{"id":"https://openalex.org/W4413917076","doi":"https://doi.org/10.1109/icra55743.2025.11128420","title":"SELP: Generating Safe and Efficient Task Plans for Robot Agents with Large Language Models","display_name":"SELP: Generating Safe and Efficient Task Plans for Robot Agents with Large Language Models","publication_year":2025,"publication_date":"2025-05-19","ids":{"openalex":"https://openalex.org/W4413917076","doi":"https://doi.org/10.1109/icra55743.2025.11128420"},"language":"en","primary_location":{"id":"doi:10.1109/icra55743.2025.11128420","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra55743.2025.11128420","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5102563832","display_name":"Yi Wu","orcid":"https://orcid.org/0009-0008-3128-1147"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi Wu","raw_affiliation_strings":["Purdue University,Computer Science Department,IN,USA,47906"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,Computer Science Department,IN,USA,47906","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088442316","display_name":"Zikang Xiong","orcid":"https://orcid.org/0000-0002-5774-6992"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zikang Xiong","raw_affiliation_strings":["Purdue University,Computer Science Department,IN,USA,47906"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,Computer Science Department,IN,USA,47906","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110053852","display_name":"Yiran Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiran Hu","raw_affiliation_strings":["Purdue University,Computer Science Department,IN,USA,47906"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,Computer Science Department,IN,USA,47906","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shreyash S. Iyengar","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shreyash S. Iyengar","raw_affiliation_strings":["Purdue University,Computer Science Department,IN,USA,47906"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,Computer Science Department,IN,USA,47906","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008181744","display_name":"Nan Jiang","orcid":"https://orcid.org/0000-0003-1712-1872"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nan Jiang","raw_affiliation_strings":["Purdue University,Computer Science Department,IN,USA,47906"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,Computer Science Department,IN,USA,47906","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058453308","display_name":"Aniket Bera","orcid":"https://orcid.org/0000-0002-0182-6985"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aniket Bera","raw_affiliation_strings":["Purdue University,Computer Science Department,IN,USA,47906"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,Computer Science Department,IN,USA,47906","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092118707","display_name":"Lin Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lin Tan","raw_affiliation_strings":["Purdue University,Computer Science Department,IN,USA,47906"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,Computer Science Department,IN,USA,47906","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034957233","display_name":"Suresh Jagannathan","orcid":"https://orcid.org/0000-0001-6871-2424"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suresh Jagannathan","raw_affiliation_strings":["Purdue University,Computer Science Department,IN,USA,47906"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,Computer Science Department,IN,USA,47906","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":14.9945,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.99189877,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2599","last_page":"2605"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9448999762535095,"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/T10028","display_name":"Topic Modeling","score":0.9448999762535095,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.942799985408783,"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/computer-science","display_name":"Computer science","score":0.7150791883468628},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6976104974746704},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5124378800392151},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.41059035062789917},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3937070965766907},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3697081208229065},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3310268223285675},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.32930517196655273},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1812971830368042},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.1479395627975464}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7150791883468628},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6976104974746704},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5124378800392151},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.41059035062789917},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3937070965766907},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3697081208229065},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3310268223285675},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.32930517196655273},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1812971830368042},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.1479395627975464}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra55743.2025.11128420","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra55743.2025.11128420","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5174186738","display_name":null,"funder_award_id":"1901242,2006688","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2522043470","https://openalex.org/W2807172739","https://openalex.org/W2948430169","https://openalex.org/W2964165364","https://openalex.org/W2964514675","https://openalex.org/W2965952829","https://openalex.org/W3090072755","https://openalex.org/W4200438872","https://openalex.org/W4383097638","https://openalex.org/W4383108457","https://openalex.org/W4383108852","https://openalex.org/W4385571689","https://openalex.org/W4388720459","https://openalex.org/W4389519952","https://openalex.org/W4393160744","https://openalex.org/W4394828156","https://openalex.org/W4401414087","https://openalex.org/W4401415471","https://openalex.org/W4402392501","https://openalex.org/W4411113092"],"related_works":["https://openalex.org/W8302103","https://openalex.org/W3171631314","https://openalex.org/W2674584172","https://openalex.org/W2967743314","https://openalex.org/W2606825221","https://openalex.org/W3213722473","https://openalex.org/W2110944602","https://openalex.org/W3196817267","https://openalex.org/W1976600725","https://openalex.org/W3098003361"],"abstract_inverted_index":{"Despite":[0],"significant":[1],"advancements":[2],"in":[3,58,186,199,210,225],"large":[4],"language":[5,17],"models":[6],"(LLMs)":[7],"that":[8],"enhance":[9,54],"robot":[10,166,174,203,219],"agents'":[11],"understanding":[12],"and":[13,33,49,68,83,125,160,168,173,196,218],"execution":[14],"of":[15,88,108,162],"natural":[16],"(NL)":[18],"commands,":[19,78],"ensuring":[20,110],"the":[21,85,91,99,105,111,116,158],"agents":[22,167],"adhere":[23],"to":[24,103,115,122,142,146,150,193],"user-specified":[25],"constraints":[26],"remains":[27],"challenging,":[28],"particularly":[29],"for":[30,215],"complex":[31,60],"commands":[32,152],"long-horizon":[34],"tasks.":[35,61],"To":[36],"address":[37],"this":[38],"challenge,":[39],"we":[40],"present":[41],"three":[42],"key":[43],"insights,":[44],"equivalence":[45],"voting,":[46],"constrained":[47],"decoding,":[48],"domain-specific":[50],"fine-tuning,":[51],"which":[52],"significantly":[53],"LLM":[55,136,144],"planners'":[56],"capability":[57],"handling":[59],"Equivalence":[62],"voting":[63],"ensures":[64],"consistency":[65],"by":[66,184,197],"generating":[67],"sampling":[69],"multiple":[70],"Linear":[71],"Temporal":[72],"Logic":[73],"(LTL)":[74],"formulas":[75,89],"from":[76],"NL":[77,194],"grouping":[79],"equivalent":[80],"LTL":[81,93,101],"formulas,":[82],"selecting":[84],"majority":[86],"group":[87],"as":[90],"final":[92],"formula.":[94],"Constrained":[95],"decoding":[96],"then":[97],"uses":[98],"generated":[100,112],"formula":[102],"enforce":[104],"autoregressive":[106],"inference":[107],"plans,":[109],"plans":[113,127,148],"conform":[114],"LTL.":[117],"Domain-specific":[118],"fine-tuning":[119],"customizes":[120],"LLMs":[121],"produce":[123],"safe":[124],"efficient":[126],"within":[128],"specific":[129],"task":[130,220],"domains.":[131],"Our":[132,213],"approach,":[133],"Safe":[134],"Efficient":[135],"Planner":[137],"(SELP),":[138],"combines":[139],"these":[140],"insights":[141],"create":[143],"planners":[145,183],"generate":[147],"adhering":[149],"user":[151],"with":[153],"high":[154],"confidence.":[155],"We":[156],"demonstrate":[157],"effective-ness":[159],"generalizability":[161],"SELP":[163,180,206],"across":[164],"different":[165],"tasks,":[169,179,205],"including":[170],"drone":[171,177],"navigation":[172,178],"manipulation.":[175],"For":[176,202],"outperforms":[181],"state-of-the-art":[182],"10.8%":[185],"safety":[187,211],"rate":[188],"(i.e.,":[189],"finishing":[190],"tasks":[191],"conforming":[192],"commands)":[195],"19.8%":[198],"plan":[200],"efficiency.":[201],"manipulation":[204],"achieves":[207],"20.4%":[208],"improvement":[209],"rate.":[212],"datasets":[214],"evaluating":[216],"NL-to-LTL":[217],"planning":[221],"will":[222],"be":[223],"released":[224],"github.com/lt-asset/selp.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}