{"id":"https://openalex.org/W7172282430","doi":"https://doi.org/10.48550/arxiv.2607.29393","title":"AquaJEPA: An Action-Conditioned Multimodal JEPA Family for Underwater Robot Dynamics","display_name":"AquaJEPA: An Action-Conditioned Multimodal JEPA Family for Underwater Robot Dynamics","publication_year":2026,"publication_date":"2026-07-31","ids":{"openalex":"https://openalex.org/W7172282430","doi":"https://doi.org/10.48550/arxiv.2607.29393"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.29393","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.29393","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,"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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.29393","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135965738","display_name":"Alan-Barsag Gazzaev","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gazzaev, Alan-Barsag","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5144284420","display_name":"Alexey Gavrilov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gavrilov, Alexey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5144275931","display_name":"Sergey Muravyov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Muravyov, Sergey","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":null,"has_fulltext":false,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.8859999775886536,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.8859999775886536,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.012600000016391277,"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":0.010200000368058681,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.49219998717308044},{"id":"https://openalex.org/keywords/occupancy-grid-mapping","display_name":"Occupancy grid mapping","score":0.47589999437332153},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.46059998869895935},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.4253999888896942},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.4244999885559082},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.4219000041484833},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.41280001401901245},{"id":"https://openalex.org/keywords/replication","display_name":"Replication (statistics)","score":0.3709000051021576}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5982000231742859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5817000269889832},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.49219998717308044},{"id":"https://openalex.org/C57077369","wikidata":"https://www.wikidata.org/wiki/Q7075747","display_name":"Occupancy grid mapping","level":4,"score":0.47589999437332153},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.4253999888896942},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.4244999885559082},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.4219000041484833},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.41280001401901245},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4036000072956085},{"id":"https://openalex.org/C12590798","wikidata":"https://www.wikidata.org/wiki/Q3933199","display_name":"Replication (statistics)","level":2,"score":0.3709000051021576},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.33180001378059387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31450000405311584},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.3003999888896942},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26969999074935913},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2648000121116638},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.25949999690055847},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.2574999928474426},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.29393","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.29393","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,"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":"doi:10.48550/arxiv.2607.29393","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.29393","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,"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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.8635271787643433,"display_name":"Life below water","id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Underwater":[0],"robots":[1],"rely":[2],"on":[3,63,75],"complementary":[4],"sensors":[5],"whose":[6],"reliability":[7],"changes":[8],"abruptly":[9],"with":[10,135],"water":[11],"visibility":[12,83],"and":[13,32,41,49,57,87,106,150,164],"vehicle":[14],"motion.":[15],"We":[16],"introduce":[17],"AquaJEPA,":[18],"a":[19,38,120],"sensor-configurable":[20],"family":[21,70,167],"of":[22,66],"action-conditioned":[23],"joint-embedding":[24],"predictive":[25],"models":[26],"spanning":[27,80],"full":[28,157],"multimodal,":[29],"camera-only,":[30],"sonar-only,":[31],"sensor-dropout":[33,173],"configurations.":[34],"Its":[35],"members":[36],"share":[37],"latent":[39],"objective":[40],"receding-horizon":[42],"control":[43,163],"interface":[44],"that":[45,156],"predict":[46],"future":[47],"representations":[48],"physical":[50],"dynamics":[51,85],"from":[52,61],"camera,":[53],"forward-looking":[54],"sonar,":[55],"proprioception,":[56],"thruster":[58],"commands.":[59],"Trained":[60],"scratch":[62],"one":[64],"hour":[65],"action-labelled":[67],"data,":[68],"the":[69,93,136,165],"is":[71],"evaluated":[72],"in":[73,169],"Stonefish":[74],"120":[76],"fresh":[77],"paired":[78,114,126],"scenarios":[79],"unseen":[81],"layouts,":[82],"changes,":[84],"shifts,":[86],"scheduled":[88],"DVL":[89],"loss.":[90,179],"AquaJEPA-base":[91],"achieves":[92],"strongest":[94],"aggregate":[95],"closed-loop":[96],"performance,":[97],"improving":[98],"success":[99],"over":[100,161],"state-only":[101,162],"by":[102,110,132],"12.5":[103],"percentage":[104],"points":[105],"reducing":[107],"final":[108,127],"error":[109,128,147],"0.189":[111],"m;":[112],"both":[113],"95%":[115],"intervals":[116],"exclude":[117],"zero.":[118],"In":[119],"separate":[121],"three-seed":[122],"evaluation,":[123],"it":[124],"reduces":[125],"relative":[129],"to":[130],"AquaJEPA-S":[131],"0.118":[133],"m,":[134],"same":[137],"direction":[138],"for":[139],"every":[140],"seed.":[141],"AquaJEPA-robust":[142],"more":[143],"than":[144],"halves":[145],"prediction":[146,159],"during":[148],"camera":[149],"camera-DVL":[151],"blackouts.":[152],"These":[153],"results":[154],"show":[155],"multimodal":[158],"improves":[160],"sonar-only":[166],"member":[168],"this":[170],"benchmark,":[171],"while":[172],"training":[174],"provides":[175],"robustness":[176],"under":[177],"sensor":[178]},"counts_by_year":[],"updated_date":"2026-08-12T07:12:00.856984","created_date":"2026-08-04T00:00:00"}
