{"id":"https://openalex.org/W7133988607","doi":"https://doi.org/10.48550/arxiv.2603.04329","title":"Gaussian Mixture-Based Inverse Perception Contract for Uncertainty-Aware Robot Navigation","display_name":"Gaussian Mixture-Based Inverse Perception Contract for Uncertainty-Aware Robot Navigation","publication_year":2026,"publication_date":"2026-03-04","ids":{"openalex":"https://openalex.org/W7133988607","doi":"https://doi.org/10.48550/arxiv.2603.04329"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.04329","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128158956","display_name":"Bingyao Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Bingyao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128197392","display_name":"Joonkyung Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Joonkyung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128193669","display_name":"Yiwei Lyu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lyu, Yiwei","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28360556,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.3930000066757202,"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":0.3930000066757202,"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":0.3490000069141388,"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":0.05889999866485596,"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/probabilistic-logic","display_name":"Probabilistic logic","score":0.6962000131607056},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5288000106811523},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4999000132083893},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4961000084877014},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49230000376701355},{"id":"https://openalex.org/keywords/ellipsoid","display_name":"Ellipsoid","score":0.4641999900341034},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.44130000472068787},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.43790000677108765}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6962000131607056},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5375999808311462},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5288000106811523},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4999000132083893},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4961000084877014},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49230000376701355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47870001196861267},{"id":"https://openalex.org/C57489055","wikidata":"https://www.wikidata.org/wiki/Q190046","display_name":"Ellipsoid","level":2,"score":0.4641999900341034},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.44130000472068787},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.43790000677108765},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.3652999997138977},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.3465999960899353},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3409000039100647},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.32280001044273376},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3192000091075897},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2992999851703644},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.2840999960899353},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.27140000462532043},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2578999996185303}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.04329","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.04329","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.04329","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":"pmh:doi:10.48550/arxiv.2603.04329","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"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":{"Reliable":[0],"navigation":[1,88],"in":[2,83,176,195],"cluttered":[3],"environments":[4],"requires":[5],"perception":[6,25,79],"outputs":[7],"that":[8,38,143,168],"are":[9],"not":[10],"only":[11],"accurate":[12],"but":[13],"also":[14],"equipped":[15],"with":[16,43,107,135],"uncertainty":[17,51,106,171],"sets":[18,37,85,112],"suitable":[19],"for":[20,148,180],"safe":[21,182],"control.":[22],"An":[23],"inverse":[24],"contract":[26],"(IPC)":[27],"provides":[28],"such":[29],"a":[30,53,68,196],"connection":[31],"by":[32],"mapping":[33],"perceptual":[34],"estimates":[35],"to":[36,63,104,132,146],"contain":[39],"the":[40,72,162,169],"ground":[41],"truth":[42],"high":[44],"confidence.":[45],"Existing":[46],"IPC":[47,103],"formulations,":[48],"however,":[49],"instantiate":[50],"as":[52],"single":[54],"ellipsoidal":[55,110],"set":[56],"and":[57,74,86,128,153,159,187],"rely":[58],"on":[59],"deterministic":[60,122],"trust":[61],"scores":[62],"guide":[64],"robot":[65,190],"motion.":[66],"Such":[67],"representation":[69],"cannot":[70],"capture":[71],"multi-modal":[73],"irregular":[75],"structure":[76],"of":[77,109,161],"fine-grained":[78],"errors,":[80],"often":[81],"resulting":[82,170],"over-conservative":[84],"degraded":[87],"performance.":[89],"In":[90],"this":[91],"work,":[92],"we":[93],"introduce":[94],"Gaussian":[95,115],"Mixture-based":[96],"Inverse":[97],"Perception":[98],"Contract":[99],"(GM-IPC),":[100],"which":[101],"extends":[102],"represent":[105],"unions":[108],"confidence":[111],"derived":[113],"from":[114],"mixture":[116],"models.":[117],"This":[118],"design":[119],"moves":[120],"beyond":[121],"single-set":[123],"abstractions,":[124],"enabling":[125,184],"fine-grained,":[126],"multi-modal,":[127],"non-convex":[129],"error":[130],"structures":[131],"be":[133,174],"captured":[134],"formal":[136],"guarantees.":[137],"A":[138],"learning":[139],"framework":[140],"is":[141],"presented":[142],"trains":[144],"GM-IPC":[145],"account":[147],"probabilistic":[149,197],"inclusion,":[150],"distribution":[151],"matching,":[152],"empty-space":[154],"penalties,":[155],"ensuring":[156],"both":[157],"validity":[158],"compactness":[160],"predicted":[163],"sets.":[164],"We":[165],"further":[166],"show":[167],"characterizations":[172],"can":[173],"leveraged":[175],"downstream":[177],"planning":[178],"frameworks":[179],"real-time":[181],"navigation,":[183],"less":[185],"conservative":[186],"more":[188],"adaptive":[189],"motion":[191],"while":[192],"preserving":[193],"safety":[194],"manner.":[198]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-06T00:00:00"}
