{"id":"https://openalex.org/W7161168211","doi":"https://doi.org/10.48550/arxiv.2605.12897","title":"DynoJEPP: Joint Estimation, Prediction and Planning in Dynamic Environments","display_name":"DynoJEPP: Joint Estimation, Prediction and Planning in Dynamic Environments","publication_year":2026,"publication_date":"2026-05-13","ids":{"openalex":"https://openalex.org/W7161168211","doi":"https://doi.org/10.48550/arxiv.2605.12897"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.12897","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12897","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.12897","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116000595","display_name":"Mikolaj Kliniewski","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kliniewski, Mikolaj","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111882183","display_name":"Jesse Morris","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morris, Jesse","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101607122","display_name":"Yiduo Wang","orcid":"https://orcid.org/0000-0003-2975-2882"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yiduo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136124469","display_name":"Ian R. Manchester","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manchester, Ian R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5028642327","display_name":"Viorela Ila","orcid":"https://orcid.org/0000-0002-8137-0833"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ila, Viorela","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.3319999873638153,"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":0.3319999873638153,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.17679999768733978,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.15860000252723694,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/robot","display_name":"Robot","score":0.6118000149726868},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5656999945640564},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.5616999864578247},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5583999752998352},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.5408999919891357},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5277000069618225},{"id":"https://openalex.org/keywords/state-information","display_name":"State information","score":0.5030999779701233}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6732000112533569},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6118000149726868},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5656999945640564},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.5616999864578247},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5583999752998352},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.5408999919891357},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5277000069618225},{"id":"https://openalex.org/C2985963534","wikidata":"https://www.wikidata.org/wiki/Q7603704","display_name":"State information","level":3,"score":0.5030999779701233},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.4876999855041504},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.41179999709129333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33500000834465027},{"id":"https://openalex.org/C2779136372","wikidata":"https://www.wikidata.org/wiki/Q10283002","display_name":"Information flow","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C113336015","wikidata":"https://www.wikidata.org/wiki/Q574010","display_name":"Complete information","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2831999957561493},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.28200000524520874},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C2989549987","wikidata":"https://www.wikidata.org/wiki/Q350882","display_name":"Route planning","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.12897","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12897","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.12897","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.12897","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"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":{"DynoJEPP":[0,50],"is":[1],"a":[2,52],"factor-graph-based":[3,20],"framework":[4],"that":[5,22,56,94],"jointly":[6,23],"formulates":[7],"and":[8,13,27,32,44,67,88,134],"simultaneously":[9],"optimizes":[10],"estimation,":[11,25,38],"prediction,":[12,26],"planning":[14,33,68],"in":[15,85,108],"dynamic":[16,89],"environments.":[17,90],"In":[18],"conventional":[19],"approaches":[21],"formulate":[24],"planning,":[28],"information":[29,59],"from":[30,69],"prediction":[31,66,133],"feeds":[34],"back":[35],"into":[36,131],"state":[37,71],"yielding":[39],"corrupted":[40],"estimates,":[41],"undesired":[42],"behaviors,":[43],"unsafe":[45],"plans.":[46],"To":[47],"address":[48],"this,":[49,115],"introduces":[51],"novel":[53],"directed":[54,78],"factor":[55,63],"enforces":[57],"directional":[58],"flow":[60],"within":[61],"the":[62,75,105,109,123],"graph,":[64],"preventing":[65],"corrupting":[70],"estimation.":[72],"We":[73],"evaluate":[74],"impact":[76],"of":[77,111],"factors":[79,96],"on":[80,114],"inter-module":[81],"interactions":[82],"during":[83],"navigation":[84],"both":[86],"static":[87],"Our":[91],"results":[92],"demonstrate":[93],"these":[95],"are":[97],"critical":[98],"for":[99],"safe":[100],"operation,":[101],"as":[102],"without":[103],"them,":[104],"robot":[106,125],"collides":[107],"majority":[110],"experiments.":[112],"Building":[113],"we":[116],"further":[117],"introduce":[118],"Cooperative":[119],"DynoJEPP,":[120],"which":[121],"enables":[122],"ego":[124],"to":[126],"incorporate":[127],"cooperative":[128],"object":[129],"behavior":[130],"its":[132],"trajectory":[135],"planning.":[136]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-15T00:00:00"}