{"id":"W2159473362","doi":"10.1109/icma.2005.1626630","title":"Localization of multiple robots with simple sensors","year":2006,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Trilateration; Robot; Particle filter; Monte Carlo localization; Mobile robot; Range (aeronautics); Centroid; Computer science; Position (finance); Artificial intelligence; Computer vision; Compass; Filter (signal processing); Engineering; Mathematics; Geography; Triangulation","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008866189,0.0008602303,0.00125919,0.0006716388,0.0004531943,0.0007541034,0.001400586,0.00120227,0.001058758],"category_scores_gemma":[0.001936592,0.0005949842,0.0008190898,0.0006010514,0.0009177357,0.001537209,0.001394323,0.0008725043,0.0006776613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006605948,"about_ca_system_score_gemma":0.0007561766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003027104,"about_ca_topic_score_gemma":0.002786785,"domain_scores_codex":[0.9990933,0.0001645769,0.00004519925,0.0002579123,0.0003850024,0.00005395453],"domain_scores_gemma":[0.9993477,0.0002388057,0.000112273,0.0001493166,0.0001130035,0.00003878797],"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":[0.000279202,0.0001643755,0.001876908,0.0003563515,0.0001720905,0.0003061893,0.0003320055,0.5971522,0.05602442,0.02040664,0.001825698,0.321104],"study_design_scores_gemma":[0.00004825246,0.000153084,0.0005340446,0.0000189063,0.00002439722,0.0001195675,0.00002640511,0.9775687,0.0104708,0.005401218,0.005605853,0.00002873237],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004704933,0.00008492261,0.9944305,0.00003331004,0.00002530858,0.00002116909,0.000007504661,0.0002106792,0.000481713],"genre_scores_gemma":[0.207933,0.0003422136,0.787072,0.0001027727,0.00007440165,0.0002093664,0.00007708613,0.00005217909,0.004136898],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003027104,"threshold_uncertainty_score":0.006018996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004645411540673374,"score_gpt":0.175434511493494,"score_spread":0.1707890999528206,"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."}}