{"id":"W4395955884","doi":"10.18280/jesa.570210","title":"Enhanced Ball Trajectory Tracking Using Visual Servoing with 2-DOF Ball on Plate Balancing System","year":2024,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Visual servoing; Ball (mathematics); Computer vision; Artificial intelligence; Computer science; Trajectory; Tracking (education); Control theory (sociology); Mathematics; Robot; Geometry; Physics; Psychology; Control (management)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001021937,0.000625806,0.0007940148,0.000594264,0.000467481,0.001514524,0.0003117224,0.0001648633,0.00004424135],"category_scores_gemma":[0.0000642848,0.0005134207,0.0002323556,0.0005927933,0.00005633493,0.0009094093,0.00003369353,0.001162446,0.0001672986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001656951,"about_ca_system_score_gemma":0.0001430271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001971479,"about_ca_topic_score_gemma":0.00001773773,"domain_scores_codex":[0.9963716,0.0005000616,0.001022328,0.0004599836,0.0007927472,0.0008532431],"domain_scores_gemma":[0.9987085,0.0003318627,0.0002565057,0.0002605315,0.0001812737,0.0002612846],"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":[0.00007417533,0.00003111223,0.0004286406,0.004452685,0.0009546063,0.002613,0.005449583,0.725235,0.2161711,0.0004757699,0.0001533722,0.04396098],"study_design_scores_gemma":[0.000766256,0.0003266814,0.01232927,0.01614914,0.0001411514,0.004268462,0.000577834,0.960802,0.003693769,0.00001415267,0.0002700228,0.0006613276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7856533,0.002611971,0.2024601,0.00001284165,0.002046873,0.0003688862,0.000009092548,0.002213187,0.004623742],"genre_scores_gemma":[0.9953088,0.00002056353,0.002955589,0.00002441876,0.001100609,0.00001446683,0.0000033483,0.000311656,0.0002605551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.235567,"threshold_uncertainty_score":0.9997317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01245651151361809,"score_gpt":0.2418704331619397,"score_spread":0.2294139216483216,"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."}}