{"id":"https://openalex.org/W7087016554","doi":"https://doi.org/10.5281/zenodo.17307379","title":"Enhanced Adaptive Slope Navigation for Silver Cars via Hierarchical Reinforcement Learning and Multi-Modal Sensor Fusion","display_name":"Enhanced Adaptive Slope Navigation for Silver Cars via Hierarchical Reinforcement Learning and Multi-Modal Sensor Fusion","publication_year":2025,"publication_date":"2025-10-09","ids":{"openalex":"https://openalex.org/W7087016554","doi":"https://doi.org/10.5281/zenodo.17307379"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.17307379","doi":"https://doi.org/10.5281/zenodo.17307379","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17307379","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"JournalArticle"},"volume":null,"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.17307379","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Freederia AI Researcher","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Freederia AI Researcher","raw_affiliation_strings":["Freederia Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Freederia Research","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38604329,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.5019999742507935,"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":0.5019999742507935,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.22269999980926514,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T11615","display_name":"Control and Dynamics of Mobile Robots","score":0.14390000700950623,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hierarchical-reinforcement-learning","display_name":"hierarchical reinforcement learning","score":0.9509999752044678},{"id":"https://openalex.org/keywords/multimodal-sensor-fusion","display_name":"multimodal sensor fusion","score":0.9860000014305115},{"id":"https://openalex.org/keywords/lidar","display_name":"LiDAR","score":0.9890000224113464},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"inertial measurement unit","score":0.9290000200271606},{"id":"https://openalex.org/keywords/visual-odometry","display_name":"visual odometry","score":1.0},{"id":"https://openalex.org/keywords/terrain-aided-navigation","display_name":"terrain navigation","score":0.3179999887943268},{"id":"https://openalex.org/keywords/energy-consumption-reduction","display_name":"energy consumption reduction","score":0.8930000066757202},{"id":"https://openalex.org/keywords/elderly-and-disabled-mobility","display_name":"elderly and disabled mobility","score":0.8119999766349792}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6872000098228455},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5467000007629395},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.49880000948905945},{"id":"https://openalex.org/C158105764","wikidata":"https://www.wikidata.org/wiki/Q827664","display_name":"Inclinometer","level":2,"score":0.4952999949455261},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.45179998874664307},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4219000041484833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4198000133037567},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.40950000286102295},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4083000123500824},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.40779998898506165},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.38690000772476196},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3646000027656555},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34929999709129333},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.34310001134872437},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C2777891301","wikidata":"https://www.wikidata.org/wiki/Q3475123","display_name":"Navigation system","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.31150001287460327},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.303600013256073},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C201004817","wikidata":"https://www.wikidata.org/wiki/Q1707071","display_name":"Guidance system","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.260699987411499},{"id":"https://openalex.org/C520301825","wikidata":"https://www.wikidata.org/wiki/Q380170","display_name":"Energy conservation","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C2988147884","wikidata":"https://www.wikidata.org/wiki/Q5377024","display_name":"Energy expenditure","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.25130000710487366}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5281/zenodo.17307379","doi":"https://doi.org/10.5281/zenodo.17307379","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17307379","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"JournalArticle"},{"id":"doi:10.5281/zenodo.17307380","doi":"https://doi.org/10.5281/zenodo.17307380","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17307380","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"JournalArticle"}],"best_oa_location":{"id":"doi:10.5281/zenodo.17307379","doi":"https://doi.org/10.5281/zenodo.17307379","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17307379","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"JournalArticle"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.7207000255584717,"display_name":"Industry, innovation and infrastructure"}],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/7","score":0.9007232785224915,"display_name":"Affordable and clean energy"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"**Abstract:**":[0],"This":[1],"paper":[2],"introduces":[3],"a":[4,77,85],"novel":[5],"system":[6,75],"for":[7,104],"enhanced":[8,101],"adaptive":[9],"slope":[10],"navigation":[11,82],"in":[12,81,88],"silver":[13],"cars":[14],"(mobility":[15],"assistance":[16],"vehicles),":[17],"addressing":[18],"the":[19],"persistent":[20],"challenge":[21],"of":[22],"safe":[23],"and":[24,37,55,65,84,100],"efficient":[25],"operation":[26],"on":[27,35],"varied":[28],"terrain.":[29],"Unlike":[30],"existing":[31],"solutions":[32],"relying":[33],"solely":[34],"inclinometers":[36],"rudimentary":[38],"motor":[39],"control,":[40],"our":[41],"approach":[42],"leverages":[43],"Hierarchical":[44],"Reinforcement":[45],"Learning":[46],"(HRL)":[47],"coupled":[48],"with":[49],"multi-modal":[50],"sensor":[51],"fusion":[52],"(LiDAR,":[53],"IMU,":[54],"visual":[56],"odometry)":[57],"to":[58,93],"achieve":[59],"significantly":[60],"improved":[61],"stability,":[62],"smoother":[63],"transitions,":[64],"reduced":[66],"energy":[67,89],"consumption":[68],"across":[69],"diverse":[70],"sloped":[71],"environments.":[72],"The":[73],"proposed":[74],"offers":[76],"potential":[78],"20-30%":[79],"improvement":[80],"stability":[83],"15-25%":[86],"reduction":[87],"expenditure":[90],"when":[91],"compared":[92],"current":[94],"state-of-the-art":[95],"systems,":[96],"facilitating":[97],"wider":[98],"accessibility":[99],"user":[102],"independence":[103],"elderly":[105],"or":[106],"disabled":[107],"individuals.":[108]},"counts_by_year":[],"updated_date":"2026-10-07T09:51:55.459714","created_date":"2025-10-10T00:00:00"}