{"id":"W1887871568","doi":"10.1109/robot.1996.509193","title":"Guiding functions in application to feedback control of a robotic platform","year":2002,"lang":"en","type":"article","venue":"","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Set (abstract data type); Lyapunov function; Control theory (sociology); Computer science; Mobile robot; Point (geometry); Motion control; Sequence (biology); Control (management); Robot; Control engineering; Feedback control; Engineering; Mathematics; 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":[0.0004318647,0.000659307,0.000375083,0.0004621562,0.0004024449,0.0003789988,0.0004458351,0.0003931099,0.0006575196],"category_scores_gemma":[0.0009864264,0.0001941413,0.000329083,0.0002605685,0.0005976458,0.0003388168,0.0005672584,0.0004860728,0.0001845822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002937759,"about_ca_system_score_gemma":0.0005280001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009517278,"about_ca_topic_score_gemma":0.0006825985,"domain_scores_codex":[0.9997918,0.00006035253,0.00001038407,0.00002595265,0.0000922535,0.00001929225],"domain_scores_gemma":[0.9997658,0.00009729295,0.00002949563,0.00001736512,0.00007402815,0.0000160934],"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":[0.000148951,0.0001029585,0.0004728303,0.0002666771,0.00004196988,0.0002850655,0.0004299668,0.4505877,0.1070055,0.1576554,0.0009504334,0.2820525],"study_design_scores_gemma":[0.00002360446,0.0003393201,0.0002376838,0.00002494232,0.00001623681,0.0001355913,0.00003079025,0.9271528,0.02360058,0.03964823,0.008758341,0.00003174995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01815356,0.0001921302,0.9797483,0.00003904449,0.00002585134,0.00003159047,0.000005345563,0.0001900955,0.001614065],"genre_scores_gemma":[0.546499,0.0007002507,0.4484242,0.00007093389,0.00005929327,0.0002035148,0.00003380594,0.0001119129,0.003897075],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009517278,"threshold_uncertainty_score":0.002283931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01256066208114128,"score_gpt":0.18949815964895,"score_spread":0.1769374975678087,"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."}}