{"id":"W4312302359","doi":"10.1109/icarm54641.2022.9959352","title":"Multi-Objective Admittance Control: An LMI-Based Method","year":2022,"lang":"en","type":"article","venue":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"National Natural Science Foundation of China","keywords":"Admittance; Robustness (evolution); Control theory (sociology); Passivity; Robust control; Admittance parameters; Computer science; Robot; Control engineering; Control system; Engineering; Control (management); Electrical impedance; Voltage; Artificial intelligence","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":[0.0009225774,0.00150896,0.0008767758,0.0006882945,0.0004557032,0.001010587,0.001284778,0.0009555494,0.007274001],"category_scores_gemma":[0.001118293,0.0004554268,0.0008080759,0.0005694624,0.0006259591,0.0007937356,0.001149056,0.001459255,0.00104684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006286747,"about_ca_system_score_gemma":0.0007706114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002544174,"about_ca_topic_score_gemma":0.002352511,"domain_scores_codex":[0.999604,0.0001069079,0.00002213905,0.00007178636,0.0001632256,0.0000319132],"domain_scores_gemma":[0.9996432,0.0001524567,0.00005104869,0.00002422382,0.0001137748,0.00001534564],"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":[0.00007652722,0.00009241497,0.0001771641,0.0004516202,0.00007801784,0.0002773353,0.0002220339,0.7642826,0.01825888,0.05011939,0.003836514,0.1621275],"study_design_scores_gemma":[0.00001028393,0.00004279732,0.00003270896,0.00001254951,0.000007010056,0.0000233041,0.000007842846,0.9945867,0.000765185,0.002925292,0.001579971,0.000006321503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007800048,0.00007647694,0.9958726,0.00005232237,0.00002244596,0.00002919483,0.00001123012,0.0001502088,0.003005574],"genre_scores_gemma":[0.4775267,0.0006886143,0.5055392,0.0002651876,0.0002145557,0.0007659253,0.0001777296,0.0003418463,0.0144803],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007274001,"threshold_uncertainty_score":0.02433395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01958398972552013,"score_gpt":0.289882857674142,"score_spread":0.2702988679486218,"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."}}