{"id":"https://openalex.org/W4312695223","doi":"https://doi.org/10.1109/iros47612.2022.9981537","title":"Excavation of Fragmented Rocks with Multi-modal Model-based Reinforcement Learning","display_name":"Excavation of Fragmented Rocks with Multi-modal Model-based Reinforcement Learning","publication_year":2022,"publication_date":"2022-10-23","ids":{"openalex":"https://openalex.org/W4312695223","doi":"https://doi.org/10.1109/iros47612.2022.9981537"},"language":"en","primary_location":{"id":"doi:10.1109/iros47612.2022.9981537","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9981537","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":"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/A5054450188","display_name":"Yifan Zhu","orcid":"https://orcid.org/0000-0002-4587-4305"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yifan Zhu","raw_affiliation_strings":["University of Illinois at Urbana-Champaign,Department of Computer Science,IL,USA","Department of Computer Science, University of Illinois at Urbana-Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign,Department of Computer Science,IL,USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Urbana-Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100749346","display_name":"Liyang Wang","orcid":"https://orcid.org/0000-0003-1454-4618"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liyang Wang","raw_affiliation_strings":["Baidu Research,Sunnyvale,CA,USA","Baidu Research, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"Baidu Research,Sunnyvale,CA,USA","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"Baidu Research, Sunnyvale, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101843628","display_name":"Liangjun Zhang","orcid":"https://orcid.org/0000-0003-1237-3384"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangjun Zhang","raw_affiliation_strings":["Baidu Research,Robotics and Auto-Driving Lab,Sunnyvale,CA,USA","Robotics and Auto-Driving Lab, Baidu Research, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"Baidu Research,Robotics and Auto-Driving Lab,Sunnyvale,CA,USA","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"Robotics and Auto-Driving Lab, Baidu Research, Sunnyvale, CA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054450188"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":1.4156,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.82264914,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"6523","last_page":"6530"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9896000027656555,"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":0.9896000027656555,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9731000065803528,"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":0.960099995136261,"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/computer-science","display_name":"Computer science","score":0.7297728061676025},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7238378524780273},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.7156163454055786},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6130010485649109},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5908626317977905},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5589550733566284},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.5115450620651245},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46071869134902954},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.45496493577957153},{"id":"https://openalex.org/keywords/excavation","display_name":"Excavation","score":0.43581336736679077},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.4285636246204376},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.425042062997818},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3246718645095825},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18888133764266968},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08792352676391602}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7297728061676025},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7238378524780273},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7156163454055786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6130010485649109},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5908626317977905},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5589550733566284},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.5115450620651245},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46071869134902954},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45496493577957153},{"id":"https://openalex.org/C31858485","wikidata":"https://www.wikidata.org/wiki/Q959782","display_name":"Excavation","level":2,"score":0.43581336736679077},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.4285636246204376},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.425042062997818},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3246718645095825},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18888133764266968},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08792352676391602},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros47612.2022.9981537","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9981537","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":35,"referenced_works":["https://openalex.org/W1967344654","https://openalex.org/W2087311215","https://openalex.org/W2108598243","https://openalex.org/W2133564696","https://openalex.org/W2150330033","https://openalex.org/W2151671764","https://openalex.org/W2157331557","https://openalex.org/W2194775991","https://openalex.org/W2281096776","https://openalex.org/W2296055201","https://openalex.org/W2403171414","https://openalex.org/W2442814322","https://openalex.org/W2507904268","https://openalex.org/W2728742905","https://openalex.org/W2804941773","https://openalex.org/W2908518653","https://openalex.org/W2911288409","https://openalex.org/W2953708620","https://openalex.org/W3004068580","https://openalex.org/W3012366945","https://openalex.org/W3043856150","https://openalex.org/W3049481978","https://openalex.org/W3098436915","https://openalex.org/W3126523611","https://openalex.org/W3127831513","https://openalex.org/W3175313230","https://openalex.org/W3185855727","https://openalex.org/W3205876759","https://openalex.org/W3207649131","https://openalex.org/W4211108606","https://openalex.org/W4321150118","https://openalex.org/W6679434410","https://openalex.org/W6760681535","https://openalex.org/W6764980988","https://openalex.org/W6780877826"],"related_works":["https://openalex.org/W4399671601","https://openalex.org/W2286924402","https://openalex.org/W1992962589","https://openalex.org/W2390668313","https://openalex.org/W3032871857","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1743191351","https://openalex.org/W2351306093","https://openalex.org/W1847088711"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,46,51,66,72,92,110],"multi-modal":[4,34,77],"model-based":[5],"reinforcement":[6],"learning":[7],"(MBRL)":[8],"approach":[9],"to":[10,20,23,91,102],"the":[11,40,62,98],"excavation":[12],"of":[13,42,54],"fragmented":[14],"rocks,":[15],"which":[16],"are":[17],"very":[18],"challenging":[19,111],"model":[21,67],"due":[22],"their":[24],"highly":[25],"variable":[26],"sizes":[27],"and":[28,30,97],"geometries,":[29],"visual":[31],"occlusions.":[32],"A":[33],"recurrent":[35],"neural":[36,94],"network":[37,95],"(RNN)":[38],"learns":[39],"dynamics":[41,84],"bucket-terrain":[43],"interaction":[44],"from":[45],"small":[47],"physical":[48],"dataset,":[49],"with":[50,58],"discrete":[52],"set":[53],"motion":[55],"primitives":[56],"encoded":[57],"domain":[59],"knowledge":[60],"as":[61],"action":[63],"space.":[64],"Then":[65],"predictive":[68],"controller":[69],"(MPC)":[70],"tracks":[71],"global":[73],"reference":[74],"path":[75],"using":[76],"feedback.":[78],"We":[79],"show":[80],"that":[81],"our":[82],"RNN-based":[83],"function":[85],"achieves":[86],"lower":[87],"prediction":[88],"errors":[89],"compared":[90],"feed-forward":[93],"baseline,":[96],"MPC":[99],"is":[100],"able":[101],"significantly":[103],"outperform":[104],"manually":[105],"designed":[106],"strategies":[107],"on":[108],"such":[109],"task.":[112]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
