{"id":"https://openalex.org/W4312528276","doi":"https://doi.org/10.1109/iros47612.2022.9981562","title":"PoseIt: A Visual-Tactile Dataset of Holding Poses for Grasp Stability Analysis","display_name":"PoseIt: A Visual-Tactile Dataset of Holding Poses for Grasp Stability Analysis","publication_year":2022,"publication_date":"2022-10-23","ids":{"openalex":"https://openalex.org/W4312528276","doi":"https://doi.org/10.1109/iros47612.2022.9981562"},"language":"en","primary_location":{"id":"doi:10.1109/iros47612.2022.9981562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9981562","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049383717","display_name":"Shubham Kanitkar","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shubham Kanitkar","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034247227","display_name":"Helen Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Helen Jiang","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055947140","display_name":"Wenzhen Yuan","orcid":"https://orcid.org/0000-0001-8014-356X"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenzhen Yuan","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"71","last_page":"78"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9998999834060669,"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":0.9998999834060669,"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/T10784","display_name":"Muscle activation and electromyography studies","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10914","display_name":"Tactile and Sensory Interactions","score":0.9890000224113464,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.9589716196060181},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7833211421966553},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7427294254302979},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6803723573684692},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6242324709892273},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5556029081344604},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.507571816444397},{"id":"https://openalex.org/keywords/tactile-sensor","display_name":"Tactile sensor","score":0.4995996952056885},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4569452702999115},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.3611898124217987},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30130064487457275},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13067752122879028}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.9589716196060181},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7833211421966553},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7427294254302979},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6803723573684692},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6242324709892273},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5556029081344604},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.507571816444397},{"id":"https://openalex.org/C46722567","wikidata":"https://www.wikidata.org/wiki/Q7674139","display_name":"Tactile sensor","level":3,"score":0.4995996952056885},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4569452702999115},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3611898124217987},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30130064487457275},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13067752122879028},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros47612.2022.9981562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9981562","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1892339738","https://openalex.org/W1941659294","https://openalex.org/W1978580730","https://openalex.org/W2005824379","https://openalex.org/W2021473074","https://openalex.org/W2031763660","https://openalex.org/W2036637075","https://openalex.org/W2041376653","https://openalex.org/W2042599225","https://openalex.org/W2047887570","https://openalex.org/W2057299504","https://openalex.org/W2102727145","https://openalex.org/W2118262422","https://openalex.org/W2150936751","https://openalex.org/W2157692698","https://openalex.org/W2164126051","https://openalex.org/W2194775991","https://openalex.org/W2201912979","https://openalex.org/W2221877149","https://openalex.org/W2588205874","https://openalex.org/W2767106145","https://openalex.org/W2775635818","https://openalex.org/W2803104652","https://openalex.org/W2804941773","https://openalex.org/W2895765426","https://openalex.org/W2910771998","https://openalex.org/W2913153715","https://openalex.org/W2962736495","https://openalex.org/W2963915174","https://openalex.org/W2970941190","https://openalex.org/W3016311333","https://openalex.org/W3098436915","https://openalex.org/W3130633756","https://openalex.org/W6703610158","https://openalex.org/W6745274615","https://openalex.org/W6755778230","https://openalex.org/W6764733053"],"related_works":["https://openalex.org/W2163296013","https://openalex.org/W165915117","https://openalex.org/W3133406196","https://openalex.org/W2657478029","https://openalex.org/W3146859979","https://openalex.org/W2080808138","https://openalex.org/W2626503888","https://openalex.org/W4387962997","https://openalex.org/W2129483190","https://openalex.org/W4386395740"],"abstract_inverted_index":{"When":[0],"humans":[1],"grasp":[2,37,50,81],"objects":[3,184],"in":[4,17,137],"the":[5,15,33,36,46,49,57,62,74,106,111,116,127,152],"real":[6],"world,":[7],"we":[8,22,83,122],"often":[9],"move":[10],"our":[11,177],"arms":[12],"to":[13,108,182],"hold":[14],"object":[16,134],"a":[18,86,98,132,138],"different":[19],"pose":[20],"where":[21],"can":[23,123,179],"use":[24],"it.":[25],"In":[26],"contrast,":[27],"typical":[28],"lab":[29],"settings":[30],"only":[31],"study":[32,75],"stability":[34,51],"of":[35,45,76,101,110,129],"immediately":[38],"after":[39],"lifting,":[40],"without":[41],"any":[42],"subsequent":[43],"re-positioning":[44,105],"arm.":[47],"However,":[48],"could":[52,69],"vary":[53],"widely":[54],"based":[55],"on":[56,151,163],"object's":[58],"holding":[59,78],"pose,":[60],"as":[61],"gravitational":[63],"torque":[64],"and":[65,93,114,125,175,185],"gripper":[66],"contact":[67],"forces":[68],"change":[70],"completely.":[71],"To":[72],"facilitate":[73],"how":[77],"poses":[79],"affect":[80],"stability,":[82],"present":[84],"PoseIt,":[85,121],"novel":[87],"multi-modal":[88,160],"dataset":[89,189],"that":[90,147,159,176],"contains":[91],"visual":[92],"tactile":[94,173],"data":[95,119,174],"collected":[96],"from":[97,120],"full":[99],"cycle":[100],"grasping":[102],"an":[103,144],"object,":[104],"arm":[107],"one":[109],"sampled":[112],"poses,":[113],"shaking":[115],"object.":[117],"Using":[118],"formulate":[124],"tackle":[126],"task":[128],"predicting":[130],"whether":[131],"grasped":[133],"is":[135,190],"stable":[136],"particular":[139],"held":[140],"pose.":[141],"We":[142],"train":[143],"LSTM":[145],"classifier":[146],"achieves":[148],"85%":[149],"accuracy":[150,167],"proposed":[153],"task.":[154],"Our":[155],"experimental":[156],"results":[157],"show":[158],"models":[161],"trained":[162],"PoseIt":[164,188],"achieve":[165],"higher":[166],"than":[168],"using":[169],"solely":[170],"vision":[171],"or":[172],"classifiers":[178],"also":[180],"generalize":[181],"unseen":[183],"poses.":[186],"The":[187],"publicly":[191],"released":[192],"here:":[193],"https://github.com/CMURoboTouch/PoseIt.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
