{"id":"https://openalex.org/W7155033584","doi":"https://doi.org/10.48550/arxiv.2604.18271","title":"EmbodiedLGR: Integrating Lightweight Graph Representation and Retrieval for Semantic-Spatial Memory in Robotic Agents","display_name":"EmbodiedLGR: Integrating Lightweight Graph Representation and Retrieval for Semantic-Spatial Memory in Robotic Agents","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7155033584","doi":"https://doi.org/10.48550/arxiv.2604.18271"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.18271","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18271","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":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.2604.18271","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072065132","display_name":"Paolo Riva","orcid":"https://orcid.org/0000-0002-9855-994X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Riva, Paolo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134144467","display_name":"Leonardo Gargani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gargani, Leonardo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008765839","display_name":"Matteo Frosi","orcid":"https://orcid.org/0000-0002-5936-7945"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Frosi, Matteo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134166990","display_name":"Matteo Matteucci","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Matteucci, Matteo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9732000231742859,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9732000231742859,"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":0.004999999888241291,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.002300000051036477,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.6269999742507935},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6238999962806702},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5863999724388123},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5577999949455261},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.555899977684021},{"id":"https://openalex.org/keywords/mnemonic","display_name":"Mnemonic","score":0.5440000295639038},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.5307999849319458},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5256999731063843}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7896000146865845},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.6269999742507935},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6238999962806702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6054999828338623},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5863999724388123},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5577999949455261},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.555899977684021},{"id":"https://openalex.org/C197792726","wikidata":"https://www.wikidata.org/wiki/Q191062","display_name":"Mnemonic","level":2,"score":0.5440000295639038},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.5307999849319458},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5256999731063843},{"id":"https://openalex.org/C192327766","wikidata":"https://www.wikidata.org/wiki/Q1038799","display_name":"Cognitive robotics","level":3,"score":0.45719999074935913},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4156999886035919},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.39719998836517334},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2831999957561493},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.275299996137619},{"id":"https://openalex.org/C103683099","wikidata":"https://www.wikidata.org/wiki/Q5370102","display_name":"Embodied agent","level":3,"score":0.27300000190734863},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25839999318122864}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.18271","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18271","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.18271","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18271","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":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":{"As":[0],"the":[1,11,42,46,56,69,86,112,120,150,162,182,187,211,215],"world":[2],"of":[3,16,45,105,119,149],"agentic":[4],"artificial":[5],"intelligence":[6],"applied":[7],"to":[8,35,59,71,79,186],"robotics":[9],"evolves,":[10],"need":[12,113],"for":[13,114,174],"agents":[14],"capable":[15],"building":[17],"and":[18,21,102,138,171,214],"retrieving":[19],"memories":[20],"observations":[22],"efficiently":[23],"is":[24,159],"increasing.":[25],"Robots":[26],"operating":[27,48,107],"in":[28,141,169,203],"complex":[29],"environments":[30],"must":[31],"build":[32],"memory":[33,117],"structures":[34],"enable":[36],"useful":[37],"human-robot":[38,207],"interactions":[39],"by":[40,122],"leveraging":[41],"mnemonic":[43],"representation":[44,118],"current":[47,188],"context.":[49],"People":[50],"interacting":[51],"with":[52,153],"robots":[53],"may":[54],"expect":[55],"embodied":[57,175],"agent":[58,70,97],"provide":[60,72],"information":[61,135],"about":[62,136],"locations,":[63],"events,":[64],"or":[65],"objects,":[66],"which":[67],"requires":[68],"precise":[73],"answers":[74],"within":[75],"human-like":[76],"inference":[77,170],"times":[78,173],"be":[80],"perceived":[81],"as":[82],"responsive.":[83],"We":[84],"propose":[85],"Embodied":[87],"Light":[88],"Graph":[89],"Retrieval":[90],"Agent":[91],"(EmbodiedLGR-Agent),":[92],"a":[93,124,142,154,197],"visual-language":[94,212],"model":[95,213],"(VLM)-driven":[96],"architecture":[98],"that":[99,132],"constructs":[100],"dense":[101],"efficient":[103,116],"representations":[104],"robot":[106],"environments.":[108],"EmbodiedLGR-Agent":[109,158,192],"directly":[110],"addresses":[111],"an":[115],"environment":[121],"providing":[123],"hybrid":[125],"building-retrieval":[126,216],"approach":[127],"built":[128],"on":[129,161,181,196],"parameter-efficient":[130],"VLMs":[131],"store":[133],"low-level":[134],"objects":[137],"their":[139],"positions":[140],"semantic":[143],"graph,":[144],"while":[145,177,209],"retaining":[146,178],"high-level":[147],"descriptions":[148],"observed":[151],"scenes":[152],"traditional":[155],"retrieval-augmented":[156],"architecture.":[157],"evaluated":[160],"popular":[163],"NaVQA":[164],"dataset,":[165],"achieving":[166],"state-of-the-art":[167,189],"performance":[168],"querying":[172],"agents,":[176],"competitive":[179],"accuracy":[180],"global":[183],"task":[184],"relative":[185],"approaches.":[190],"Moreover,":[191],"was":[193],"successfully":[194],"deployed":[195],"physical":[198],"robot,":[199],"showing":[200],"practical":[201],"utility":[202],"real-world":[204],"contexts":[205],"through":[206],"interaction,":[208],"running":[210],"pipeline":[217],"locally.":[218]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-22T00:00:00"}
