{"id":"W1982539563","doi":"10.1299/jsdd.1.536","title":"Genetic Fuzzy Control for Path-Tracking of an Autonomous Robotic Bicycle","year":2007,"lang":"en","type":"article","venue":"Journal of System Design and Dynamics","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Science Council","keywords":"Holonomic; Control theory (sociology); Fuzzy logic; Path (computing); Genetic algorithm; Fuzzy control system; Constraint (computer-aided design); Motion planning; Tracking (education); Controller (irrigation); Nonholonomic system; Computer science; Mathematics; Mathematical optimization; Control (management); Mobile robot; Artificial intelligence; Robot","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001115885,0.0001673781,0.0005051529,0.000200133,0.00005003728,0.00004336162,0.0001537863,0.0001213062,6.135883e-7],"category_scores_gemma":[0.00002397849,0.0001501305,0.0001333693,0.00008051241,0.00002609109,0.0001696197,0.000007569019,0.0001243173,4.057532e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001687129,"about_ca_system_score_gemma":0.0000436154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006732084,"about_ca_topic_score_gemma":0.00002461939,"domain_scores_codex":[0.9986082,0.00004030568,0.0008064038,0.0001034472,0.0001736207,0.0002680787],"domain_scores_gemma":[0.9988769,0.0003018209,0.0003030341,0.0001397874,0.0002053304,0.0001730785],"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":[0.000170108,0.00004078064,0.0007476042,0.000507092,0.0001221245,0.00005816005,0.00009916308,0.964252,0.005633288,0.001046627,0.000005599535,0.02731744],"study_design_scores_gemma":[0.00168378,0.0004242113,0.006731951,0.0002209651,0.0001266589,0.000412724,0.000231636,0.9896094,0.00004505282,0.0003540931,0.000005209063,0.0001543723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1708723,0.001119069,0.8271654,0.000006799001,0.0004070795,0.0003106286,0.000008516405,0.00003694212,0.00007332353],"genre_scores_gemma":[0.9610639,0.00002727869,0.03868231,0.000008261872,0.0001676883,0.00000387968,0.000001331232,0.00003677222,0.000008628177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7901916,"threshold_uncertainty_score":0.6122143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00767652133733854,"score_gpt":0.2089612414425433,"score_spread":0.2012847201052048,"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."}}