{"id":"W2557818991","doi":"10.1115/1.4037331","title":"The Right Invariant Nonlinear Complementary Filter for Low Cost Attitude and Heading Estimation of Platforms","year":2017,"lang":"en","type":"article","venue":"Journal of Dynamic Systems Measurement and Control","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":10,"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":"Control theory (sociology); Extended Kalman filter; Computer science; Invariant extended Kalman filter; Filter (signal processing); Gyroscope; Kalman filter; Nonlinear filter; Filter design; Kernel adaptive filter; Noise (video); Engineering; Artificial intelligence; Computer vision","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":[0.0003620592,0.0004141272,0.000407976,0.0003071325,0.0002560086,0.0004043718,0.0004143617,0.0006348907,0.001202249],"category_scores_gemma":[0.001176413,0.0001417366,0.0004307264,0.0003123006,0.0004461835,0.0005233278,0.0003588934,0.0005960629,0.0004125682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005005567,"about_ca_system_score_gemma":0.0007995722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003513643,"about_ca_topic_score_gemma":0.003314517,"domain_scores_codex":[0.9996766,0.00005181591,0.00001240766,0.00006774814,0.0001676548,0.00002380402],"domain_scores_gemma":[0.9997194,0.0001057315,0.00003933729,0.00003732117,0.0000880416,0.00001014627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002411468,0.00007738936,0.001407372,0.0004324973,0.0001155374,0.0002915798,0.0002208917,0.2163599,0.1317587,0.1364787,0.004750326,0.507866],"study_design_scores_gemma":[0.00001903896,0.000160786,0.0007193467,0.00002157638,0.00003742138,0.0001345194,0.00001466962,0.9619249,0.01597661,0.009370181,0.01159123,0.0000297733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00307748,0.0001406926,0.9957932,0.00003704026,0.00004200919,0.000009967445,0.00001381393,0.00009703101,0.0007887493],"genre_scores_gemma":[0.4549355,0.001142423,0.5356819,0.0001880849,0.0003062568,0.000155827,0.0002207387,0.00008934525,0.007279858],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003513643,"threshold_uncertainty_score":0.00698638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01681653621787003,"score_gpt":0.2435093031165483,"score_spread":0.2266927668986783,"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."}}