{"id":"W2285870816","doi":"10.1109/tcst.2015.2454484","title":"Vision-Based Model Predictive Control for Steering of a Nonholonomic Mobile Robot","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Control Systems Technology","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":162,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Program for New Century Excellent Talents in University; National Natural Science Foundation of China","keywords":"Control theory (sociology); Kinematics; Model predictive control; Quadratic programming; Controller (irrigation); Nonholonomic system; Computer science; Mobile robot; Trajectory; Control engineering; Convergence (economics); Stability (learning theory); Artificial neural network; Vehicle dynamics; Robot; Engineering; Control (management); Mathematics; Mathematical optimization; 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":[0.0002233948,0.0004614184,0.0004376691,0.0002032073,0.0002775058,0.0004487047,0.0005644735,0.0004148641,0.0008261399],"category_scores_gemma":[0.000443333,0.0002573274,0.0003155115,0.0002222972,0.0003642743,0.0003915215,0.0003670881,0.0005873395,0.0002217553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002711507,"about_ca_system_score_gemma":0.0006245456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004242202,"about_ca_topic_score_gemma":0.004872448,"domain_scores_codex":[0.9998635,0.00002102439,0.000006264755,0.00002656701,0.00006746947,0.00001506917],"domain_scores_gemma":[0.9998603,0.00003738749,0.00002848098,0.0000122133,0.00005231585,0.000009254035],"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":[0.0001432703,0.00007619922,0.000546815,0.0002963103,0.00004788769,0.0002411241,0.000163756,0.8084137,0.03962922,0.007456665,0.001250891,0.1417342],"study_design_scores_gemma":[0.000008507718,0.00006646605,0.0001626713,0.000005472598,0.000007594994,0.00002111862,0.000006866016,0.9955249,0.00265341,0.0006630287,0.0008742039,0.000005853824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01987616,0.0007155076,0.9758353,0.0001204357,0.00009141333,0.00002807667,0.0000147968,0.0003983456,0.00291996],"genre_scores_gemma":[0.9456641,0.0005406908,0.05009043,0.00006850448,0.00004396076,0.00006654998,0.00004487983,0.00002510123,0.003455844],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004242202,"threshold_uncertainty_score":0.008435011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01444763781235136,"score_gpt":0.2386203537380057,"score_spread":0.2241727159256543,"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."}}