{"id":"https://openalex.org/W2772821934","doi":"https://doi.org/10.1109/iros.2017.8202271","title":"Joint perception and planning for efficient obstacle avoidance using stereo vision","display_name":"Joint perception and planning for efficient obstacle avoidance using stereo vision","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2772821934","doi":"https://doi.org/10.1109/iros.2017.8202271","mag":"2772821934"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2017.8202271","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2017.8202271","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5023899233","display_name":"Sourish Ghosh","orcid":"https://orcid.org/0000-0001-8438-9487"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sourish Ghosh","raw_affiliation_strings":["Department of Mathematics, Indian Institute of Technology, Kharagpur, West Bengal, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Indian Institute of Technology, Kharagpur, West Bengal, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004302220","display_name":"Joydeep Biswas","orcid":"https://orcid.org/0000-0002-1211-1731"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joydeep Biswas","raw_affiliation_strings":["College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2008,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.87665123,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","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/T10586","display_name":"Robotic Path Planning Algorithms","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9994000196456909,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9968000054359436,"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/computer-vision","display_name":"Computer vision","score":0.7771587371826172},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.7407498359680176},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.711786150932312},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7083967924118042},{"id":"https://openalex.org/keywords/stereopsis","display_name":"Stereopsis","score":0.6948509216308594},{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.6899306774139404},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.6833515763282776},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5316380262374878},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5302006006240845},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.4970112144947052},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4467577636241913},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.43468931317329407},{"id":"https://openalex.org/keywords/planner","display_name":"Planner","score":0.4330521523952484},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.14683806896209717},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08232012391090393},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.07572564482688904}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7771587371826172},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.7407498359680176},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.711786150932312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7083967924118042},{"id":"https://openalex.org/C68537008","wikidata":"https://www.wikidata.org/wiki/Q247932","display_name":"Stereopsis","level":2,"score":0.6948509216308594},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.6899306774139404},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.6833515763282776},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5316380262374878},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5302006006240845},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.4970112144947052},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4467577636241913},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.43468931317329407},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.4330521523952484},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14683806896209717},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08232012391090393},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.07572564482688904},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros.2017.8202271","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2017.8202271","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-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":16,"referenced_works":["https://openalex.org/W10244975","https://openalex.org/W1492287580","https://openalex.org/W1676459225","https://openalex.org/W1984475609","https://openalex.org/W2104853049","https://openalex.org/W2107684513","https://openalex.org/W2110946546","https://openalex.org/W2111482306","https://openalex.org/W2112278911","https://openalex.org/W2131071980","https://openalex.org/W2132400125","https://openalex.org/W2137448073","https://openalex.org/W2164638305","https://openalex.org/W2171331791","https://openalex.org/W2571302414","https://openalex.org/W6676797363"],"related_works":["https://openalex.org/W2930076404","https://openalex.org/W4253519380","https://openalex.org/W2071957557","https://openalex.org/W2596413128","https://openalex.org/W2356867392","https://openalex.org/W2782776446","https://openalex.org/W3043170174","https://openalex.org/W2155948905","https://openalex.org/W4380590094","https://openalex.org/W2050548713"],"abstract_inverted_index":{"Stereo":[0],"vision":[1],"is":[2,29,155],"commonly":[3],"used":[4,31],"for":[5,32,105],"local":[6],"obstacle":[7,103,120],"avoidance":[8],"of":[9,24,62,128,148,164,201],"autonomous":[10],"mobile":[11],"robots:":[12],"stereo":[13,85,131,136],"images":[14],"are":[15,139],"first":[16],"processed":[17],"to":[18,57,65,78,142],"yield":[19],"a":[20,59,99,126],"dense":[21],"3D":[22,112],"reconstruction":[23],"the":[25,52,63,67,145,170,195,202],"observed":[26],"scene,":[27],"which":[28,38,87,138],"then":[30],"navigation":[33,53,106],"planning.":[34,165],"Such":[35],"an":[36,76],"approach,":[37],"we":[39,74,114],"term":[40],"Sequential":[41],"Perception":[42,80],"and":[43,81,133,178,190],"Planning":[44,82],"(SPP),":[45],"results":[46,185],"in":[47,116],"significant":[48],"unnecessary":[49],"computations":[50,204],"as":[51,94],"planner":[54],"only":[55,93],"needs":[56],"explore":[58],"small":[60],"part":[61],"scene":[64],"compute":[66,143],"shortest":[68],"obstacle-free":[69],"path.":[70],"In":[71],"this":[72,117],"paper,":[73],"introduce":[75],"approach":[77],"Joint":[79],"(JPP)":[83],"using":[84],"vision,":[86],"performs":[88],"disparity":[89,203],"checks":[90,104],"on":[91,98],"demand,":[92],"necessary":[95],"while":[96,160],"searching":[97],"planning":[100,107],"graph.":[101],"Furthermore,":[102],"do":[108],"not":[109],"require":[110],"full":[111],"reconstruction:":[113],"present":[115,182],"paper":[118],"how":[119,169],"queries":[121],"can":[122],"be":[123],"decomposed":[124],"into":[125],"sequence":[127],"confident":[129,134],"positive":[130],"matches":[132],"negative":[135],"matches,":[137],"significantly":[140,156],"faster":[141,157],"than":[144,158,199],"exact":[146],"depth":[147],"points.":[149],"The":[150],"resulting":[151],"complete":[152],"JPP":[153,171,196],"formulation":[154],"SPP,":[159],"still":[161],"maintaining":[162],"correctness":[163],"We":[166,181],"also":[167],"show":[168],"works":[172],"with":[173],"different":[174],"planners,":[175],"including":[176],"search-based":[177],"sampling-based":[179],"planners.":[180],"extensive":[183],"experimental":[184],"from":[186],"real":[187],"robot":[188],"data":[189],"simulation":[191],"experiments,":[192],"demonstrating":[193],"that":[194],"requires":[197],"less":[198],"10%":[200],"required":[205],"by":[206],"SPP.":[207]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
