":"Probabilistic roadmap","level":4,"score":0.35920000076293945},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3296999931335449},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.3280999958515167},{"id":"https://openalex.org/C187192777","wikidata":"https://www.wikidata.org/wiki/Q381699","display_name":"Rejection sampling","level":5,"score":0.3212999999523163},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C192489979","wikidata":"https://www.wikidata.org/wiki/Q1502997","display_name":"Systematic sampling","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C129045301","wikidata":"https://www.wikidata.org/wiki/Q7144654","display_name":"Path length","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C2781050692","wikidata":"https://www.wikidata.org/wiki/Q5282869","display_name":"Distance sampling","level":3,"score":0.29670000076293945},{"id":"https://openalex.org/C82152865","wikidata":"https://www.wikidata.org/wiki/Q7208505","display_name":"Poisson sampling","level":5,"score":0.2782000005245209},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.27219998836517334},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2671999931335449},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2655999958515167},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C20326153","wikidata":"https://www.wikidata.org/wiki/Q7049638","display_name":"Nonuniform sampling","level":3,"score":0.2590000033378601},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C75917345","wikidata":"https://www.wikidata.org/wiki/Q2725298","display_name":"Sampling bias","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3628212","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3628212","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:13fdf5030cd1479ebf2d4a98f3fbc400","is_oa":true,"landing_page_url":"https://doaj.org/article/13fdf5030cd1479ebf2d4a98f3fbc400","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 189242-189254 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3628212","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3628212","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Path":[0],"planning":[1,53],"algorithms":[2,13],"are":[3,20],"a":[4,62,101],"crucial":[5],"component":[6],"of":[7,30],"robotic":[8],"navigation.":[9],"Among":[10],"them,":[11],"sampling-based":[12],"such":[14],"as":[15],"RRT*,":[16,124],"Informed-RRT*":[17,125],"and":[18,90,118,126,139],"BIT*":[19,127],"widely":[21],"adopted":[22],"in":[23,40,44],"complex":[24],"environments":[25],"due":[26],"to":[27,51,104],"their":[28,34],"property":[29],"asymptotic":[31],"optimality.":[32],"However,":[33],"reliance":[35],"on":[36,86],"random":[37],"sampling":[38,42,65,75,83,92,98,109],"results":[39],"low":[41],"efficiency":[43],"narrow":[45],"or":[46],"misleading":[47],"obstacle":[48],"scenarios,":[49],"leading":[50],"longer":[52],"times.":[54],"To":[55],"address":[56],"these":[57],"limitations,":[58],"this":[59],"paper":[60],"proposes":[61],"novel":[63],"Fusion-Guided":[64,97],"framework":[66,99],"(FG),":[67],"which":[68],"flexibly":[69],"integrates":[70],"Artificial":[71],"Potential":[72],"Field":[73],"(APF)-guided":[74],"for":[76,84,93],"goal-oriented":[77],"exploration,":[78],"Probability":[79],"Density":[80],"Function":[81],"(PDF)-based":[82],"focusing":[85],"key":[87],"geometric":[88],"features,":[89],"uniform":[91],"maintaining":[94],"global":[95],"exploration.":[96],"employs":[100],"probabilistic":[102],"mechanism":[103],"dynamically":[105],"switch":[106],"between":[107],"different":[108],"strategies,":[110],"significantly":[111],"improving":[112],"both":[113],"the":[114,130],"initial":[115,136],"path":[116,137],"search":[117],"subsequent":[119],"convergence.":[120],"Experimental":[121],"combination":[122],"with":[123,145],"demonstrate":[128],"that":[129],"proposed":[131],"method":[132],"consistently":[133],"achieves":[134],"shorter":[135],"length":[138],"convergence":[140],"time":[141],"across":[142],"three":[143],"scenarios":[144],"varying":[146],"characteristics.":[147]},"counts_by_year":[],"updated_date":"2025-11-23T05:10:03.516525","created_date":"2025-11-03T00:00:00"}