{"id":"W4384695012","doi":"10.22215/etd/2023-15476","title":"Deep Reinforcement Learning for Robust Control of 6-DOF Robotic Manipulators","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"PID controller; Control engineering; Reinforcement learning; Robot manipulator; Control theory (sociology); Robotics; Robustness (evolution); Settling time; Computer science; Engineering; Controller (irrigation); Automation; Artificial intelligence; Robot; Control (management); Temperature control; Step response","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":[0.0007297491,0.000557941,0.0004400434,0.0001624576,0.0001635712,0.0003432177,0.0005002426,0.0004474777,0.00110676],"category_scores_gemma":[0.001312896,0.0002021056,0.0003245609,0.0001167628,0.0005195779,0.0003207661,0.0005593072,0.0008108179,0.0001794128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005479411,"about_ca_system_score_gemma":0.000549729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002996712,"about_ca_topic_score_gemma":0.002265637,"domain_scores_codex":[0.9998147,0.00004462918,0.000009566695,0.00003670228,0.00006526423,0.00002911358],"domain_scores_gemma":[0.9995955,0.0001987637,0.00007386202,0.00002752234,0.00008368547,0.00002068354],"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":[0.00003625614,0.00002569173,0.0002321808,0.00005111784,0.00001922855,0.0000331952,0.0000238235,0.9680779,0.004682863,0.002687978,0.0001983289,0.02393147],"study_design_scores_gemma":[0.000003296203,0.00002931045,0.0000452494,0.000002440921,0.000001605413,0.000003847967,0.000001356631,0.998752,0.0005086421,0.0005034711,0.0001472495,0.000001545786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04583691,0.0004794338,0.9497766,0.000153057,0.00003922284,0.00003437711,0.00001616197,0.0003592159,0.003304918],"genre_scores_gemma":[0.9427865,0.0002039869,0.05405736,0.00006740278,0.00002050232,0.00005482206,0.00003011327,0.00002738985,0.002752003],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002996712,"threshold_uncertainty_score":0.005958557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01332724712207902,"score_gpt":0.2293129236751961,"score_spread":0.215985676553117,"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."}}