{"id":"W2980755614","doi":"10.1109/aim.2019.8868577","title":"Directional Endpoint-based Enhanced EKF-SLAM for Indoor Mobile Robots","year":2019,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Extended Kalman filter; Simultaneous localization and mapping; Computer science; Mobile robot; Feature (linguistics); Computer vision; Artificial intelligence; Kalman filter; Line (geometry); Robot; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005835071,0.0001188622,0.0001349122,0.00006975232,0.00003346606,0.00002734075,0.00006119811,0.00007647625,0.0005833555],"category_scores_gemma":[0.00001124669,0.000114321,0.00007308228,0.0001062897,0.000008609515,0.0000636999,0.000005291127,0.00005625203,0.0001348494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005264348,"about_ca_system_score_gemma":0.00002014006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006153345,"about_ca_topic_score_gemma":0.00001094716,"domain_scores_codex":[0.9993644,0.000007734935,0.0001670792,0.0001571718,0.0001133593,0.0001902369],"domain_scores_gemma":[0.9996373,0.00008049601,0.00001828307,0.0001523753,0.00006293277,0.0000486102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001580544,0.00002166571,0.0001080859,0.00005220197,0.00001456174,1.761194e-7,0.00001752542,0.954834,0.04174458,0.0008580042,0.0008014066,0.00153199],"study_design_scores_gemma":[0.0006475358,0.00007794708,0.0002751806,0.0000113802,0.00000705594,3.259856e-7,0.00001882038,0.7644144,0.2288611,0.00007894164,0.005432962,0.0001743438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.106648,0.00003932653,0.8822548,0.00003043152,0.0007413643,0.0005790091,0.0000152846,0.0003712455,0.00932056],"genre_scores_gemma":[0.9866207,0.00000591963,0.01108306,0.0001075483,0.00009135404,0.0001017252,0.0001075702,0.00003998623,0.001842166],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8799727,"threshold_uncertainty_score":0.6387333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004164251139942005,"score_gpt":0.1956174980758427,"score_spread":0.1914532469359007,"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."}}