{"id":"W3132911058","doi":"10.1109/iros45743.2020.9340796","title":"Interacting Multiple Model Navigation System for Quadrotor Micro Aerial Vehicles Subject to Rotor Drag","year":2020,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland","keywords":"Kalman filter; Control theory (sociology); Inertial navigation system; Navigation system; Rotor (electric); Drag; Filter (signal processing); Computer science; Extended Kalman filter; Control engineering; Engineering; Inertial frame of reference; Artificial intelligence; Aerospace engineering; Computer vision; Control (management)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002411077,0.0005083818,0.0005095211,0.0001722669,0.0003584633,0.0004764902,0.000525038,0.0005925236,0.0009834002],"category_scores_gemma":[0.0005072997,0.0002150177,0.0003541638,0.0001791202,0.0002745298,0.0004366242,0.0005483013,0.0005654343,0.0003571214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003405374,"about_ca_system_score_gemma":0.0005797653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005098991,"about_ca_topic_score_gemma":0.004572826,"domain_scores_codex":[0.9998249,0.00002653912,0.000008956385,0.00005674014,0.00006508963,0.00001779696],"domain_scores_gemma":[0.9998373,0.00004275457,0.00004365941,0.00001663797,0.00004960345,0.00001005421],"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":[0.0001435899,0.00004996946,0.00202429,0.0001853504,0.00007378236,0.000253552,0.0001895729,0.8584983,0.02112827,0.009348345,0.001886224,0.1062187],"study_design_scores_gemma":[0.000007525499,0.00006015277,0.0002343469,0.000003321659,0.000007725164,0.00002396583,0.000009561783,0.9970359,0.001090157,0.0004837695,0.001039373,0.000004238858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02044221,0.0001620696,0.9769637,0.00009353893,0.00006700691,0.00002444683,0.00004707655,0.0003979032,0.001802052],"genre_scores_gemma":[0.9036517,0.0002442329,0.09067762,0.00008194153,0.00005368248,0.0001337833,0.0002103099,0.00003271638,0.004914151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005098991,"threshold_uncertainty_score":0.01013863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02290993507074155,"score_gpt":0.2318634156519619,"score_spread":0.2089534805812203,"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."}}