{"id":"https://openalex.org/W2774004838","doi":"https://doi.org/10.1109/iros.2017.8202193","title":"Shape-based object classification and recognition through continuum manipulation","display_name":"Shape-based object classification and recognition through continuum manipulation","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2774004838","doi":"https://doi.org/10.1109/iros.2017.8202193","mag":"2774004838"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2017.8202193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2017.8202193","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"article","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/A5048873138","display_name":"Huitan Mao","orcid":"https://orcid.org/0000-0003-1148-6555"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Huitan Mao","raw_affiliation_strings":["Department of Computer Science, University of North Carolina, Charlotte"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of North Carolina, Charlotte","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070173803","display_name":"Jing Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jing Xiao","raw_affiliation_strings":["Department of Computer Science, University of North Carolina, Charlotte"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of North Carolina, Charlotte","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079568748","display_name":"Mabel M. Zhang","orcid":"https://orcid.org/0000-0002-5130-1183"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mabel M. Zhang","raw_affiliation_strings":["GRASP Laboratory, University of Pennsylvania"],"affiliations":[{"raw_affiliation_string":"GRASP Laboratory, University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050660826","display_name":"Kostas Daniilidis","orcid":"https://orcid.org/0000-0003-0498-0758"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kostas Daniilidis","raw_affiliation_strings":["GRASP Laboratory, University of Pennsylvania"],"affiliations":[{"raw_affiliation_string":"GRASP Laboratory, University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5048873138"],"corresponding_institution_ids":["https://openalex.org/I102149020"],"apc_list":null,"apc_paid":null,"fwci":1.4081,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.83302402,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"456","last_page":"463"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9994000196456909,"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":0.9994000196456909,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9940000176429749,"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/T11301","display_name":"Advanced Surface Polishing Techniques","score":0.9915000200271606,"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/computer-science","display_name":"Computer science","score":0.6309547424316406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6290220618247986},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.5641181468963623},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5192201733589172},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.44846591353416443},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44792649149894714}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6309547424316406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6290220618247986},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.5641181468963623},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5192201733589172},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.44846591353416443},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44792649149894714}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros.2017.8202193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2017.8202193","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309106","display_name":"Clemson University","ror":"https://ror.org/037s24f05"},{"id":"https://openalex.org/F4320337396","display_name":"Division of Industrial Innovation and Partnerships","ror":"https://ror.org/03xyg3m20"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W31424620","https://openalex.org/W102778925","https://openalex.org/W1560724230","https://openalex.org/W1601081659","https://openalex.org/W1625390266","https://openalex.org/W1746819321","https://openalex.org/W1780555481","https://openalex.org/W1891615552","https://openalex.org/W1972094833","https://openalex.org/W1978131245","https://openalex.org/W1984974392","https://openalex.org/W2011792403","https://openalex.org/W2021314974","https://openalex.org/W2036637075","https://openalex.org/W2041376653","https://openalex.org/W2043484674","https://openalex.org/W2050595634","https://openalex.org/W2051359602","https://openalex.org/W2095462685","https://openalex.org/W2096645690","https://openalex.org/W2104347990","https://openalex.org/W2109081464","https://openalex.org/W2115846099","https://openalex.org/W2119531408","https://openalex.org/W2126316555","https://openalex.org/W2126828342","https://openalex.org/W2127212794","https://openalex.org/W2137907155","https://openalex.org/W2145501120","https://openalex.org/W2161099435","https://openalex.org/W2164891910","https://openalex.org/W2180140657","https://openalex.org/W2218213558","https://openalex.org/W2334110889","https://openalex.org/W2565250676","https://openalex.org/W2566450466","https://openalex.org/W2737131067","https://openalex.org/W2747605198","https://openalex.org/W3112422759","https://openalex.org/W3195149063","https://openalex.org/W4211049957","https://openalex.org/W6601271567","https://openalex.org/W6636578284","https://openalex.org/W6638109603","https://openalex.org/W6661294129","https://openalex.org/W6663252827","https://openalex.org/W6685602438"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W1969923398","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2079911747","https://openalex.org/W2170022336"],"abstract_inverted_index":{"We":[0],"introduce":[1],"a":[2,15,23,31],"novel":[3],"approach":[4,46],"to":[5,93],"shape-based":[6],"object":[7,29,52],"classification":[8],"and":[9,49,81,95,112],"recognition":[10,50,67,85,103],"through":[11],"the":[12,19,40,43,56,63,115],"use":[13],"of":[14,39,42,51,58,68,86,89,117],"continuum":[16,24,59],"manipulator.":[17],"Noticing":[18],"fact":[20],"that":[21,70],"when":[22],"manipulator":[25],"wraps":[26],"around":[27],"an":[28],"in":[30,99],"whole-arm":[32],"grasping,":[33],"its":[34],"own":[35],"shape":[36,41,97],"is":[37],"indicative":[38],"object,":[44],"our":[45,118],"enables":[47],"learning":[48],"classes":[53],"based":[54,104],"on":[55,105],"shapes":[57],"wraps.":[60],"It":[61],"offers":[62],"following":[64],"advantages:":[65],"(1)":[66],"objects":[69,88],"are":[71],"not":[72],"easily":[73],"detected":[74],"by":[75],"vision,":[76],"such":[77,87],"as":[78],"transparent":[79],"objects,":[80],"(2)":[82],"highly":[83],"efficient":[84],"varied":[90],"sizes":[91],"due":[92],"high-level":[94],"rich":[96],"information":[98],"each":[100],"wrap,":[101],"unlike":[102],"tactile":[106],"sensing":[107],"via":[108],"conventional":[109],"grasping.":[110],"Simulation":[111],"experiments":[113],"demonstrate":[114],"effectiveness":[116],"approach.":[119]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
