{"id":"https://openalex.org/W2951474871","doi":"https://doi.org/10.48550/arxiv.1610.03651","title":"Efficient Probabilistic Collision Detection for Non-Convex Shapes","display_name":"Efficient Probabilistic Collision Detection for Non-Convex Shapes","publication_year":2016,"publication_date":"2016-10-12","ids":{"openalex":"https://openalex.org/W2951474871","doi":"https://doi.org/10.48550/arxiv.1610.03651","mag":"2951474871"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1610.03651","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1610.03651","pdf_url":"https://arxiv.org/pdf/1610.03651","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1610.03651","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111818593","display_name":"Jae Sung Park","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Park, Jae Sung","raw_affiliation_strings":["Dept. of Computer Science, Univ. of North Carolina at Chapel Hill,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, Univ. of North Carolina at Chapel Hill,","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047669959","display_name":"Chonhyon Park","orcid":"https://orcid.org/0000-0002-6161-3498","observed_orcids":["https://orcid.org/0000-0002-6161-3498"]},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Park, Chonhyon","raw_affiliation_strings":["Dept. of Computer Science, Univ. of North Carolina at Chapel Hill,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, Univ. of North Carolina at Chapel Hill,","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004194238","display_name":"Dinesh Manocha","orcid":"https://orcid.org/0000-0001-7047-9801","observed_orcids":["https://orcid.org/0000-0001-7047-9801"]},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manocha, Dinesh","raw_affiliation_strings":["Dept. of Computer Science, Univ. of North Carolina at Chapel Hill,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, Univ. of North Carolina at Chapel Hill,","institution_ids":["https://openalex.org/I114027177"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114027177"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":0.8428000211715698,"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":0.8428000211715698,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.030899999663233757,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.0210999995470047,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convex-shape","display_name":"convex shape","score":0.7289999723434448},{"id":"https://openalex.org/keywords/normal-distribution","display_name":"normal distribution","score":0.8299999833106995},{"id":"https://openalex.org/keywords/hierarchical-representation","display_name":"hierarchical representation","score":0.7919999957084656},{"id":"https://openalex.org/keywords/trajectory-planning","display_name":"trajectory planning","score":0.8769999742507935},{"id":"https://openalex.org/keywords/robot-manipulators","display_name":"robot manipulators","score":0.703000009059906}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.661325216293335},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.6608729362487793},{"id":"https://openalex.org/C111110010","wikidata":"https://www.wikidata.org/wiki/Q2627315","display_name":"Convex combination","level":4,"score":0.5458441972732544},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5357728600502014},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4764048159122467},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.45390191674232483},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.45005369186401367},{"id":"https://openalex.org/C206194317","wikidata":"https://www.wikidata.org/wiki/Q1138624","display_name":"Convex hull","level":3,"score":0.44509726762771606},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.42820724844932556},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4220302700996399},{"id":"https://openalex.org/C199668693","wikidata":"https://www.wikidata.org/wiki/Q1550329","display_name":"Collision detection","level":3,"score":0.41611504554748535},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4120672941207886},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35034236311912537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30826735496520996},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.14971232414245605},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:1610.03651","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1610.03651","pdf_url":"https://arxiv.org/pdf/1610.03651","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2951474871","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1610.03651","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1610.03651","doi":"https://doi.org/10.48550/arxiv.1610.03651","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1610.03651","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,"listed_in":[],"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":"pmh:oai:arXiv.org:1610.03651","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1610.03651","pdf_url":"https://arxiv.org/pdf/1610.03651","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"score":0.6000000238418579,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2951474871.pdf","grobid_xml":"https://content.openalex.org/works/W2951474871.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W61873113","https://openalex.org/W123135564","https://openalex.org/W1497695555","https://openalex.org/W1964644507","https://openalex.org/W1999250663","https://openalex.org/W2024802078","https://openalex.org/W2053044028","https://openalex.org/W2065096474","https://openalex.org/W2069743430","https://openalex.org/W2103052138","https://openalex.org/W2123703543","https://openalex.org/W2125880285","https://openalex.org/W2126539456","https://openalex.org/W2151910862","https://openalex.org/W2166316739","https://openalex.org/W2171429862"],"related_works":["https://openalex.org/W2529897673","https://openalex.org/W2147438862","https://openalex.org/W2699102138","https://openalex.org/W2900705224","https://openalex.org/W3119633049","https://openalex.org/W2110046341","https://openalex.org/W2508158574","https://openalex.org/W2736386853","https://openalex.org/W2129112982","https://openalex.org/W2161269358","https://openalex.org/W1885187308","https://openalex.org/W2291459425","https://openalex.org/W158780599","https://openalex.org/W2132664947","https://openalex.org/W170466186","https://openalex.org/W2101426222","https://openalex.org/W2528420095","https://openalex.org/W1507383618","https://openalex.org/W3020035394","https://openalex.org/W2138550851"],"abstract_inverted_index":{"We":[0,35,57],"present":[1,36],"new":[2,39],"algorithms":[3,63],"to":[4,21,51],"perform":[5],"fast":[6,38],"probabilistic":[7],"collision":[8],"queries":[9],"between":[10],"convex":[11,45,66],"as":[12,14],"well":[13],"non-convex":[15,52,68],"objects.":[16],"Our":[17],"approach":[18,50],"is":[19],"applicable":[20],"general":[22],"shapes,":[23],"where":[24],"one":[25],"or":[26],"more":[27],"objects":[28],"are":[29],"represented":[30],"using":[31,54],"Gaussian":[32],"probability":[33],"distributions.":[34],"a":[37,42,79],"algorithm":[40],"for":[41,78],"pair":[43],"of":[44,61],"objects,":[46],"and":[47,67,74],"extend":[48],"the":[49,59],"models":[53],"hierarchical":[55],"representations.":[56],"highlight":[58],"performance":[60],"our":[62],"with":[64],"various":[65],"shapes":[69],"on":[70],"complex":[71],"synthetic":[72],"benchmarks":[73,77],"trajectory":[75],"planning":[76],"7-DOF":[80],"Fetch":[81],"robot":[82],"arm.":[83]},"counts_by_year":[],"updated_date":"2026-10-13T10:08:12.033832","created_date":"2025-10-10T00:00:00"}
