{"id":"https://openalex.org/W7164531567","doi":"https://doi.org/10.48550/arxiv.2606.13394","title":"GeoHAT: Geometry-Adaptive Hybrid Action Transformer for Mobile Manipulation","display_name":"GeoHAT: Geometry-Adaptive Hybrid Action Transformer for Mobile Manipulation","publication_year":2026,"publication_date":"2026-06-11","ids":{"openalex":"https://openalex.org/W7164531567","doi":"https://doi.org/10.48550/arxiv.2606.13394"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.13394","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13394","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.13394","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138545377","display_name":"Xiangyu Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Xiangyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129657014","display_name":"Renjun Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Renjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037007371","display_name":"L. Ge","orcid":"https://orcid.org/0009-0006-8188-4507"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ge, Luzhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138530405","display_name":"Jinyan Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jinyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138514360","display_name":"Xuesong Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xuesong","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/T10653","display_name":"Robot Manipulation and Learning","score":0.8693000078201294,"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"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.8693000078201294,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.04450000077486038,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.020099999383091927,"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/encoder","display_name":"Encoder","score":0.6437000036239624},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4867999851703644},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4715000092983246},{"id":"https://openalex.org/keywords/active-perception","display_name":"Active perception","score":0.39089998602867126},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.38040000200271606},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.3587000072002411},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.3434999883174896},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.3264999985694885},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.323199987411499}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7595999836921692},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6437000036239624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.586899995803833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5435000061988831},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4867999851703644},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4715000092983246},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.39089998602867126},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.38040000200271606},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.3587000072002411},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3434999883174896},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.323199987411499},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.30140000581741333},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.2996000051498413},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.2874000072479248},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C194995250","wikidata":"https://www.wikidata.org/wiki/Q531136","display_name":"Affordance","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.13394","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13394","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.13394","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.13394","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":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6554431915283203,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Whole-body":[0],"mobile":[1,5],"manipulation":[2],"requires":[3],"coordinating":[4],"base":[6,41,154],"and":[7,17,36,40,88,153,158,179],"manipulator":[8],"under":[9,61],"shifting":[10],"viewpoints,":[11],"posing":[12],"challenges":[13],"in":[14],"geometric":[15,108],"perception":[16],"action":[18,44,144,161],"generation.":[19],"Current":[20],"policies":[21],"either":[22],"rely":[23],"on":[24,77,183,206],"2D":[25],"features":[26,126],"or":[27],"sparse":[28,170],"3D":[29,105,113],"representations":[30,60],"that":[31,46,101,189],"lack":[32],"dense":[33,54,103],"spatial":[34,99,141],"structure,":[35],"typically":[37],"encode":[38],"arm":[39,152],"within":[42],"one":[43],"vector":[45],"ignores":[47],"their":[48],"distinct":[49,156],"control":[50],"demands.":[51],"Moreover,":[52],"existing":[53],"fusion":[55,130],"strategies":[56],"risk":[57],"corrupting":[58],"pretrained":[59],"noisy":[62],"depth":[63,133],"while":[64,139,172],"incurring":[65],"heavy":[66],"computational":[67],"overhead.":[68],"We":[69],"present":[70],"GeoHAT,":[71],"an":[72,111],"end-to-end":[73],"diffusion-based":[74],"framework":[75],"built":[76],"a":[78,96,146,192],"simple":[79],"principle:":[80],"geometry":[81],"should":[82],"be":[83],"injected":[84,121],"only":[85,91],"where":[86,92],"reliable":[87],"attended":[89],"to":[90,164],"needed.":[93],"GeoHAT":[94,190],"employs":[95],"lightweight":[97],"Fourier":[98],"encoder":[100],"maps":[102],"per-pixel":[104],"coordinates":[106],"into":[107,122,155],"tokens":[109,117],"without":[110],"additional":[112],"vision":[114,123],"backbone.":[115],"These":[116],"are":[118],"then":[119],"selectively":[120],"foundation":[124],"model":[125],"through":[127,169],"per-token":[128],"gated":[129],"modulated":[131],"by":[132,201],"validity,":[134],"preserving":[135],"the":[136,184,198],"semantic":[137],"prior":[138],"enriching":[140],"understanding.":[142],"For":[143],"generation,":[145],"Hybrid":[147],"Whole-Body":[148],"Action":[149],"Decoder":[150],"decomposes":[151],"subspaces":[157],"lets":[159],"each":[160],"modality":[162],"attend":[163],"its":[165],"task-relevant":[166],"visual":[167],"context":[168],"cross-attention,":[171],"causal":[173],"temporal":[174],"modeling":[175],"captures":[176],"intra-timestep":[177],"coordination":[178],"inter-timestep":[180],"dependencies.":[181],"Experiments":[182],"ManiSkill-HAB":[185],"simulation":[186],"benchmark":[187],"demonstrate":[188],"achieves":[191],"79.3%":[193],"mean":[194],"success":[195],"rate,":[196],"surpassing":[197],"strongest":[199],"baseline":[200],"23.7%.":[202],"Furthermore,":[203],"real-world":[204],"experiments":[205],"diverse":[207],"tasks":[208],"also":[209],"confirm":[210],"consistent":[211],"improvements":[212],"over":[213],"all":[214],"baselines.":[215]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-13T00:00:00"}
