{"id":"https://openalex.org/W7104918830","doi":"https://doi.org/10.48550/arxiv.2511.05889","title":"From Words to Safety: Language-Conditioned Safety Filtering for Robot Navigation","display_name":"From Words to Safety: Language-Conditioned Safety Filtering for Robot Navigation","publication_year":2025,"publication_date":"2025-11-08","ids":{"openalex":"https://openalex.org/W7104918830","doi":"https://doi.org/10.48550/arxiv.2511.05889"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2511.05889","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.05889","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2511.05889","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Feng, Zeyuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Feng, Zeyuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Zhang, Haimingyue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Haimingyue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Bansal, Somil","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bansal, Somil","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.2337999939918518,"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":0.2337999939918518,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.13809999823570251,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.09669999778270721,"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/obstacle","display_name":"Obstacle","score":0.6262999773025513},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5737000107765198},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.5461000204086304},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.5202999711036682},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5060999989509583},{"id":"https://openalex.org/keywords/semantic-mapping","display_name":"Semantic mapping","score":0.398499995470047},{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.39800000190734863},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.3799999952316284}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6435999870300293},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.6262999773025513},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5737000107765198},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.5461000204086304},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.5202999711036682},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5060999989509583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4253999888896942},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.398499995470047},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.39800000190734863},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.3790999948978424},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.336899995803833},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.3124000132083893},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2833999991416931},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.2703999876976013},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C145084290","wikidata":"https://www.wikidata.org/wiki/Q2713824","display_name":"Metric map","level":4,"score":0.2606000006198883},{"id":"https://openalex.org/C132835097","wikidata":"https://www.wikidata.org/wiki/Q7663745","display_name":"System safety","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2511.05889","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.05889","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2511.05889","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.05889","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"},"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":{"As":[0],"robots":[1],"become":[2],"increasingly":[3],"integrated":[4],"into":[5,86],"open-world,":[6],"human-centered":[7],"environments,":[8],"their":[9,52],"ability":[10],"to":[11,18,35],"interpret":[12],"natural":[13],"language":[14,34,78],"instructions":[15,85],"and":[16,25,54,106,119,137,145,156],"adhere":[17],"safety":[19,40,63,88,113],"constraints":[20,121,149],"is":[21,69],"critical":[22],"for":[23,61],"effective":[24],"trustworthy":[26],"interaction.":[27],"Existing":[28],"approaches":[29],"often":[30],"focus":[31],"on":[32],"mapping":[33],"reward":[36],"functions":[37],"instead":[38],"of":[39,71,103,129,154],"specifications":[41,97],"or":[42],"address":[43],"only":[44],"narrow":[45],"constraint":[46],"classes":[47],"(e.g.,":[48],"obstacle":[49],"avoidance),":[50],"limiting":[51],"robustness":[53],"applicability.":[55],"We":[56,125],"propose":[57],"a":[58,76,91,108,151],"modular":[59],"framework":[60,68,132],"language-conditioned":[62],"in":[64,122],"robot":[65],"navigation.":[66],"Our":[67],"composed":[70],"three":[72],"core":[73],"components:":[74],"(1)":[75],"large":[77],"model":[79,109],"(LLM)-based":[80],"module":[81,93],"that":[82,94,115,141],"translates":[83],"free-form":[84],"structured":[87],"specifications,":[89],"(2)":[90],"perception":[92],"grounds":[95],"these":[96],"by":[98],"maintaining":[99],"object-level":[100],"3D":[101],"representations":[102],"the":[104,127,130],"environment,":[105],"(3)":[107],"predictive":[110],"control":[111],"(MPC)-based":[112],"filter":[114],"enforces":[116,146],"both":[117,134],"semantic":[118],"geometric":[120],"real":[123],"time.":[124],"evaluate":[126],"effectiveness":[128],"proposed":[131],"through":[133],"simulation":[135],"studies":[136],"hardware":[138],"experiments,":[139],"demonstrating":[140],"it":[142],"robustly":[143],"interprets":[144],"diverse":[147],"language-specified":[148],"across":[150],"wide":[152],"range":[153],"environments":[155],"scenarios.":[157]},"counts_by_year":[],"updated_date":"2025-11-12T23:15:19.534421","created_date":"2025-11-12T00:00:00"}