{"id":"https://openalex.org/W2963795444","doi":"https://doi.org/10.1109/lra.2019.2930426","title":"GAPLE: Generalizable Approaching Policy LEarning for Robotic Object Searching in Indoor Environment","display_name":"GAPLE: Generalizable Approaching Policy LEarning for Robotic Object Searching in Indoor Environment","publication_year":2019,"publication_date":"2019-07-23","ids":{"openalex":"https://openalex.org/W2963795444","doi":"https://doi.org/10.1109/lra.2019.2930426","mag":"2963795444"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2019.2930426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2019.2930426","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-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/A5100348103","display_name":"Xin Ye","orcid":"https://orcid.org/0000-0002-1962-9031"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xin Ye","raw_affiliation_strings":["Active Perception Group, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA"],"raw_orcid":"https://orcid.org/0000-0002-1962-9031","affiliations":[{"raw_affiliation_string":"Active Perception Group, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101564904","display_name":"Zhe Lin","orcid":"https://orcid.org/0000-0003-1154-9907"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhe Lin","raw_affiliation_strings":["Adobe Inc., San Jose, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Inc., San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044267273","display_name":"Joon\u2010Young Lee","orcid":"https://orcid.org/0000-0003-4822-855X"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joon-Young Lee","raw_affiliation_strings":["Adobe Inc., San Jose, CA, USA"],"raw_orcid":"https://orcid.org/0000-0003-4822-855X","affiliations":[{"raw_affiliation_string":"Adobe Inc., San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036510129","display_name":"Jianming Zhang","orcid":"https://orcid.org/0000-0002-9954-6294"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianming Zhang","raw_affiliation_strings":["Adobe Inc., San Jose, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-9954-6294","affiliations":[{"raw_affiliation_string":"Adobe Inc., San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020196471","display_name":"Shibin Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shibin Zheng","raw_affiliation_strings":["Active Perception Group, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Active Perception Group, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002278578","display_name":"Yezhou Yang","orcid":"https://orcid.org/0000-0003-0126-8976"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yezhou Yang","raw_affiliation_strings":["Active Perception Group, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA"],"raw_orcid":"https://orcid.org/0000-0003-0126-8976","affiliations":[{"raw_affiliation_string":"Active Perception Group, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100348103"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":2.1443,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.90289426,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"4","issue":"4","first_page":"4003","last_page":"4010"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9997000098228455,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9987999796867371,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9930999875068665,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7768009305000305},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7257289290428162},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6739741563796997},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6518248915672302},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6394148468971252},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.543699324131012},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5314459204673767},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4911046028137207},{"id":"https://openalex.org/keywords/policy-learning","display_name":"Policy learning","score":0.4780305325984955},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.44204604625701904},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09236857295036316}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7768009305000305},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7257289290428162},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6739741563796997},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6518248915672302},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6394148468971252},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.543699324131012},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5314459204673767},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4911046028137207},{"id":"https://openalex.org/C2779436431","wikidata":"https://www.wikidata.org/wiki/Q30672407","display_name":"Policy learning","level":2,"score":0.4780305325984955},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.44204604625701904},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09236857295036316},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2019.2930426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2019.2930426","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8895109798","display_name":null,"funder_award_id":"IIS-1750082","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W65124300","https://openalex.org/W1905829557","https://openalex.org/W1915250530","https://openalex.org/W1978278938","https://openalex.org/W2047197161","https://openalex.org/W2117539524","https://openalex.org/W2145339207","https://openalex.org/W2194775991","https://openalex.org/W2531409750","https://openalex.org/W2575705757","https://openalex.org/W2593584281","https://openalex.org/W2593769898","https://openalex.org/W2783375473","https://openalex.org/W2799017078","https://openalex.org/W2883574738","https://openalex.org/W2950697717","https://openalex.org/W2950872548","https://openalex.org/W2952578114","https://openalex.org/W2962684798","https://openalex.org/W2962887844","https://openalex.org/W2963038646","https://openalex.org/W2963095800","https://openalex.org/W2963133245","https://openalex.org/W2963488291","https://openalex.org/W2963523627","https://openalex.org/W2963591054","https://openalex.org/W2964043796","https://openalex.org/W2964309882","https://openalex.org/W2967853831","https://openalex.org/W3103567320","https://openalex.org/W4294375521","https://openalex.org/W4297795161","https://openalex.org/W4298857966","https://openalex.org/W6629098493","https://openalex.org/W6637967152","https://openalex.org/W6682778277","https://openalex.org/W6692846177","https://openalex.org/W6729556111","https://openalex.org/W6729788943","https://openalex.org/W6730111887","https://openalex.org/W6731334075","https://openalex.org/W6745983339","https://openalex.org/W6746518932","https://openalex.org/W6747912417","https://openalex.org/W6751569509"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W2080152487","https://openalex.org/W2239445980","https://openalex.org/W2995553446","https://openalex.org/W2732813147","https://openalex.org/W2143460112"],"abstract_inverted_index":{"We":[0],"study":[1],"the":[2,45,55,62,96,99,108],"problem":[3],"of":[4,19,88],"learning":[5,101],"a":[6,69,75,113,117],"generalizable":[7,70],"action":[8],"policy":[9,100],"for":[10],"an":[11,17,22],"intelligent":[12],"agent":[13],"to":[14,98],"actively":[15],"approach":[16],"object":[18,56],"interest,":[20],"in":[21,116],"indoor":[23],"environment,":[24],"solely":[25],"from":[26,44],"its":[27],"visual":[28,34,89],"inputs.":[29],"While":[30],"scene-driven":[31],"or":[32],"recognition-driven":[33],"navigation":[35],"has":[36],"been":[37],"widely":[38],"studied,":[39],"prior":[40],"efforts":[41],"suffer":[42],"severely":[43],"limited":[46],"generalization":[47],"capability.":[48],"In":[49],"this":[50],"letter,":[51],"we":[52,73,124],"first":[53],"argue":[54],"searching":[57],"task":[58],"is":[59,65],"environment-dependent":[60],"while":[61],"approaching":[63,71],"ability":[64],"general.":[66],"To":[67],"learn":[68],"policy,":[72],"present":[74],"novel":[76],"solution":[77],"dubbed":[78],"as":[79,95],"Generalizable":[80],"Approaching":[81],"Policy":[82],"LEarning,":[83],"which":[84],"adopts":[85],"two":[86],"channels":[87],"features:":[90],"depth":[91],"and":[92,111,123],"semantic":[93],"segmentation,":[94],"inputs":[97],"module.":[102],"The":[103],"empirical":[104],"studies":[105],"conducted":[106],"on":[107,112],"House3D":[109],"dataset":[110],"physical":[114],"platform":[115],"real-world":[118],"scenario":[119],"validate":[120],"our":[121],"hypothesis,":[122],"further":[125],"provide":[126],"in-depth":[127],"qualitative":[128],"analysis.":[129]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
