{"id":"https://openalex.org/W4395091156","doi":"https://doi.org/10.1007/s42979-024-02640-8","title":"Reliable and Accurate Implicit Neural Representation of Multiple Swept Volumes with Application to Safe Human\u2013Robot Interaction","display_name":"Reliable and Accurate Implicit Neural Representation of Multiple Swept Volumes with Application to Safe Human\u2013Robot Interaction","publication_year":2024,"publication_date":"2024-03-12","ids":{"openalex":"https://openalex.org/W4395091156","doi":"https://doi.org/10.1007/s42979-024-02640-8"},"language":"en","primary_location":{"id":"doi:10.1007/s42979-024-02640-8","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s42979-024-02640-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-024-02640-8.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s42979-024-02640-8.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000296906","display_name":"Ming-Hsiu Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ming-Hsiu Lee","raw_affiliation_strings":["Institute of Information Science, Academia Sinica, Nangang, Taipei, 11529, Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, Nangang, Taipei, 11529, Taiwan, ROC","institution_ids":["https://openalex.org/I4210098366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034523100","display_name":"Jing\u2010Sin Liu","orcid":"https://orcid.org/0000-0002-4935-8965"},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Jing-Sin Liu","raw_affiliation_strings":["Institute of Information Science, Academia Sinica, Nangang, Taipei, 11529, Taiwan, ROC"],"raw_orcid":"https://orcid.org/0000-0002-4935-8965","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, Nangang, Taipei, 11529, Taiwan, ROC","institution_ids":["https://openalex.org/I4210098366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034523100"],"corresponding_institution_ids":["https://openalex.org/I4210098366"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":0.3273,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50205047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"5","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9958000183105469,"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"}},{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/representation","display_name":"Representation (politics)","score":0.6487169861793518},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6133478283882141},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5676742792129517},{"id":"https://openalex.org/keywords/human\u2013robot-interaction","display_name":"Human\u2013robot interaction","score":0.4798850119113922},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4215453267097473}],"concepts":[{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6487169861793518},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6133478283882141},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5676742792129517},{"id":"https://openalex.org/C145460709","wikidata":"https://www.wikidata.org/wiki/Q859951","display_name":"Human\u2013robot interaction","level":3,"score":0.4798850119113922},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4215453267097473},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s42979-024-02640-8","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s42979-024-02640-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-024-02640-8.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s42979-024-02640-8","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s42979-024-02640-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-024-02640-8.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4395091156.pdf"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2002983110","https://openalex.org/W2017745767","https://openalex.org/W2043152949","https://openalex.org/W2100470760","https://openalex.org/W2146885748","https://openalex.org/W2147675181","https://openalex.org/W2164896732","https://openalex.org/W2789905221","https://openalex.org/W2910081881","https://openalex.org/W2921293840","https://openalex.org/W2945475836","https://openalex.org/W2963627347","https://openalex.org/W3009220630","https://openalex.org/W3033504397","https://openalex.org/W3034395814","https://openalex.org/W3045503639","https://openalex.org/W3114570494","https://openalex.org/W3120385703","https://openalex.org/W3125537303","https://openalex.org/W3132728277","https://openalex.org/W3163031895","https://openalex.org/W3164088261","https://openalex.org/W3174178900","https://openalex.org/W3184957317","https://openalex.org/W4229856339","https://openalex.org/W4233857083","https://openalex.org/W4247833119","https://openalex.org/W4297792192","https://openalex.org/W4309217139","https://openalex.org/W4387328860"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W4287179229","https://openalex.org/W3205513966","https://openalex.org/W3120459843","https://openalex.org/W4366547574","https://openalex.org/W3200191727"],"abstract_inverted_index":{"Abstract":[0],"In":[1],"automated":[2],"production":[3],"using":[4,35],"collaborative":[5],"robots":[6,25],"in":[7,26,127,150,219,239,248],"a":[8,11,63,68,79,171,177,193],"manufacturing":[9],"cell,":[10],"crucial":[12],"aspect":[13],"is":[14,34,117,235,246],"to":[15,18,40,66,98,119],"avoid":[16],"collisions":[17,33],"ensure":[19],"the":[20,36,89,99,114,121,128,133,139,143,158,161,185,189,199,202,220,226,249],"safety":[21],"of":[22,62,70,81,94,101,109,123,142,147,152,160,188,195,201,215],"workers":[23],"and":[24,51,83,92,131,164,205,242],"human\u2013robot":[27,221],"interaction.":[28],"One":[29],"approach":[30],"for":[31,45,175],"detecting":[32],"swept":[37],"volume":[38],"(SV)":[39],"identify":[41],"safe":[42],"protective":[43],"space":[44],"operation.":[46],"We":[47,137],"learn":[48],"an":[49,230],"accurate":[50],"reliable":[52],"signed":[53],"distance":[54,108,156,194],"function":[55],"(SDF)":[56],"network":[57,76,174],"from":[58,157,198],"raw":[59],"point":[60],"clouds":[61],"pre-computed":[64],"SV":[65,179],"represent":[67],"class":[69],"linear":[71],"joint":[72],"motion":[73],"trajectories.":[74],"The":[75,107,237],"requires":[77],"only":[78],"set":[80],"parameters":[82],"constant":[84],"execution":[85,218,240],"time,":[86],"thus":[87],"reducing":[88],"computational":[90,134],"time":[91,241],"memory":[93],"collision":[95,110,124,233,243],"checking":[96],"due":[97],"complexity":[100],"explicit":[102],"geometry":[103,190],"during":[104],"task":[105,217],"execution.":[106],"danger":[111],"foresaw":[112],"by":[113,167,224],"learned":[115,227],"SDF":[116,228],"exploited":[118],"reduce":[120,132],"frequency":[122],"detection":[125,244],"calls":[126],"dynamic":[129],"environment":[130],"cost":[135],"further.":[136],"assess":[138],"relative":[140],"merits":[141],"implicit":[144],"neural":[145],"representation":[146],"multiple":[148],"SVs":[149],"terms":[151],"F":[153],"1-score,":[154],"error":[155],"surface":[159,200],"truth":[162,203],"geometry,":[163,204],"3D":[165],"visualization":[166],"comparing":[168],"favorably":[169],"with":[170,180],"binary":[172],"voxel":[173],"learning":[176],"single":[178],"similar":[181],"inference":[182],"time.":[183],"All":[184],"predicted":[186],"errors":[187,208],"lie":[191],"within":[192,210],"4":[196],"voxels":[197],"most":[206],"reconstruction":[207],"are":[209],"3":[211],"voxels.":[212],"A":[213],"simulation":[214],"pick-and-place":[216],"interaction":[222],"scenarios":[223],"leveraging":[225],"as":[229],"efficient":[231],"continuous":[232],"detector":[234],"performed.":[236],"improvement":[238],"number":[245],"validated":[247],"simulation.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
