{"id":"https://openalex.org/W2939124210","doi":"https://doi.org/10.1080/01691864.2019.1602564","title":"Saliency and spatial information-based landmark selection for mobile robot navigation in natural environments","display_name":"Saliency and spatial information-based landmark selection for mobile robot navigation in natural environments","publication_year":2019,"publication_date":"2019-04-11","ids":{"openalex":"https://openalex.org/W2939124210","doi":"https://doi.org/10.1080/01691864.2019.1602564","mag":"2939124210"},"language":"en","primary_location":{"id":"doi:10.1080/01691864.2019.1602564","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01691864.2019.1602564","pdf_url":null,"source":{"id":"https://openalex.org/S192584203","display_name":"Advanced Robotics","issn_l":"0169-1864","issn":["0169-1864","1568-5535"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advanced Robotics","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/A5051414896","display_name":"G\u00e1bor Kov\u00e1cs","orcid":"https://orcid.org/0000-0001-6913-4048"},"institutions":[{"id":"https://openalex.org/I96679780","display_name":"Chuo University","ror":"https://ror.org/03qvqb743","country_code":"JP","type":"education","lineage":["https://openalex.org/I96679780"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"G\u00e1bor Kov\u00e1cs","raw_affiliation_strings":["Faculty of Science and Engineering, Chuo University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Science and Engineering, Chuo University, Tokyo, Japan","institution_ids":["https://openalex.org/I96679780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112662257","display_name":"Yasuharu Kunii","orcid":null},"institutions":[{"id":"https://openalex.org/I96679780","display_name":"Chuo University","ror":"https://ror.org/03qvqb743","country_code":"JP","type":"education","lineage":["https://openalex.org/I96679780"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasuharu Kunii","raw_affiliation_strings":["Faculty of Science and Engineering, Chuo University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Science and Engineering, Chuo University, Tokyo, Japan","institution_ids":["https://openalex.org/I96679780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034741835","display_name":"Takao Maeda","orcid":"https://orcid.org/0000-0001-8321-7237"},"institutions":[{"id":"https://openalex.org/I96679780","display_name":"Chuo University","ror":"https://ror.org/03qvqb743","country_code":"JP","type":"education","lineage":["https://openalex.org/I96679780"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takao Maeda","raw_affiliation_strings":["Faculty of Science and Engineering, Chuo University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Science and Engineering, Chuo University, Tokyo, Japan","institution_ids":["https://openalex.org/I96679780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038664472","display_name":"Hideki Hashimoto","orcid":"https://orcid.org/0000-0003-3663-6564"},"institutions":[{"id":"https://openalex.org/I96679780","display_name":"Chuo University","ror":"https://ror.org/03qvqb743","country_code":"JP","type":"education","lineage":["https://openalex.org/I96679780"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hideki Hashimoto","raw_affiliation_strings":["Faculty of Science and Engineering, Chuo University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Science and Engineering, Chuo University, Tokyo, Japan","institution_ids":["https://openalex.org/I96679780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5051414896"],"corresponding_institution_ids":["https://openalex.org/I96679780"],"apc_list":null,"apc_paid":null,"fwci":0.911,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.7858763,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":"33","issue":"10","first_page":"520","last_page":"535"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9994000196456909,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9994000196456909,"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":0.9991999864578247,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991000294685364,"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/landmark","display_name":"Landmark","score":0.9380072951316833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7808982133865356},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.775209367275238},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7399707436561584},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6886970400810242},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.523071825504303},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.4932844042778015},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.48795217275619507},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.4372006356716156},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4282046854496002},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4237355887889862},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.3266262412071228},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13029751181602478}],"concepts":[{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.9380072951316833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7808982133865356},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.775209367275238},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7399707436561584},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6886970400810242},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.523071825504303},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.4932844042778015},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.48795217275619507},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.4372006356716156},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4282046854496002},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4237355887889862},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3266262412071228},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13029751181602478},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/01691864.2019.1602564","is_oa":false,"landing_page_url":"https://doi.org/10.1080/01691864.2019.1602564","pdf_url":null,"source":{"id":"https://openalex.org/S192584203","display_name":"Advanced Robotics","issn_l":"0169-1864","issn":["0169-1864","1568-5535"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advanced Robotics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309889","display_name":"Chuo University","ror":"https://ror.org/03qvqb743"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1963841606","https://openalex.org/W2111073598","https://openalex.org/W2128272608","https://openalex.org/W2143715815","https://openalex.org/W2151103935","https://openalex.org/W4247299037"],"related_works":["https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2005087563","https://openalex.org/W2378111931","https://openalex.org/W4243161226","https://openalex.org/W2950647290","https://openalex.org/W2620829895","https://openalex.org/W2356918560","https://openalex.org/W1993438337","https://openalex.org/W1977899511"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,52,62,81,91],"landmark":[4,45,104,131],"selection":[5,46],"and":[6,23,152],"tracking":[7,39],"approach":[8],"is":[9,48,95,118,150],"presented":[10,31],"for":[11,105,154],"mobile":[12],"robot":[13],"navigation":[14],"in":[15,61,108],"natural":[16,155],"environments,":[17],"using":[18],"textural":[19,82],"distinctiveness-based":[20,83],"saliency":[21,84],"detection":[22],"spatial":[24,88],"information":[25],"acquired":[26],"from":[27,80,140],"stereo":[28],"data.":[29],"The":[30,44,113],"method":[32,47,149],"focuses":[33],"on":[34],"achieving":[35],"high":[36],"robustness":[37,126],"of":[38,55,65,100,116],"rather":[40],"than":[41],"self-positioning":[42],"accuracy.":[43],"designed":[49],"to":[50,69,110],"select":[51],"small":[53],"amount":[54],"the":[56,98,147],"most":[57],"salient":[58],"feature":[59],"points":[60],"wide":[63],"variety":[64],"sparse":[66],"unknown":[67],"environments":[68],"ensure":[70],"successful":[71],"matching.":[72],"Landmarks":[73],"are":[74],"selected":[75,103],"by":[76,133],"an":[77],"iterative":[78],"algorithm":[79],"map":[85],"extended":[86],"with":[87,120],"information,":[89],"where":[90],"repulsive":[92],"potential":[93],"field":[94],"created":[96],"around":[97],"position":[99],"each":[101],"already":[102],"better":[106],"distribution":[107],"order":[109],"increase":[111],"robustness.":[112],"template":[114],"matching":[115],"landmarks":[117],"aided":[119],"visual":[121],"odometry-based":[122],"motion":[123],"estimation.":[124],"Other":[125],"increasing":[127],"strategies":[128],"includes":[129],"estimating":[130],"positions":[132],"unscented":[134],"Kalman":[135],"filters":[136],"as":[137,139],"well":[138],"surrounding":[141],"landmarks.":[142],"Experimental":[143],"results":[144],"show":[145],"that":[146],"introduced":[148],"robust":[151],"suitable":[153],"environments.":[156]},"counts_by_year":[{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}