{"id":"https://openalex.org/W4211108606","doi":"https://doi.org/10.1109/lra.2022.3150511","title":"Excavation Reinforcement Learning Using Geometric Representation","display_name":"Excavation Reinforcement Learning Using Geometric Representation","publication_year":2022,"publication_date":"2022-02-12","ids":{"openalex":"https://openalex.org/W4211108606","doi":"https://doi.org/10.1109/lra.2022.3150511"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2022.3150511","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2022.3150511","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/A5028872990","display_name":"Qingkai Lu","orcid":"https://orcid.org/0000-0002-3820-475X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qingkai Lu","raw_affiliation_strings":["Robotics and Auto-Driving Lab, Baidu Research, Sunnyvale, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-3820-475X","affiliations":[{"raw_affiliation_string":"Robotics and Auto-Driving Lab, Baidu Research, Sunnyvale, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054450188","display_name":"Yifan Zhu","orcid":"https://orcid.org/0000-0002-4587-4305"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yifan Zhu","raw_affiliation_strings":["Robotics and Auto-Driving Lab, Baidu Research, Sunnyvale, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-4587-4305","affiliations":[{"raw_affiliation_string":"Robotics and Auto-Driving Lab, Baidu Research, Sunnyvale, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101843626","display_name":"Liangjun Zhang","orcid":"https://orcid.org/0000-0001-5737-2540"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liangjun Zhang","raw_affiliation_strings":["Robotics and Auto-Driving Lab, Baidu Research, Sunnyvale, CA, USA"],"raw_orcid":"https://orcid.org/0000-0001-5737-2540","affiliations":[{"raw_affiliation_string":"Robotics and Auto-Driving Lab, Baidu Research, Sunnyvale, CA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1281,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.85652034,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"7","issue":"2","first_page":"4472","last_page":"4479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12482","display_name":"Tunneling and Rock Mechanics","score":0.9830999970436096,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T12482","display_name":"Tunneling and Rock Mechanics","score":0.9830999970436096,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10653","display_name":"Robot Manipulation and Learning","score":0.9781000018119812,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9359999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/excavation","display_name":"Excavation","score":0.8342366814613342},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.7158608436584473},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7028300762176514},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6870326995849609},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6532536745071411},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6335103511810303},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6131913065910339},{"id":"https://openalex.org/keywords/plan","display_name":"Plan (archaeology)","score":0.5583434700965881},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5505155920982361},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49211210012435913},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1728953719139099},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.1661076545715332},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13950154185295105},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.09525713324546814},{"id":"https://openalex.org/keywords/archaeology","display_name":"Archaeology","score":0.06844061613082886},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06341469287872314}],"concepts":[{"id":"https://openalex.org/C31858485","wikidata":"https://www.wikidata.org/wiki/Q959782","display_name":"Excavation","level":2,"score":0.8342366814613342},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.7158608436584473},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7028300762176514},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6870326995849609},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6532536745071411},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6335103511810303},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6131913065910339},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.5583434700965881},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5505155920982361},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49211210012435913},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1728953719139099},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1661076545715332},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13950154185295105},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.09525713324546814},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.06844061613082886},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06341469287872314},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2022.3150511","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2022.3150511","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":[{"score":0.47999998927116394,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1852251700","https://openalex.org/W1899309388","https://openalex.org/W1905829557","https://openalex.org/W1967344654","https://openalex.org/W2066380996","https://openalex.org/W2074658631","https://openalex.org/W2087311215","https://openalex.org/W2150330033","https://openalex.org/W2151671764","https://openalex.org/W2153318775","https://openalex.org/W2157867424","https://openalex.org/W2403171414","https://openalex.org/W2442814322","https://openalex.org/W2507904268","https://openalex.org/W2570734388","https://openalex.org/W2674324363","https://openalex.org/W2728742905","https://openalex.org/W2736601468","https://openalex.org/W2787666871","https://openalex.org/W2790924949","https://openalex.org/W2798927139","https://openalex.org/W2908518653","https://openalex.org/W2911288409","https://openalex.org/W2976081675","https://openalex.org/W3004068580","https://openalex.org/W3005783773","https://openalex.org/W3012366945","https://openalex.org/W3039448353","https://openalex.org/W3049481978","https://openalex.org/W3087636018","https://openalex.org/W3093426589","https://openalex.org/W3107041087","https://openalex.org/W3126321819","https://openalex.org/W3126523611","https://openalex.org/W3127831513","https://openalex.org/W3175313230","https://openalex.org/W3185855727","https://openalex.org/W6739778489","https://openalex.org/W6741002519","https://openalex.org/W6763422710","https://openalex.org/W6783628644"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W2115214301","https://openalex.org/W1981531423","https://openalex.org/W2070318884","https://openalex.org/W1679012645","https://openalex.org/W2011939812","https://openalex.org/W1977371217"],"abstract_inverted_index":{"Excavation":[0],"of":[1,47,57,66,135,141,144],"irregular":[2,51,145],"rigid":[3,52,146],"objects":[4,147],"in":[5,106,148],"clutter,":[6],"such":[7],"as":[8],"fragmented":[9],"rocks":[10],"and":[11,23,39],"wood":[12],"blocks,":[13],"is":[14],"very":[15],"challenging":[16],"due":[17],"to":[18,35,42,96,137],"their":[19],"complex":[20],"interaction":[21],"dynamics":[22],"highly":[24],"variable":[25],"geometries.":[26],"In":[27],"this":[28,37,129],"paper,":[29],"we":[30,60,113],"adopt":[31],"reinforcement":[32],"learning":[33],"(RL)":[34],"tackle":[36],"challenge":[38],"learn":[40,62],"policies":[41],"plan":[43,138],"for":[44,50,88],"a":[45,63,103,110,139],"sequence":[46,140],"excavation":[48,58,142],"trajectories":[49,143],"objects,":[53],"given":[54],"point":[55,68],"clouds":[56],"scenes.Moreover,":[59],"separately":[61],"compact":[64],"representation":[65,84,121],"the":[67,83,116,120,132],"cloud":[69],"on":[70,109],"geometric":[71],"tasks":[72],"that":[73,81,115],"do":[74],"not":[75],"require":[76],"human":[77],"labeling.":[78],"We":[79],"show":[80,114],"using":[82,102],"reduces":[85],"training":[86],"time":[87],"RL,":[89],"while":[90],"achieving":[91],"similar":[92],"asymptotic":[93],"performance":[94],"compare":[95],"an":[97],"end-to-end":[98,123],"RL":[99,136],"algorithm.":[100],"When":[101],"policy":[104,117],"trained":[105,118],"simulation":[107],"directly":[108],"real":[111],"scene,":[112],"with":[119],"outperforms":[122],"RL.":[124],"To":[125],"our":[126],"best":[127],"knowledge,":[128],"letter":[130],"presents":[131],"first":[133],"application":[134],"clutter.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}