{"id":"https://openalex.org/W4317383037","doi":"https://doi.org/10.1109/robio55434.2022.10011819","title":"Learning Robust Vehicle Navigation Policy Under Interference and Partial Sensor Failures","display_name":"Learning Robust Vehicle Navigation Policy Under Interference and Partial Sensor Failures","publication_year":2022,"publication_date":"2022-12-05","ids":{"openalex":"https://openalex.org/W4317383037","doi":"https://doi.org/10.1109/robio55434.2022.10011819"},"language":"en","primary_location":{"id":"doi:10.1109/robio55434.2022.10011819","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/robio55434.2022.10011819","pdf_url":null,"source":{"id":"https://openalex.org/S4363607789","display_name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","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 International Conference on Robotics and Biomimetics (ROBIO)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100462362","display_name":"Zhe Liu","orcid":"https://orcid.org/0000-0002-2513-2662"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Liu","raw_affiliation_strings":["AI Institute, Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence,China","MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Institute, Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030318122","display_name":"Kefan Jin","orcid":"https://orcid.org/0000-0001-7457-2392"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kefan Jin","raw_affiliation_strings":["AI Institute, Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence,China","MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Institute, Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103022180","display_name":"Yu Zhai","orcid":"https://orcid.org/0009-0005-6660-1268"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zhai","raw_affiliation_strings":["China University of Mining and Technology,School of Information and Control Engineering,China","School of Information and Control Engineering, China University of Mining and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Mining and Technology,School of Information and Control Engineering,China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"School of Information and Control Engineering, China University of Mining and Technology, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021924831","display_name":"Yanzi Miao","orcid":"https://orcid.org/0000-0002-2688-7477"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanzi Miao","raw_affiliation_strings":["China University of Mining and Technology,School of Information and Control Engineering,China","School of Information and Control Engineering, China University of Mining and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Mining and Technology,School of Information and Control Engineering,China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"School of Information and Control Engineering, China University of Mining and Technology, China","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2774,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.63609188,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"33","issue":null,"first_page":"15","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7583657503128052},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7465634346008301},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5727986097335815},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.5547967553138733},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.47339928150177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4611419141292572},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.44490674138069153},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.43707695603370667},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3875081241130829}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7583657503128052},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7465634346008301},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5727986097335815},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5547967553138733},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.47339928150177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4611419141292572},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.44490674138069153},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.43707695603370667},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3875081241130829},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/robio55434.2022.10011819","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/robio55434.2022.10011819","pdf_url":null,"source":{"id":"https://openalex.org/S4363607789","display_name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","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 International Conference on Robotics and Biomimetics (ROBIO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1959608418","https://openalex.org/W2741019409","https://openalex.org/W2886061540","https://openalex.org/W2905173465","https://openalex.org/W2937814560","https://openalex.org/W2948153973","https://openalex.org/W2959364614","https://openalex.org/W2962894046","https://openalex.org/W2967975754","https://openalex.org/W2968008415","https://openalex.org/W2969277962","https://openalex.org/W2986519585","https://openalex.org/W3015217705","https://openalex.org/W3018823604","https://openalex.org/W3035237749","https://openalex.org/W3081203761","https://openalex.org/W3098881644","https://openalex.org/W3101856276","https://openalex.org/W3129935960","https://openalex.org/W3131623996","https://openalex.org/W3132321768","https://openalex.org/W3133466685","https://openalex.org/W3174686248","https://openalex.org/W3185523273","https://openalex.org/W3205373118","https://openalex.org/W3209445167","https://openalex.org/W4200451128","https://openalex.org/W4206138072","https://openalex.org/W4292347911","https://openalex.org/W6738700159","https://openalex.org/W6761988744","https://openalex.org/W6780093097"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W2381850946","https://openalex.org/W4380449851","https://openalex.org/W3150465815","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W1997222214","https://openalex.org/W2560439919","https://openalex.org/W3125091513"],"abstract_inverted_index":{"Autonomous":[0],"driving":[1,17,50],"has":[2],"been":[3],"a":[4,57],"research":[5],"hotspot":[6],"for":[7,90],"several":[8],"years.":[9],"However,":[10],"most":[11],"researchers":[12],"focus":[13],"on":[14,96,114],"the":[15,20,30,36,76,97,102,116,122],"ideal":[16],"condition,":[18],"where":[19],"sensor":[21,37,71],"data":[22,38,120],"is":[23,33],"always":[24],"accurate":[25],"and":[26,35,69,82,121],"clean.":[27],"In":[28,52],"reality,":[29],"urban":[31],"environment":[32],"complex":[34],"can":[39,44],"easily":[40],"be":[41],"disturbed,":[42],"which":[43,73],"lead":[45],"to":[46,63,87],"failures":[47],"of":[48,78,104],"existing":[49],"approaches.":[51],"this":[53],"paper,":[54],"we":[55],"present":[56],"multi-sensor":[58],"fusion":[59],"based":[60],"navigation":[61,66,92],"framework":[62],"achieve":[64],"robust":[65,91],"under":[67],"interference":[68],"partial":[70],"failures,":[72],"implicitly":[74],"learns":[75],"reliability":[77],"each":[79],"input":[80,117],"information":[81],"introduces":[83],"graph":[84],"neural":[85],"networks":[86],"reconstruct":[88],"features":[89],"policy":[93],"learning.":[94],"Experiments":[95],"high-fidelity":[98],"CARLA":[99],"platform":[100],"demonstrate":[101],"effectiveness":[103],"our":[105,108],"approach,":[106],"especially":[107],"strong":[109],"robustness":[110],"against":[111],"various":[112],"disturbances":[113],"both":[115],"point":[118],"cloud":[119],"visual":[123],"images.":[124]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}