{"id":"https://openalex.org/W4410068133","doi":"https://doi.org/10.1145/3715014.3722073","title":"RetroLiDAR: A Liquid-crystal Fiducial Marker System for High-fidelity Perception of Embodied AI","display_name":"RetroLiDAR: A Liquid-crystal Fiducial Marker System for High-fidelity Perception of Embodied AI","publication_year":2025,"publication_date":"2025-05-04","ids":{"openalex":"https://openalex.org/W4410068133","doi":"https://doi.org/10.1145/3715014.3722073"},"language":"en","primary_location":{"id":"doi:10.1145/3715014.3722073","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3715014.3722073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems","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/A5015625764","display_name":"Kenuo Xu","orcid":"https://orcid.org/0000-0003-3774-644X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kenuo Xu","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3774-644X","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017720328","display_name":"Bo Liang","orcid":"https://orcid.org/0000-0001-7226-8178"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Liang","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7226-8178","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736639","display_name":"Wei Li","orcid":"https://orcid.org/0000-0002-0370-5183"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Li","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0370-5183","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003999919","display_name":"Chenren Xu","orcid":"https://orcid.org/0000-0001-9171-2596"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenren Xu","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9171-2596","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015625764"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":2.0327,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.87637615,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"588","last_page":"589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9851999878883362,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9851999878883362,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9722999930381775,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9661999940872192,"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/fiducial-marker","display_name":"Fiducial marker","score":0.9130920767784119},{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.8308162689208984},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.6085041165351868},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.5995540618896484},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5210106372833252},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48303326964378357},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.46879610419273376},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4599657654762268},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.28370869159698486},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.214990496635437},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.0977887213230133},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.0929945707321167}],"concepts":[{"id":"https://openalex.org/C173974348","wikidata":"https://www.wikidata.org/wiki/Q1469893","display_name":"Fiducial marker","level":2,"score":0.9130920767784119},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.8308162689208984},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.6085041165351868},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.5995540618896484},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5210106372833252},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48303326964378357},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.46879610419273376},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4599657654762268},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.28370869159698486},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.214990496635437},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0977887213230133},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0929945707321167},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3715014.3722073","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3715014.3722073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3420942567","display_name":null,"funder_award_id":"62061146001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3949751732","display_name":null,"funder_award_id":"2023YFB2903902","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8888994136","display_name":null,"funder_award_id":"62272010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":82,"referenced_works":["https://openalex.org/W217217970","https://openalex.org/W1971560510","https://openalex.org/W1981725258","https://openalex.org/W1994349244","https://openalex.org/W2111830885","https://openalex.org/W2346667022","https://openalex.org/W2460321923","https://openalex.org/W2547263323","https://openalex.org/W2744435466","https://openalex.org/W2761146675","https://openalex.org/W2762660266","https://openalex.org/W2789847116","https://openalex.org/W2804339068","https://openalex.org/W2806539655","https://openalex.org/W2905090914","https://openalex.org/W2918870161","https://openalex.org/W2947375106","https://openalex.org/W2949105459","https://openalex.org/W2954023824","https://openalex.org/W3003508462","https://openalex.org/W3009445627","https://openalex.org/W3021125579","https://openalex.org/W3034602892","https://openalex.org/W3034681945","https://openalex.org/W3046550298","https://openalex.org/W3046911120","https://openalex.org/W3147079575","https://openalex.org/W3147449049","https://openalex.org/W3157643474","https://openalex.org/W3174688585","https://openalex.org/W3187041650","https://openalex.org/W3200540310","https://openalex.org/W3211863805","https://openalex.org/W3214557258","https://openalex.org/W4200257926","https://openalex.org/W4200629701","https://openalex.org/W4212928489","https://openalex.org/W4221145329","https://openalex.org/W4221152040","https://openalex.org/W4237512112","https://openalex.org/W4239470619","https://openalex.org/W4251571580","https://openalex.org/W4281257062","https://openalex.org/W4281773951","https://openalex.org/W4285142571","https://openalex.org/W4296736955","https://openalex.org/W4299363634","https://openalex.org/W4310203544","https://openalex.org/W4312307873","https://openalex.org/W4313915808","https://openalex.org/W4317926925","https://openalex.org/W4319068731","https://openalex.org/W4320519895","https://openalex.org/W4322717100","https://openalex.org/W4323349553","https://openalex.org/W4323650549","https://openalex.org/W4353072342","https://openalex.org/W4372271909","https://openalex.org/W4376955605","https://openalex.org/W4385526255","https://openalex.org/W4386071758","https://openalex.org/W4386269258","https://openalex.org/W4387010773","https://openalex.org/W4387212098","https://openalex.org/W4390489105","https://openalex.org/W4399121555","https://openalex.org/W4399121783","https://openalex.org/W4399324247","https://openalex.org/W4400276740","https://openalex.org/W4400276894","https://openalex.org/W4400681288","https://openalex.org/W4402715951","https://openalex.org/W4403483955","https://openalex.org/W4405014357","https://openalex.org/W6740987384","https://openalex.org/W6753962735","https://openalex.org/W6791581579","https://openalex.org/W6809825656","https://openalex.org/W6809943964","https://openalex.org/W6846367726","https://openalex.org/W6850959469","https://openalex.org/W6863365416"],"related_works":["https://openalex.org/W2005500833","https://openalex.org/W2333449417","https://openalex.org/W4313443006","https://openalex.org/W2945374968","https://openalex.org/W4293777179","https://openalex.org/W4385452045","https://openalex.org/W2164070813","https://openalex.org/W2135608140","https://openalex.org/W2895525995","https://openalex.org/W2332512904"],"abstract_inverted_index":{"As":[0],"embodied":[1,13],"AI":[2],"gradually":[3],"transitions":[4],"into":[5],"practical":[6],"applications,":[7],"enhancing":[8],"the":[9,16,79,82,88,110,119,132,135,139,150,155,174,191,215],"fidelity":[10],"of":[11,81,90,134],"how":[12],"agents":[14],"perceive":[15],"physical":[17],"world":[18],"has":[19],"become":[20],"a":[21,97,126,144,200,205],"critical":[22],"challenge.":[23],"Current":[24],"perception":[25],"methods":[26],"typically":[27],"rely":[28],"on":[29],"computer":[30],"vision-based":[31],"fiducial":[32,99,170],"marker":[33,100,111,202],"systems,":[34],"which":[35,85],"suffer":[36],"from":[37,162],"limitations":[38],"such":[39],"as":[40],"insufficient":[41],"reading":[42,175],"distance,":[43],"poor":[44],"localization":[45],"accuracy,":[46],"and":[47,72,124,183,209,218],"high":[48,70],"susceptibility":[49],"to":[50,66,95,117,130,148,168,180,187,213],"environmental":[51],"lighting":[52],"conditions.":[53],"Currently,":[54],"SPAD":[55],"sensor-based":[56],"LiDAR":[57,140],"technology":[58],"is":[59],"emerging":[60],"in":[61,92],"commercial":[62],"mobile":[63],"devices":[64],"due":[65],"its":[67],"compact":[68],"size,":[69],"precision,":[71],"low":[73],"power":[74],"consumption.":[75],"This":[76],"paper":[77],"presents":[78],"design":[80,143],"RetroLiDAR":[83,172],"system,":[84],"chimes":[86],"with":[87],"concept":[89],"backscatter":[91],"wireless":[93],"technology,":[94],"create":[96],"liquid-crystal":[98],"system":[101],"that":[102,166],"can":[103],"be":[104],"directly":[105],"read":[106],"by":[107,177,184,195],"LiDAR.":[108],"On":[109,138],"side,":[112],"we":[113,142],"use":[114],"retroreflective":[115],"materials":[116],"reflect":[118],"LiDAR's":[120],"emitted":[121],"light":[122,136],"back":[123],"employ":[125],"liquid":[127],"crystal":[128],"modulator":[129],"adjust":[131],"intensity":[133],"signal.":[137],"end,":[141],"signal":[145,158],"processing":[146],"pipeline":[147],"demodulate":[149],"marker's":[151],"modulation":[152],"message":[153],"using":[154],"temporal":[156],"received":[157],"strength.":[159],"Experimental":[160],"results":[161],"our":[163],"prototype":[164],"demonstrate":[165],"compared":[167,179,186],"visual":[169],"markers,":[171],"extends":[173],"distance":[176],"2.6x":[178],"QR":[181],"codes":[182],"44%":[185],"AprilTags,":[188],"while":[189],"reducing":[190],"median":[192],"ranging":[193],"error":[194],"85%.":[196],"We":[197],"also":[198],"present":[199],"low-power":[201],"circuit":[203],"design,":[204],"link":[206],"budget":[207],"analysis,":[208],"two":[210],"proof-of-concept":[211],"applications":[212],"validate":[214],"system's":[216],"efficacy":[217],"practicality.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-09T13:55:54.758798","created_date":"2025-10-10T00:00:00"}