{"id":"https://openalex.org/W7149024832","doi":"https://doi.org/10.48550/arxiv.2604.02038","title":"O-ConNet: Geometry-Aware End-to-End Inference of Over-Constrained Spatial Mechanisms","display_name":"O-ConNet: Geometry-Aware End-to-End Inference of Over-Constrained Spatial Mechanisms","publication_year":2026,"publication_date":"2026-04-02","ids":{"openalex":"https://openalex.org/W7149024832","doi":"https://doi.org/10.48550/arxiv.2604.02038"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.02038","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02038","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.2604.02038","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132878221","display_name":"Haoyu Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Haoyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132882912","display_name":"Meng Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Meng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100610983","display_name":"Tianhao Wang","orcid":"https://orcid.org/0000-0002-2126-6110"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Tianhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5043023421","display_name":"Jianxu Wu","orcid":"https://orcid.org/0000-0002-9732-8322"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jianxu","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/T11206","display_name":"Model Reduction and Neural Networks","score":0.1720000058412552,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.1720000058412552,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.13760000467300415,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10571","display_name":"Robotic Mechanisms and Dynamics","score":0.1354999989271164,"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/constraint","display_name":"Constraint (computer-aided design)","score":0.6884999871253967},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6019999980926514},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5925999879837036},{"id":"https://openalex.org/keywords/kinematics","display_name":"Kinematics","score":0.5112000107765198},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.5044999718666077},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4625000059604645},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4262999892234802},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.38499999046325684}],"concepts":[{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.6884999871253967},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.619700014591217},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6019999980926514},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5925999879837036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5458999872207642},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.5112000107765198},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.5044999718666077},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.489300012588501},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4262999892234802},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.38499999046325684},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2969000041484833},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2847999930381775},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2791000008583069},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.02038","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02038","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.2604.02038","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.02038","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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.45019182562828064}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning":[1,103],"has":[2],"shown":[3],"strong":[4],"potential":[5],"for":[6,114],"scientific":[7],"discovery,":[8],"but":[9],"its":[10],"ability":[11],"to":[12],"model":[13],"macroscopic":[14],"rigid-body":[15],"kinematic":[16],"constraints":[17],"remains":[18],"underexplored.":[19],"We":[20],"study":[21],"this":[22],"problem":[23],"on":[24],"spatial":[25,118],"over-constrained":[26,119],"mechanisms":[27,120],"and":[28,74,94,109],"propose":[29],"O-ConNet,":[30],"an":[31],"end-to-end":[32,102],"framework":[33],"that":[34,101],"infers":[35],"mechanism":[36],"structural":[37],"parameters":[38],"from":[39],"only":[40],"three":[41],"sparse":[42,123],"reachable":[43],"points":[44],"while":[45],"reconstructing":[46],"the":[47,86],"full":[48],"motion":[49],"trajectory,":[50],"without":[51],"explicitly":[52],"solving":[53],"constraint":[54],"equations":[55],"during":[56],"inference.":[57],"On":[58],"a":[59,111],"self-constructed":[60],"Bennett":[61],"4R":[62],"dataset":[63],"of":[64,117],"42,860":[65],"valid":[66],"samples,":[67],"O-ConNet":[68],"achieves":[69],"Param-MAE":[70],"0.276":[71],"+/-":[72,77,80],"0.077":[73],"Traj-MAE":[75],"0.145":[76],"0.018":[78],"(mean":[79],"std":[81],"over":[82],"10":[83],"runs),":[84],"outperforming":[85],"strongest":[87],"sequence":[88],"baseline":[89],"(LSTM-Seq2Seq)":[90],"by":[91],"65.1":[92],"percent":[93],"88.2":[95],"percent,":[96],"respectively.":[97],"These":[98],"results":[99],"suggest":[100],"can":[104],"capture":[105],"closed-loop":[106],"geometric":[107],"structure":[108],"provide":[110],"practical":[112],"route":[113],"inverse":[115],"design":[116],"under":[121],"extremely":[122],"observations.":[124]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-04T00:00:00"}
