{"id":"W7104562205","doi":"10.1109/lra.2025.3630870","title":"Decentralized and Fully Onboard: Range-Aided Cooperative Localization and Navigation on Micro Aerial Vehicles","year":2025,"lang":"","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Odometry; Robot; Scalability; Block (permutation group theory); Computation; Decentralised system; Mobile robot; State (computer science); Control (management)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002283621,0.0003375627,0.0004019216,0.0001850833,0.0002663798,0.0003878093,0.000586034,0.0003733113,0.0007685386],"category_scores_gemma":[0.0008622507,0.0002353516,0.0001983542,0.0002292648,0.0004643571,0.0006361815,0.0007291492,0.0003720385,0.0002037135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003065638,"about_ca_system_score_gemma":0.0005262187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005680674,"about_ca_topic_score_gemma":0.005715267,"domain_scores_codex":[0.9997717,0.0000571988,0.000006118195,0.0000523855,0.00007949102,0.00003322507],"domain_scores_gemma":[0.9996799,0.0001050009,0.00006183773,0.00006962642,0.00006236226,0.0000212877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008820528,0.00002427983,0.0007112218,0.00003769694,0.00001783204,0.00009814987,0.00009970891,0.9168673,0.009186435,0.006507632,0.0009695833,0.06539193],"study_design_scores_gemma":[0.000008464225,0.00002765284,0.0002534277,0.000001632742,0.000002406004,0.00001215427,0.00001280677,0.9960147,0.001159287,0.001982867,0.0005213997,0.000003183297],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08686736,0.0001558141,0.909315,0.000134982,0.0000282034,0.00003345,0.00005397695,0.0005111583,0.002900007],"genre_scores_gemma":[0.9386504,0.00007989685,0.05928388,0.00003131086,0.00001775654,0.00004159464,0.00007379955,0.00003462255,0.001786631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005680674,"threshold_uncertainty_score":0.01129526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01015579049761753,"score_gpt":0.2413478301942976,"score_spread":0.2311920396966801,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}