{"id":"https://openalex.org/W7140309623","doi":"https://doi.org/10.48550/arxiv.2603.22650","title":"MAGICIAN: Efficient Long-Term Planning with Imagined Gaussians for Active Mapping","display_name":"MAGICIAN: Efficient Long-Term Planning with Imagined Gaussians for Active Mapping","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7140309623","doi":"https://doi.org/10.48550/arxiv.2603.22650"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.22650","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22650","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.2603.22650","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130574817","display_name":"Shiyao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Shiyao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058831886","display_name":"Antoine Gu\u00e9don","orcid":"https://orcid.org/0009-0001-3107-4454"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu\u00e9don, Antoine","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130564433","display_name":"Shizhe Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Shizhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5070382607","display_name":"Vincent Lepetit","orcid":"https://orcid.org/0000-0001-9985-4433"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lepetit, Vincent","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.5501000285148621,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.5501000285148621,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.16410000622272491,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.07970000058412552,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6442000269889832},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6097999811172485},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.538100004196167},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4966999888420105},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.47209998965263367},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.3467000126838684},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3287999927997589}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7229999899864197},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6442000269889832},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6097999811172485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5813999772071838},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.538100004196167},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4966999888420105},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.47209998965263367},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38999998569488525},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.3467000126838684},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32109999656677246},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.3165999948978424},{"id":"https://openalex.org/C193611912","wikidata":"https://www.wikidata.org/wiki/Q4677596","display_name":"Active vision","level":2,"score":0.29910001158714294},{"id":"https://openalex.org/C114073186","wikidata":"https://www.wikidata.org/wiki/Q2631895","display_name":"Automated planning and scheduling","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C2989549987","wikidata":"https://www.wikidata.org/wiki/Q350882","display_name":"Route planning","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C57077369","wikidata":"https://www.wikidata.org/wiki/Q7075747","display_name":"Occupancy grid mapping","level":4,"score":0.2770000100135803},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.22650","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22650","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.2603.22650","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22650","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":[{"id":"https://metadata.un.org/sdg/11","score":0.7433359026908875,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Active":[0],"mapping":[1],"aims":[2],"to":[3,10],"determine":[4],"how":[5],"an":[6],"agent":[7],"should":[8],"move":[9],"efficiently":[11],"reconstruct":[12],"unknown":[13],"environments.":[14],"Most":[15],"existing":[16],"approaches":[17],"rely":[18],"on":[19,54],"greedy":[20],"next-best-view":[21],"prediction,":[22],"resulting":[23],"in":[24,101,125],"inefficient":[25],"exploration":[26],"and":[27,97,112],"incomplete":[28],"reconstruction.":[29],"To":[30],"address":[31],"this,":[32],"we":[33],"introduce":[34],"MAGICIAN,":[35],"a":[36,50,60,87,102],"novel":[37,77],"long-term":[38,123],"planning":[39,124],"framework":[40],"that":[41],"maximizes":[42],"accumulated":[43],"surface":[44],"coverage":[45,72],"gain":[46,73],"through":[47],"Imagined":[48,95],"Gaussians,":[49],"scene":[51],"representation":[52,69],"based":[53],"3D":[55],"Gaussian":[56],"Splatting,":[57],"derived":[58],"from":[59],"pre-trained":[61],"occupancy":[62],"network":[63],"with":[64,115],"strong":[65],"structural":[66],"priors.":[67],"This":[68],"enables":[70],"efficient":[71],"computation":[74],"for":[75,90],"any":[76],"viewpoint":[78],"via":[79],"fast":[80],"volumetric":[81],"rendering,":[82],"allowing":[83],"its":[84],"integration":[85],"into":[86],"tree-search":[88],"algorithm":[89],"long-horizon":[91],"planning.":[92],"We":[93],"update":[94],"Gaussians":[96],"refine":[98],"the":[99,120],"trajectory":[100],"closed":[103],"loop.":[104],"Our":[105],"method":[106],"achieves":[107],"state-of-the-art":[108],"performance":[109],"across":[110],"indoor":[111],"outdoor":[113],"benchmarks":[114],"varying":[116],"action":[117],"spaces,":[118],"highlighting":[119],"advantage":[121],"of":[122],"active":[126],"mapping.":[127]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-26T00:00:00"}
