{"id":"https://openalex.org/W2783440693","doi":"https://doi.org/10.1109/coase.2017.8256195","title":"An algorithm for transferring parallel-jaw grasps between 3D mesh subsegments","display_name":"An algorithm for transferring parallel-jaw grasps between 3D mesh subsegments","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2783440693","doi":"https://doi.org/10.1109/coase.2017.8256195","mag":"2783440693"},"language":"en","primary_location":{"id":"doi:10.1109/coase.2017.8256195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coase.2017.8256195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","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/A5090422109","display_name":"Matthew Matl","orcid":"https://orcid.org/0000-0003-0173-2820"},"institutions":[{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Matl","raw_affiliation_strings":["AUTO LAB at UC Berkeley","EECS, Berkeley, UC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AUTO LAB at UC Berkeley","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"EECS, Berkeley, UC","institution_ids":["https://openalex.org/I134446601"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071607482","display_name":"Jeff Mahler","orcid":null},"institutions":[{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeff Mahler","raw_affiliation_strings":["AUTO LAB at UC Berkeley","EECS, Berkeley, UC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AUTO LAB at UC Berkeley","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"EECS, Berkeley, UC","institution_ids":["https://openalex.org/I134446601"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050342525","display_name":"Ken Goldberg","orcid":"https://orcid.org/0000-0002-2661-4524"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ken Goldberg","raw_affiliation_strings":["AUTO LAB at UC Berkeley","IEOR, Berkeley, UC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AUTO LAB at UC Berkeley","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"IEOR, Berkeley, UC","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4415,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57709995,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"22","issue":null,"first_page":"756","last_page":"763"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10868","display_name":"Soft Robotics and Applications","score":0.9840999841690063,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.8210371136665344},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6438553929328918},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.631519079208374},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6149618625640869},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5778576135635376},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5270885825157166},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.4611279368400574},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.437019944190979},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4346567392349243},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics","score":0.4336436986923218},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4270240366458893},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.42483627796173096},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41325005888938904},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2105221152305603},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.10677820444107056}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.8210371136665344},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6438553929328918},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.631519079208374},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6149618625640869},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5778576135635376},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5270885825157166},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.4611279368400574},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.437019944190979},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4346567392349243},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.4336436986923218},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4270240366458893},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42483627796173096},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41325005888938904},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2105221152305603},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.10677820444107056},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/coase.2017.8256195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coase.2017.8256195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th IEEE Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W645084999","https://openalex.org/W1510186039","https://openalex.org/W1568751436","https://openalex.org/W1794703952","https://openalex.org/W1974537989","https://openalex.org/W1978131245","https://openalex.org/W1980602022","https://openalex.org/W2028987140","https://openalex.org/W2029524207","https://openalex.org/W2034950486","https://openalex.org/W2036637075","https://openalex.org/W2050204708","https://openalex.org/W2060698516","https://openalex.org/W2068641309","https://openalex.org/W2076374635","https://openalex.org/W2085949256","https://openalex.org/W2088043683","https://openalex.org/W2090359754","https://openalex.org/W2118262422","https://openalex.org/W2156219259","https://openalex.org/W2160994953","https://openalex.org/W2295332248","https://openalex.org/W2414685554","https://openalex.org/W2560609797","https://openalex.org/W2999893964","https://openalex.org/W3004739592","https://openalex.org/W4243385754"],"related_works":["https://openalex.org/W2163296013","https://openalex.org/W2743859443","https://openalex.org/W2326995835","https://openalex.org/W165915117","https://openalex.org/W2059402478","https://openalex.org/W2123347777","https://openalex.org/W4387804363","https://openalex.org/W2019547100","https://openalex.org/W2477150073","https://openalex.org/W2515493494"],"abstract_inverted_index":{"In":[0],"this":[1,115],"paper,":[2],"we":[3],"present":[4],"an":[5],"algorithm":[6,38,67,78,116,137,156],"that":[7,134],"improves":[8],"the":[9,135,139,165],"rate":[10,141],"of":[11,129],"successful":[12],"grasp":[13,43,124,146],"transfer":[14,44,54],"between":[15,29,34],"3D":[16],"mesh":[17,22,46,72],"models":[18,94],"by":[19,100],"breaking":[20],"each":[21,71],"into":[23],"functional":[24],"subsegments":[25,31,69,86,103],"and":[26,82,91,132],"transferring":[27],"grasps":[28,152,167],"similar":[30,85,102],"rather":[32],"than":[33,164],"full":[35],"models.":[36],"This":[37],"combines":[39],"prior":[40],"research":[41],"on":[42,121,162],"with":[45,74,87,104,154],"segmentation":[47,77],"techniques":[48],"from":[49,70,147],"computer":[50],"graphics":[51],"to":[52,149],"successfully":[53],"contact":[55],"points":[56],"more":[57],"often":[58],"while":[59],"potentially":[60],"preserving":[61],"task-specific":[62],"knowledge":[63],"across":[64,126],"transfers.":[65],"The":[66],"extracts":[68],"model":[73],"a":[75,106,118,127,144],"customized":[76],"designed":[79],"for":[80,142],"speed":[81],"then":[83,98],"groups":[84],"D2":[88],"shape":[89],"descriptors":[90],"Gaussian":[92],"mixture":[93],"(GMMs).":[95],"Grasps":[96],"are":[97],"transferred":[99,145,153],"aligning":[101],"Super4PCS,":[105],"global":[107],"point":[108],"cloud":[109],"registration":[110],"algorithm.":[111],"We":[112],"experimentally":[113],"evaluated":[114],"against":[117],"non-segmenting":[119],"baseline":[120],"over":[122],"20,000":[123],"transfers":[125],"set":[128],"80":[130],"objects":[131],"found":[133],"segmentation-based":[136],"improved":[138],"success":[140],"finding":[143],"82%":[148],"98%.":[150],"Additionally,":[151],"our":[155],"were":[157],"only":[158],"8.7%":[159],"less":[160],"robust":[161],"average":[163],"original":[166],"without":[168],"any":[169],"local":[170],"re-planning.":[171]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
