{"id":"W2110140328","doi":"10.1109/robot.1996.503788","title":"Adaptive control for constrained robots without using regressor","year":2002,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Trajectory; Robot; Constraint (computer-aided design); Controller (irrigation); Nonlinear system; Adaptive control; Computer science; Degrees of freedom (physics and chemistry); Control (management); Robot end effector; Tracking (education); Robot control; Control engineering; Mathematical optimization; Mathematics; Mobile robot; Artificial intelligence; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00005400206,0.00009634057,0.0001339314,0.00004733498,0.00005988224,0.00002457859,0.00004190458,0.00004869771,0.0005460778],"category_scores_gemma":[0.00002682976,0.00009044135,0.00004606124,0.00005579497,0.00001853611,0.00008820067,0.000003053556,0.00007028061,0.00003398176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002715672,"about_ca_system_score_gemma":0.000002588205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004119806,"about_ca_topic_score_gemma":0.000003929823,"domain_scores_codex":[0.9995262,0.00001215659,0.000132037,0.00009539899,0.00006205097,0.0001721299],"domain_scores_gemma":[0.9997593,0.00005701049,0.0000218574,0.00007987961,0.00003295115,0.00004905213],"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":[0.000006819987,0.000004781425,0.0002503323,0.000008883836,0.0000316974,0.000001290817,0.0001120943,0.9942609,0.001516199,0.001795823,0.0005577915,0.001453385],"study_design_scores_gemma":[0.0009653646,0.00001937628,0.0001617799,0.00001461465,0.00001525009,0.000007387976,0.0000771671,0.9978885,0.000157901,0.00003413629,0.0005321667,0.0001263549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003993618,0.0001019274,0.9788263,0.00007231374,0.0001434451,0.0002622563,0.000001004258,0.000345413,0.01625366],"genre_scores_gemma":[0.9764726,0.000001956541,0.02214875,0.00007956021,0.00008332449,0.00001106272,0.000001469,0.00002576173,0.00117551],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.972479,"threshold_uncertainty_score":0.5979169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06973160249043536,"score_gpt":0.2537959192523344,"score_spread":0.184064316761899,"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."}}