{"id":"https://openalex.org/W2218183533","doi":"https://doi.org/10.1109/iros.2015.7354030","title":"Learning optimal striking points for a ping-pong playing robot","display_name":"Learning optimal striking points for a ping-pong playing robot","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2218183533","doi":"https://doi.org/10.1109/iros.2015.7354030","mag":"2218183533"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2015.7354030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2015.7354030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 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/A5012387768","display_name":"Yanlong Huang","orcid":"https://orcid.org/0000-0002-5395-5076"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Yanlong Huang","raw_affiliation_strings":["Bernhard Scholkopf, and Jan Peters are with the Max-Planck Institute for Intelligent Systems, Tiibingen, Germany"],"affiliations":[{"raw_affiliation_string":"Bernhard Scholkopf, and Jan Peters are with the Max-Planck Institute for Intelligent Systems, Tiibingen, Germany","institution_ids":["https://openalex.org/I4210135521"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044005697","display_name":"Bernhard Sch\u00f6lkopf","orcid":"https://orcid.org/0000-0002-8177-0925"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernhard Scholkopf","raw_affiliation_strings":["Bernhard Scholkopf, and Jan Peters are with the Max-Planck Institute for Intelligent Systems, Tiibingen, Germany"],"affiliations":[{"raw_affiliation_string":"Bernhard Scholkopf, and Jan Peters are with the Max-Planck Institute for Intelligent Systems, Tiibingen, Germany","institution_ids":["https://openalex.org/I4210135521"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071367253","display_name":"Jan Peters","orcid":"https://orcid.org/0000-0002-5266-8091"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]},{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jan Peters","raw_affiliation_strings":["Bernhard Scholkopf, and Jan Peters are with the Max-Planck Institute for Intelligent Systems, Tiibingen, Germany","Technische Universitat Darmstadt, Darmstadt, Germany"],"affiliations":[{"raw_affiliation_string":"Bernhard Scholkopf, and Jan Peters are with the Max-Planck Institute for Intelligent Systems, Tiibingen, Germany","institution_ids":["https://openalex.org/I4210135521"]},{"raw_affiliation_string":"Technische Universitat Darmstadt, Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012387768"],"corresponding_institution_ids":["https://openalex.org/I4210135521"],"apc_list":null,"apc_paid":null,"fwci":2.7243,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.91050555,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4587","last_page":"4592"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9937999844551086,"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":0.9930999875068665,"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/ball","display_name":"Ball (mathematics)","score":0.716823160648346},{"id":"https://openalex.org/keywords/racket","display_name":"Racket","score":0.6852831840515137},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6096614599227905},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5950828790664673},{"id":"https://openalex.org/keywords/workspace","display_name":"Workspace","score":0.580707848072052},{"id":"https://openalex.org/keywords/ping-pong","display_name":"Ping pong","score":0.5591668486595154},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4576515257358551},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.450374960899353},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4263906478881836},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3344919979572296},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28971874713897705},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1396518051624298},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.11152568459510803},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.11129629611968994}],"concepts":[{"id":"https://openalex.org/C122041747","wikidata":"https://www.wikidata.org/wiki/Q838611","display_name":"Ball (mathematics)","level":2,"score":0.716823160648346},{"id":"https://openalex.org/C2778707667","wikidata":"https://www.wikidata.org/wiki/Q1254148","display_name":"Racket","level":3,"score":0.6852831840515137},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6096614599227905},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5950828790664673},{"id":"https://openalex.org/C58581272","wikidata":"https://www.wikidata.org/wiki/Q12741163","display_name":"Workspace","level":3,"score":0.580707848072052},{"id":"https://openalex.org/C2985464141","wikidata":"https://www.wikidata.org/wiki/Q3930","display_name":"Ping pong","level":3,"score":0.5591668486595154},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4576515257358551},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.450374960899353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4263906478881836},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3344919979572296},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28971874713897705},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1396518051624298},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.11152568459510803},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.11129629611968994},{"id":"https://openalex.org/C65655974","wikidata":"https://www.wikidata.org/wiki/Q14867674","display_name":"Swing","level":2,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C185078393","wikidata":"https://www.wikidata.org/wiki/Q313783","display_name":"Stereo camera","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iros.2015.7354030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2015.7354030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.mpg.de:item_2260976","is_oa":false,"landing_page_url":"http://hdl.handle.net/11858/00-001M-0000-002A-20A3-2","pdf_url":null,"source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015)","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1492728092","https://openalex.org/W1535581754","https://openalex.org/W1746819321","https://openalex.org/W1949974402","https://openalex.org/W1968591741","https://openalex.org/W1982803779","https://openalex.org/W1987616874","https://openalex.org/W2012204020","https://openalex.org/W2023801472","https://openalex.org/W2064276653","https://openalex.org/W2086648974","https://openalex.org/W2086890595","https://openalex.org/W2102341081","https://openalex.org/W2111978237","https://openalex.org/W2112089018","https://openalex.org/W2112090547","https://openalex.org/W2112963000","https://openalex.org/W2131531493","https://openalex.org/W2136719407","https://openalex.org/W2142300342","https://openalex.org/W2144576818","https://openalex.org/W2144636911","https://openalex.org/W2158449558","https://openalex.org/W2369633868","https://openalex.org/W2516390886","https://openalex.org/W2591436094","https://openalex.org/W4211049957","https://openalex.org/W6629475238","https://openalex.org/W6629804754","https://openalex.org/W6987068114"],"related_works":["https://openalex.org/W1970971750","https://openalex.org/W2971683044","https://openalex.org/W2349284809","https://openalex.org/W2500432627","https://openalex.org/W584172674","https://openalex.org/W2295737993","https://openalex.org/W1595846144","https://openalex.org/W2096808190","https://openalex.org/W1599896731","https://openalex.org/W281011826"],"abstract_inverted_index":{"In":[0,131],"this":[1,132],"paper,":[2],"an":[3],"approach":[4],"for":[5,81],"learning":[6,164],"optimal":[7,110,180],"striking":[8,25,37,88,111,147,160],"points":[9,26,38,89,112],"is":[10,79,96],"proposed.":[11],"Based":[12],"on":[13,114],"a":[14,18,21,82,92,115,138,155,185],"ball-flight":[15],"model":[16],"and":[17,72,126,173],"rebound":[19],"model,":[20],"set":[22],"of":[23,99,154,158,170,192],"reachable":[24],"within":[27],"the":[28,49,53,56,58,67,97,122,127,142,145,168,190,193],"robot's":[29,50],"workspace":[30],"can":[31],"be":[32,104],"obtained.":[33],"However,":[34],"while":[35],"these":[36],"are":[39],"geometrically":[40],"reachable,":[41],"their":[42],"success":[43],"probability":[44],"differs":[45],"substantially":[46],"due":[47],"to":[48,55,60,75,86,136,151,178],"nonlinear":[51],"dynamics,":[52],"distance":[54],"ball,":[57],"need":[59],"reach":[61,179],"sufficient":[62],"velocity":[63],"as":[64,66],"well":[65,121],"right":[68],"angle":[69],"at":[70],"interception":[71,95],"non-uniform":[73],"sensitivity":[74],"errors.":[76],"Thus,":[77],"it":[78],"crucial":[80],"ping-pong":[83,123],"robotic":[84,187],"system":[85,188],"select":[87],"well.":[90],"As":[91],"successful":[93],"ball":[94],"result":[98],"various":[100],"factors":[101],"that":[102,118],"cannot":[103],"modeled":[105],"straightforwardly,":[106],"we":[107,134],"suggest":[108],"determining":[109],"based":[113],"reward":[116,143],"function":[117],"measures":[119],"how":[120],"ball's":[124],"trajectory":[125],"racket's":[128],"movement":[129],"coincidence.":[130],"approach,":[133],"propose":[135],"learn":[137],"stochastic":[139],"policy":[140],"over":[141],"given":[144],"prospective":[146,159],"point":[148],"in":[149],"order":[150],"facilitate":[152],"exploration":[153],"wide":[156],"range":[157],"points.":[161],"The":[162],"resulting":[163],"method":[165],"takes":[166],"both":[167],"amount":[169],"experience":[171],"data":[172],"its":[174],"confidence":[175],"into":[176],"account":[177],"solutions":[181],"reliably.":[182],"Evaluation":[183],"with":[184],"real":[186],"demonstrates":[189],"applicability":[191],"proposed":[194],"method.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}