{"id":"https://openalex.org/W3016324113","doi":"https://doi.org/10.1109/icaiic48513.2020.9065237","title":"PPMC Training Algorithm: A Deep Learning Based Path Planner and Motion Controller","display_name":"PPMC Training Algorithm: A Deep Learning Based Path Planner and Motion Controller","publication_year":2020,"publication_date":"2020-02-01","ids":{"openalex":"https://openalex.org/W3016324113","doi":"https://doi.org/10.1109/icaiic48513.2020.9065237","mag":"3016324113"},"language":"en","primary_location":{"id":"doi:10.1109/icaiic48513.2020.9065237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic48513.2020.9065237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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/A5014418188","display_name":"Tamir Blum","orcid":"https://orcid.org/0000-0002-7012-6480"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Tamir Blum","raw_affiliation_strings":["Department of Aerospace Engineering, Tohoku University, Sendai, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059761082","display_name":"William Jones","orcid":"https://orcid.org/0000-0003-2999-9025"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"William Jones","raw_affiliation_strings":["Department of Aerospace Engineering, Tohoku University, Sendai, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023419492","display_name":"Kazuya Yoshida","orcid":"https://orcid.org/0000-0003-3889-5877"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuya Yoshida","raw_affiliation_strings":["Department of Aerospace Engineering, Tohoku University, Sendai, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, Tohoku University, Sendai, Japan","institution_ids":["https://openalex.org/I201537933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5014418188"],"corresponding_institution_ids":["https://openalex.org/I201537933"],"apc_list":null,"apc_paid":null,"fwci":0.7954,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77716128,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"1","issue":null,"first_page":"193","last_page":"198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9987999796867371,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9958999752998352,"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/motion-planning","display_name":"Motion planning","score":0.8126580715179443},{"id":"https://openalex.org/keywords/planner","display_name":"Planner","score":0.723401665687561},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7222380042076111},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6765239238739014},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.6657403707504272},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5995655059814453},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.5895742177963257},{"id":"https://openalex.org/keywords/motion-control","display_name":"Motion control","score":0.5101056694984436},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5048401951789856},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.48091456294059753},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4513767957687378},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.36139118671417236},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.32428619265556335},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10337361693382263},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.08707919716835022}],"concepts":[{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.8126580715179443},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.723401665687561},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7222380042076111},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6765239238739014},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.6657403707504272},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5995655059814453},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.5895742177963257},{"id":"https://openalex.org/C145565327","wikidata":"https://www.wikidata.org/wiki/Q852514","display_name":"Motion control","level":3,"score":0.5101056694984436},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5048401951789856},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.48091456294059753},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4513767957687378},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.36139118671417236},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.32428619265556335},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10337361693382263},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.08707919716835022},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic48513.2020.9065237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic48513.2020.9065237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W121023703","https://openalex.org/W2121863487","https://openalex.org/W2563670399","https://openalex.org/W2565555125","https://openalex.org/W2726187156","https://openalex.org/W2736601468","https://openalex.org/W2739330054","https://openalex.org/W2749928749","https://openalex.org/W2772545238","https://openalex.org/W2784449021","https://openalex.org/W2787938642","https://openalex.org/W2900879308","https://openalex.org/W2907537824","https://openalex.org/W2942608247","https://openalex.org/W2942742441","https://openalex.org/W2959100364","https://openalex.org/W2960249673","https://openalex.org/W2962917939","https://openalex.org/W2963184939","https://openalex.org/W2963428623","https://openalex.org/W2963794592","https://openalex.org/W2990747716","https://openalex.org/W3011344322","https://openalex.org/W3105609823","https://openalex.org/W4288363736","https://openalex.org/W4288638482"],"related_works":["https://openalex.org/W2155467318","https://openalex.org/W122632647","https://openalex.org/W2060743914","https://openalex.org/W2359600231","https://openalex.org/W187779371","https://openalex.org/W2380019117","https://openalex.org/W3138952546","https://openalex.org/W1660309994","https://openalex.org/W2369187583","https://openalex.org/W3197207153"],"abstract_inverted_index":{"In":[0,83],"the":[1,17,97,104,115,121,212],"pursuit":[2],"of":[3,52,57,91],"a":[4,50,62,68,112,143,148,167,175],"fully":[5],"autonomous":[6],"learning":[7,37],"agent":[8,71,213],"able":[9],"to":[10,66,72,74,78,80,106,123,125,154,164,187,214,216],"interact,":[11],"move,":[12],"and":[13,26,29,42,55,77,94,146,171,190,197,201,204,224],"be":[14,140],"useful":[15],"in":[16,128,183],"real":[18],"world,":[19],"two":[20,88],"fundamental":[21],"problems":[22],"are":[23],"path":[24,92,169,222],"planning":[25,93,223],"motion":[27,95,172,225],"control,":[28],"user-agent":[30],"interaction.":[31],"We":[32,158],"address":[33],"these":[34],"through":[35],"reinforcement":[36],"using":[38,202],"our":[39,209],"Path":[40],"Planning":[41],"Motion":[43],"Controller":[44],"(PPMC)":[45],"Training":[46],"Algorithm,":[47],"which":[48,179],"uses":[49],"combination":[51],"observable":[53],"goals":[54,58],"randomization":[56],"during":[59],"training,":[60],"with":[61],"customized":[63],"reward":[64],"function,":[65],"teach":[67],"simulated":[69],"quadruped":[70],"respond":[73,215],"user":[75,217],"commands":[76,218],"travel":[79,107,124],"designated":[81],"areas.":[82],"this":[84],"regard,":[85],"we":[86,206],"identified":[87],"critical":[89],"components":[90],"control:":[96],"first":[98],"is":[99,117,135,162],"region":[100],"enabled":[101],"travel,":[102,119],"or":[103,120],"ability":[105,122],"towards":[108],"any":[109],"location":[110],"within":[111],"prescribed":[113],"area;":[114],"second":[116],"multi-point":[118],"multiple":[126],"points":[127],"succession.":[129],"An":[130],"important":[131],"open":[132],"ended":[133],"question":[134],"how":[136],"many":[137],"tasks":[138],"should":[139],"handled":[141],"by":[142],"single":[144,149,176],"policy":[145,150],"if":[147],"can":[151],"even":[152],"learn":[153],"manage":[155],"several":[156],"tasks.":[157],"demonstrate":[159],"that":[160],"it":[161],"possible":[163],"contain":[165],"both":[166],"maples":[168],"planner":[170],"controller":[173],"on":[174],"neural":[177],"network,":[178],"could":[180],"prove":[181],"promising":[182],"future":[184],"work":[185],"due":[186],"their":[188],"interlinked":[189],"synergistic":[191],"nature.":[192],"Using":[193],"control":[194],"group":[195],"policies":[196],"various":[198],"test":[199],"cases":[200],"ACKTR":[203],"PPO,":[205],"empirically":[207],"validate":[208],"algorithm":[210],"teaches":[211],"as":[219,221],"well":[220],"control.":[226]},"counts_by_year":[{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}