{"id":"W3080982884","doi":"10.1177/1045389x20947166","title":"Suppression of robot vibrations using input shaping and learning-based structural models","year":2020,"lang":"en","type":"article","venue":"Journal of Intelligent Material Systems and Structures","topic":"Dynamics and Control of Mechanical Systems","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Robot; Input shaping; Vibration; Engineering; Payload (computing); Artificial neural network; Control engineering; Workspace; Artificial intelligence; Industrial robot; Vibration control; Control theory (sociology); Computer science; Acoustics","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":[0.0002398924,0.0004212489,0.0002746848,0.0001891988,0.0001492659,0.0002186199,0.0004513917,0.0003101746,0.0007311825],"category_scores_gemma":[0.0005666915,0.000174198,0.0003330726,0.0001273278,0.0003348987,0.0003479274,0.0003496629,0.0003633926,0.0002033029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002244284,"about_ca_system_score_gemma":0.0003100368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001021686,"about_ca_topic_score_gemma":0.001345782,"domain_scores_codex":[0.9998511,0.00002697362,0.000007757668,0.0000280941,0.00007230262,0.00001373171],"domain_scores_gemma":[0.9997402,0.0001099697,0.00005765956,0.00003662884,0.00004810906,0.00000739192],"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":[0.00009912879,0.0000707153,0.0004060205,0.00009272517,0.00001955375,0.00005610042,0.00009910006,0.7909452,0.07646295,0.002034696,0.0002308001,0.1294829],"study_design_scores_gemma":[0.00000371086,0.00006439842,0.0001796977,0.000004462385,0.000004353472,0.0000177369,0.000004156117,0.9898183,0.009242994,0.0003584842,0.0002979083,0.000003833449],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02877324,0.00006869208,0.9689743,0.00002965039,0.000007885794,0.00001722138,0.000008266686,0.0004828838,0.001637825],"genre_scores_gemma":[0.911038,0.0000990132,0.08689492,0.00002707952,0.000008654656,0.000056627,0.0000377102,0.00004912862,0.001788744],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001021686,"threshold_uncertainty_score":0.002445996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02672573446637497,"score_gpt":0.2332755952036955,"score_spread":0.2065498607373206,"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."}}