{"id":"W3018466250","doi":"10.15837/ijccc.2020.3.3844","title":"Grey Wolf Optimizer-Based Approaches to Path Planning and Fuzzy Logic-based Tracking Control for Mobile Robots","year":2020,"lang":"en","type":"article","venue":"International Journal of Computers Communications & Control","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mobile robot; Computer science; Trajectory; Fuzzy logic; Motion planning; Nonholonomic system; Robot; Controller (irrigation); Path (computing); Tracking (education); Mathematical optimization; Control theory (sociology); Control (management); Artificial intelligence; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008576961,0.000256969,0.0005136483,0.0003336711,0.0002131863,0.0005378438,0.004113751,0.00008335409,0.000001361066],"category_scores_gemma":[0.000349127,0.0002461793,0.0002288461,0.000233619,0.00009822134,0.0005219348,0.0002422316,0.0003885357,0.000003379189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00011308,"about_ca_system_score_gemma":0.000257186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004363838,"about_ca_topic_score_gemma":2.66418e-7,"domain_scores_codex":[0.9976668,0.0002975409,0.0008491479,0.0003322062,0.0005599014,0.0002943881],"domain_scores_gemma":[0.9953618,0.00208266,0.0007369007,0.0006708122,0.0008167143,0.0003310823],"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":[0.0002365563,0.0001667547,0.0009105442,0.00001034784,0.0002332919,0.00003195809,0.0008053426,0.9684417,0.0002442709,0.003189271,0.0004834787,0.02524651],"study_design_scores_gemma":[0.005925149,0.0005929963,0.001077482,0.0001922657,0.00005015222,0.00005049236,0.00005461142,0.9898181,0.00006999796,0.0005033591,0.00142479,0.0002406324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006259038,0.0008917623,0.9538022,0.04338633,0.0004867242,0.0006323535,0.00003549456,0.00008745963,0.00005179418],"genre_scores_gemma":[0.5223676,0.000003648484,0.4726873,0.004734921,0.0001354617,0.00004959979,0.000008116769,0.00001222371,0.000001103763],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5217417,"threshold_uncertainty_score":0.999999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1316061996431636,"score_gpt":0.3115582995587154,"score_spread":0.1799520999155517,"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."}}