{"id":"https://openalex.org/W7161788366","doi":"https://doi.org/10.48550/arxiv.2605.19420","title":"Beyond Waypoints: Dual-Heatmap Grounding for Cross-Embodiment Semantic Navigation","display_name":"Beyond Waypoints: Dual-Heatmap Grounding for Cross-Embodiment Semantic Navigation","publication_year":2026,"publication_date":"2026-05-19","ids":{"openalex":"https://openalex.org/W7161788366","doi":"https://doi.org/10.48550/arxiv.2605.19420"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.19420","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19420","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.2605.19420","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136590272","display_name":"Kaijie Yun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yun, Kaijie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136541040","display_name":"Yue Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"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":0.7261000275611877,"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":0.7261000275611877,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.06270000338554382,"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"}},{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.05950000137090683,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/affordance","display_name":"Affordance","score":0.7347000241279602},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.7175999879837036},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5302000045776367},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.48820000886917114},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.48739999532699585},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.482699990272522},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.43230000138282776},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4196000099182129},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4075999855995178}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7864000201225281},{"id":"https://openalex.org/C194995250","wikidata":"https://www.wikidata.org/wiki/Q531136","display_name":"Affordance","level":2,"score":0.7347000241279602},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.7175999879837036},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5302000045776367},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.48820000886917114},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.48739999532699585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48669999837875366},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.482699990272522},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.44830000400543213},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.43230000138282776},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.38920000195503235},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.38690000772476196},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.3330000042915344},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.2700999975204468},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.19420","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19420","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.2605.19420","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19420","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Grounding":[0],"open-ended":[1],"semantic":[2,52,71,120,210],"instructions":[3],"into":[4],"physically":[5],"executable":[6,191],"local":[7,127],"goals":[8],"is":[9],"a":[10,55,78,89,95,106,118,135,144,162,204],"fundamental":[11],"challenge":[12],"in":[13,86,190],"human-robot":[14],"interaction.":[15],"While":[16],"existing":[17],"navigation":[18,96],"frameworks":[19],"often":[20],"regress":[21],"deterministic":[22],"waypoints,":[23],"this":[24,42,131],"rigid":[25],"formulation":[26],"collapses":[27],"spatial":[28],"uncertainty":[29],"and":[30,62,73,142,165],"frequently":[31],"targets":[32,188],"non-traversable":[33],"object":[34],"centers,":[35],"leading":[36],"to":[37],"severe":[38],"execution":[39],"failures.":[40],"In":[41],"work,":[43],"we":[44,76,133],"focus":[45],"on":[46],"the":[47,67,182,198],"practical":[48],"setting":[49],"of":[50,88,200],"in-FOV":[51],"navigation,":[53],"where":[54],"robot":[56,170],"receives":[57],"concise,":[58],"interleaved":[59],"multimodal":[60],"(text":[61],"image)":[63],"prompts.":[64],"To":[65,129],"bridge":[66],"gap":[68],"between":[69],"abstract":[70],"intent":[72],"physical":[74],"reachability,":[75],"propose":[77],"unified":[79],"Vision-Language":[80],"framework":[81,93,153,195],"that":[82,99,151,176],"abandons":[83],"single-point":[84],"regression":[85],"favor":[87],"Dual-Heatmap":[90],"representation.":[91],"Our":[92],"predicts":[94],"affordance":[97],"heatmap":[98,108,178],"captures":[100],"continuous":[101],"reachable":[102],"regions,":[103],"coupled":[104],"with":[105,125],"facing":[107],"for":[109],"orientation":[110],"constraints.":[111],"These":[112],"dense":[113],"outputs":[114],"inherently":[115],"function":[116],"as":[117],"differentiable":[119],"potential":[121],"field,":[122],"integrating":[123],"seamlessly":[124],"downstream":[126],"planners.":[128],"support":[130],"paradigm,":[132],"build":[134],"fully":[136],"automated,":[137],"foundation-model-assisted":[138],"synthetic":[139],"data":[140],"pipeline":[141],"establish":[143],"comprehensive":[145],"simulation":[146,166],"benchmark.":[147],"Extensive":[148],"experiments":[149],"demonstrate":[150],"our":[152,194],"achieves":[154],"state-of-the-art":[155],"performance":[156],"among":[157],"comparable":[158],"8B":[159],"baselines.":[160],"Crucially,":[161],"feature-fusion":[163],"study":[164],"studies":[167],"across":[168],"diverse":[169],"embodiments":[171],"(Jetbot,":[172],"H1,":[173],"Aliengo)":[174],"reveal":[175],"explicit":[177],"prediction":[179],"drastically":[180],"improves":[181],"Affordance":[183],"Rate":[184],"(AR).":[185],"By":[186],"placing":[187],"reliably":[189],"free":[192],"space,":[193],"effectively":[196],"mitigates":[197],"brittleness":[199],"point":[201],"regression,":[202],"offering":[203],"transferable":[205],"path":[206],"toward":[207],"safe":[208],"cross-embodiment":[209],"navigation.":[211]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-21T00:00:00"}
