{"id":"https://openalex.org/W7161985426","doi":"https://doi.org/10.48550/arxiv.2605.20801","title":"Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation","display_name":"Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7161985426","doi":"https://doi.org/10.48550/arxiv.2605.20801"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.20801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20801","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.20801","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136689701","display_name":"Mohamed Khair Altrabulsi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Altrabulsi, Mohamed Khair","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136643667","display_name":"Nouhaila Innan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Innan, Nouhaila","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042642081","display_name":"Alberto Marchisio","orcid":"https://orcid.org/0000-0002-0689-4776"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marchisio, Alberto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136723575","display_name":"Muhammad Kashif","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kashif, Muhammad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136724729","display_name":"Muhammad Shafique","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shafique, Muhammad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.6579999923706055,"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.6579999923706055,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.056699998676776886,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.05510000139474869,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7045999765396118},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.6419000029563904},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6229000091552734},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5763000249862671},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4986000061035156},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45100000500679016},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4235999882221222},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3955000042915344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7128999829292297},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7045999765396118},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.6419000029563904},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6229000091552734},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5763000249862671},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5268999934196472},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4986000061035156},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45100000500679016},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4235999882221222},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3955000042915344},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.37959998846054077},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.3785000145435333},{"id":"https://openalex.org/C70388272","wikidata":"https://www.wikidata.org/wiki/Q5968558","display_name":"IBM","level":2,"score":0.3528999984264374},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.33230000734329224},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.32269999384880066},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.3127000033855438},{"id":"https://openalex.org/C196340769","wikidata":"https://www.wikidata.org/wiki/Q7698910","display_name":"Temporal difference learning","level":3,"score":0.3082999885082245},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2953999936580658},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2786000072956085},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C65401140","wikidata":"https://www.wikidata.org/wiki/Q7353385","display_name":"Robot control","level":4,"score":0.2646999955177307},{"id":"https://openalex.org/C188888258","wikidata":"https://www.wikidata.org/wiki/Q7353390","display_name":"Robot learning","level":4,"score":0.26339998841285706},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.20801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20801","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.20801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20801","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Adaptive":[0],"robot":[1,32],"navigation":[2],"in":[3,154],"dynamic":[4,107],"environments":[5,94],"requires":[6],"policies":[7],"that":[8,128],"can":[9],"reach":[10],"the":[11,69,72,131,155,166,170],"target":[12],"reliably":[13],"while":[14,149],"producing":[15],"efficient":[16],"and":[17,37,51,66,101,106,120,140],"stable":[18],"trajectories.":[19],"This":[20],"paper":[21],"presents":[22],"Q-SpiRL,":[23],"a":[24,63],"quantum":[25,85,162],"spiking":[26,53],"reinforcement":[27],"learning":[28],"framework":[29,35],"for":[30],"obstacle-aware":[31],"navigation.":[33],"The":[34],"develops":[36],"evaluates":[38],"five":[39],"agent":[40],"families:":[41],"tabular":[42],"Q-learning,":[43],"classical":[44,46],"MLP,":[45],"SNN,":[47],"quantum-enhanced":[48,52],"MLP":[49],"(QMLP),":[50],"neural":[54],"network":[55],"(QSNN).":[56],"While":[57],"all":[58],"models":[59],"are":[60,89],"implemented":[61],"under":[62,123,174],"unified":[64],"training":[65],"evaluation":[67],"pipeline,":[68],"QSNN":[70,129],"is":[71,110],"central":[73],"architecture":[74],"of":[75,95,168],"interest,":[76],"as":[77],"it":[78],"combines":[79],"spike-based":[80],"temporal":[81],"processing":[82],"with":[83,103],"variational":[84],"feature":[86],"transformation.":[87],"Experiments":[88],"conducted":[90],"across":[91],"three":[92],"grid-world":[93],"increasing":[96],"size,":[97],"namely":[98],"20x20,":[99],"30x30,":[100],"40x40,":[102],"both":[104],"static":[105],"obstacles.":[108],"Performance":[109],"assessed":[111],"using":[112],"success":[113,147],"rate,":[114],"success-weighted":[115],"path":[116,118,152],"length,":[117,119],"turn":[121],"rate":[122,148],"deterministic":[124],"inference.":[125],"Results":[126],"show":[127],"achieves":[130],"strongest":[132],"overall":[133],"trade-off":[134],"between":[135],"task":[136],"completion,":[137],"trajectory":[138],"efficiency,":[139],"motion":[141],"smoothness,":[142],"reaching":[143],"up":[144],"to":[145],"99%":[146],"maintaining":[150],"high":[151],"efficiency":[153],"most":[156],"challenging":[157],"setting.":[158],"Execution":[159],"on":[160],"IBM":[161],"hardware":[163],"further":[164],"demonstrates":[165],"feasibility":[167],"deploying":[169],"proposed":[171],"hybrid":[172],"policy":[173],"real-device":[175],"conditions.":[176]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-22T00:00:00"}
