{"id":"W2110373459","doi":"10.1109/robot.1992.220044","title":"3D relative position and orientation estimation using Kalman filter for robot control","year":2003,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Kalman filter; Orientation (vector space); Computer vision; Artificial intelligence; Position (finance); Extended Kalman filter; Computer science; Pose; Tracking (education); Invariant extended Kalman filter; Fast Kalman filter; Filter (signal processing); Robot; Object (grammar); Noise (video); Mathematics; Image (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004100337,0.0004635111,0.0005258996,0.0005159417,0.0002351446,0.0006943905,0.0004318943,0.0004991416,0.001244588],"category_scores_gemma":[0.001117911,0.0003052244,0.000492062,0.000477488,0.0003806482,0.0009114054,0.0004183948,0.0004237195,0.0005418119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006134216,"about_ca_system_score_gemma":0.0005385261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009056711,"about_ca_topic_score_gemma":0.006499439,"domain_scores_codex":[0.9997379,0.00006521729,0.00001838328,0.00004796867,0.000108461,0.00002213045],"domain_scores_gemma":[0.9997723,0.00008302444,0.000043125,0.00002979124,0.00006583433,0.000005961744],"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":[0.0001067882,0.00003635678,0.0008670539,0.0001633577,0.00007572852,0.0001210094,0.0001420033,0.6823506,0.0242729,0.03240093,0.003263416,0.2561998],"study_design_scores_gemma":[0.000006119734,0.00002460335,0.0003243556,0.000009677494,0.00001286706,0.00003696995,0.00000686207,0.9886346,0.003121033,0.004975022,0.00283,0.00001790968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002040307,0.0003268212,0.9966575,0.00004303187,0.00001931871,0.000005316106,0.00001492455,0.0003738893,0.000518833],"genre_scores_gemma":[0.5261676,0.002727023,0.4643259,0.00009292711,0.0001382955,0.0001807867,0.0002913219,0.00016001,0.005916064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009056711,"threshold_uncertainty_score":0.01800799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01314216648804931,"score_gpt":0.23545078648787,"score_spread":0.2223086199998207,"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."}}