{"id":"https://openalex.org/W4281696864","doi":"https://doi.org/10.1109/lra.2022.3178791","title":"Deep Reinforcement Learning for Robot Collision Avoidance With Self-State-Attention and Sensor Fusion","display_name":"Deep Reinforcement Learning for Robot Collision Avoidance With Self-State-Attention and Sensor Fusion","publication_year":2022,"publication_date":"2022-06-07","ids":{"openalex":"https://openalex.org/W4281696864","doi":"https://doi.org/10.1109/lra.2022.3178791"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2022.3178791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2022.3178791","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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/A5035402576","display_name":"Yiheng Han","orcid":"https://orcid.org/0000-0002-3986-7555"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiheng Han","raw_affiliation_strings":["BNRist, MOE-Key Laboratory of Pervasive Computing, Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3986-7555","affiliations":[{"raw_affiliation_string":"BNRist, MOE-Key Laboratory of Pervasive Computing, Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080199770","display_name":"Irvin Haozhe Zhan","orcid":"https://orcid.org/0000-0003-3391-5437"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Irvin Haozhe Zhan","raw_affiliation_strings":["BNRist, MOE-Key Laboratory of Pervasive Computing, Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3391-5437","affiliations":[{"raw_affiliation_string":"BNRist, MOE-Key Laboratory of Pervasive Computing, Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036441647","display_name":"Wang Zhao","orcid":"https://orcid.org/0000-0001-8925-8574"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Zhao","raw_affiliation_strings":["BNRist, MOE-Key Laboratory of Pervasive Computing, Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8925-8574","affiliations":[{"raw_affiliation_string":"BNRist, MOE-Key Laboratory of Pervasive Computing, Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076812698","display_name":"Jia Pan","orcid":"https://orcid.org/0000-0001-9003-2054"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jia Pan","raw_affiliation_strings":["Department of Computer Science, University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-9003-2054","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107808892","display_name":"Ziyang Zhang","orcid":"https://orcid.org/0000-0001-9543-2567"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyang Zhang","raw_affiliation_strings":["Advanced Computing and Storage Laboratory, Huawei Technologies Company Ltd, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Computing and Storage Laboratory, Huawei Technologies Company Ltd, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107808569","display_name":"Yaoyuan Wang","orcid":"https://orcid.org/0000-0003-1060-4898"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaoyuan Wang","raw_affiliation_strings":["Advanced Computing and Storage Laboratory, Huawei Technologies Company Ltd, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Computing and Storage Laboratory, Huawei Technologies Company Ltd, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008076279","display_name":"Yong\u2010Jin Liu","orcid":"https://orcid.org/0000-0001-5774-1916"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong-Jin Liu","raw_affiliation_strings":["BNRist, MOE-Key Laboratory of Pervasive Computing, Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5774-1916","affiliations":[{"raw_affiliation_string":"BNRist, MOE-Key Laboratory of Pervasive Computing, Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.4548,"has_fulltext":false,"cited_by_count":61,"citation_normalized_percentile":{"value":0.96177471,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"7","issue":"3","first_page":"6886","last_page":"6893"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9994999766349792,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9994999766349792,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10036","display_name":"Advanced Neural Network Applications","score":0.9980999827384949,"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/lidar","display_name":"Lidar","score":0.7766966819763184},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7578278183937073},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6788321733474731},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6693179607391357},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6602556109428406},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6190386414527893},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.49519744515419006},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.48834463953971863},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.42317935824394226},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.4129367470741272},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3782484829425812},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.26935112476348877},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.252613365650177},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.14088061451911926}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7766966819763184},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7578278183937073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6788321733474731},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6693179607391357},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6602556109428406},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6190386414527893},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.49519744515419006},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.48834463953971863},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.42317935824394226},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.4129367470741272},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3782484829425812},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.26935112476348877},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.252613365650177},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.14088061451911926},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2022.3178791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2022.3178791","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G1736198338","display_name":null,"funder_award_id":"61725204","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W178419168","https://openalex.org/W192919555","https://openalex.org/W1803059841","https://openalex.org/W1976517551","https://openalex.org/W2006140353","https://openalex.org/W2082585576","https://openalex.org/W2097639646","https://openalex.org/W2117211893","https://openalex.org/W2117539524","https://openalex.org/W2125409550","https://openalex.org/W2132400125","https://openalex.org/W2132947399","https://openalex.org/W2137448073","https://openalex.org/W2142943472","https://openalex.org/W2150066425","https://openalex.org/W2554243884","https://openalex.org/W2565555125","https://openalex.org/W2604216058","https://openalex.org/W2736601468","https://openalex.org/W2884233967","https://openalex.org/W2890001928","https://openalex.org/W2937151783","https://openalex.org/W2962741876","https://openalex.org/W2962917939","https://openalex.org/W2963045776","https://openalex.org/W2963428623","https://openalex.org/W2963544079","https://openalex.org/W2963591054","https://openalex.org/W2963821308","https://openalex.org/W2964326562","https://openalex.org/W2967115342","https://openalex.org/W2967847744","https://openalex.org/W2968217299","https://openalex.org/W3031798691","https://openalex.org/W3110653837","https://openalex.org/W3129265786","https://openalex.org/W3131482536","https://openalex.org/W3204464332","https://openalex.org/W6631190155","https://openalex.org/W6685261749","https://openalex.org/W6693682517","https://openalex.org/W6741002519","https://openalex.org/W6753807494","https://openalex.org/W6761677890"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W1964041166","https://openalex.org/W4390887692","https://openalex.org/W4293094720","https://openalex.org/W2739701376"],"abstract_inverted_index":{"3D":[0,5],"LiDAR":[1,20,77,114,143,226],"sensors":[2,21],"can":[3,22,70,165,194,217],"provide":[4,24],"point":[6,25,118],"clouds":[7,119],"of":[8,40,89,105,111,149],"the":[9,101,109,112,129],"environment,":[10],"and":[11,32,65,79,139,145,184,188,201,209,228],"are":[12,34],"widely":[13],"used":[14,36],"in":[15,27,120],"automobile":[16],"navigation;":[17],"while":[18],"2D":[19,29,76,113,135,142,225],"only":[23,35,222],"cloud":[26],"a":[28,52,67,75,80,85,121,134,157,173,182,210],"sweeping":[30],"plane,":[31],"then":[33],"for":[37,178],"navigating":[38],"robots":[39],"small":[41],"height,":[42],"e.g.,":[43],"floor":[44],"mopping":[45],"robots.":[46],"In":[47],"this":[48,192],"letter,":[49],"we":[50,98],"propose":[51],"simple":[53],"yet":[54],"effective":[55,185],"deep":[56],"reinforcement":[57],"learning":[58],"(DRL)":[59],"method":[60,216],"with":[61,108,123,141,152,167],"our":[62,153,215],"self-state-attention":[63,154,186],"unit":[64,155,187,193],"give":[66],"solution":[68],"that":[69,97,164,190,214],"use":[71,148],"low-cost":[72,224],"devices":[73],"(i.e.,":[74,117],"sensor":[78,115,227],"monocular":[81,229],"camera)":[82],"to":[83,156],"navigate":[84],"tall":[86],"mobile":[87],"robot":[88,179,212],"one":[90],"meter":[91],"height.":[92],"The":[93],"overrall":[94],"pipeline":[95],"is":[96],"(1)":[99],"infer":[100],"dense":[102,130],"depth":[103,131,137],"information":[104],"RGB":[106],"images":[107],"aid":[110],"data":[116,138,208],"plane":[122],"fixed":[124],"height),":[125],"(2)":[126],"further":[127],"filter":[128],"map":[132],"into":[133],"minimal":[136],"fuse":[140],"data,":[144],"(3)":[146],"make":[147],"DRL":[150,175],"module":[151],"partially":[158,168],"observable":[159],"sequential":[160],"decision":[161],"making":[162],"problem":[163],"deal":[166],"accurate":[169],"data.":[170],"We":[171],"present":[172],"novel":[174],"training":[176],"scheme":[177],"navigation,":[180],"proposing":[181],"concise":[183],"proving":[189],"applying":[191],"replace":[195],"multi-stage":[196],"training,":[197],"achieve":[198],"better":[199],"results":[200],"generalization":[202],"capability.":[203],"Experiments":[204],"on":[205],"both":[206],"simulated":[207],"real":[211],"show":[213],"perform":[218],"efficient":[219],"collision":[220],"avoidance":[221],"using":[223],"camera.":[230]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}