{"id":"W2323384454","doi":"10.2514/6.2012-5048","title":"Vision-based Quadrotor Micro-UAV Position and Yaw Estimation and Control","year":2012,"lang":"en","type":"article","venue":"AIAA Guidance, Navigation, and Control Conference","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heading (navigation); Position (finance); Kalman filter; Computer vision; Computer science; Euler angles; Artificial intelligence; Tracking (education); Yaw; Pose; Extended Kalman filter; Control theory (sociology); Control (management); Engineering; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008648076,0.00035053,0.0004806114,0.0001361784,0.0004072669,0.0006482933,0.0003236385,0.0001762382,0.000006324292],"category_scores_gemma":[0.0001248785,0.0003346278,0.00005565795,0.0002430969,0.0002228281,0.001434021,0.00005139911,0.0001715042,0.00001912552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000652218,"about_ca_system_score_gemma":0.0001311174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001295075,"about_ca_topic_score_gemma":0.00000797931,"domain_scores_codex":[0.9976245,0.0002992717,0.0006177231,0.0006004538,0.0003453766,0.0005127368],"domain_scores_gemma":[0.998,0.0004079546,0.0003666515,0.000473716,0.0004459894,0.0003057392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006141255,0.0006778213,0.291117,0.0007398563,0.000464975,0.00002444536,0.002133522,0.0004178954,0.2956861,0.233201,0.001429199,0.1734941],"study_design_scores_gemma":[0.01029119,0.0002510112,0.2329778,0.0004830208,0.0001358582,0.00004968001,0.00006104074,0.7482262,0.002046907,0.003070483,0.00176285,0.0006439773],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1336149,0.002575761,0.8596907,0.002259083,0.0003397322,0.001087647,0.00007283127,0.0001687734,0.0001905551],"genre_scores_gemma":[0.9951584,0.00002691623,0.003360467,0.001017545,0.0001026747,0.0002207603,0.00004788301,0.00001627308,0.00004911596],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8615435,"threshold_uncertainty_score":0.9999106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007684993071630016,"score_gpt":0.2411368673868919,"score_spread":0.2334518743152619,"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."}}