{"id":"W4405444403","doi":"10.3390/robotics13120180","title":"Backstepping-Based Nonsingular Terminal Sliding Mode Control for Finite-Time Trajectory Tracking of a Skid-Steer Mobile Robot","year":2024,"lang":"en","type":"article","venue":"Robotics","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Backstepping; Control theory (sociology); Mobile robot; Trajectory; Lyapunov stability; Terminal sliding mode; Control engineering; Lyapunov function; Engineering; Sliding mode control; Robot; Computer science; Adaptive control; Nonlinear system; Control (management); Artificial intelligence; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002769862,0.0003398249,0.0005682763,0.0002585232,0.00007672654,0.0001075191,0.0002168442,0.0001982195,0.00003113803],"category_scores_gemma":[0.00008620768,0.0003547242,0.0003729178,0.0002076838,0.00004147725,0.0001668589,0.00001825444,0.0002526426,0.00002207429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001354419,"about_ca_system_score_gemma":0.000106459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005469774,"about_ca_topic_score_gemma":0.00001304415,"domain_scores_codex":[0.9983513,0.00003184786,0.0005498987,0.0003294794,0.0002347136,0.0005027481],"domain_scores_gemma":[0.9984192,0.0009609453,0.00005937951,0.0003273303,0.000111894,0.0001212727],"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":[0.00003825646,0.00004814459,0.0000267051,0.0007008917,0.0001489506,0.00002937775,0.0001352474,0.9661518,0.02334047,0.0002351275,0.0001339793,0.009011078],"study_design_scores_gemma":[0.001207027,0.0001351968,0.00003071727,0.0004638727,0.0002379122,0.000009021275,0.00002349787,0.9955882,0.001160067,0.000139482,0.000627513,0.0003775294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006223768,0.002292435,0.9888721,0.00006679438,0.0007736863,0.0008259416,0.0001575458,0.0005114469,0.0002762733],"genre_scores_gemma":[0.9805761,0.00001476885,0.0186743,0.00004812317,0.0002589493,0.0001082459,0.00004586463,0.0001291868,0.0001444828],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9743523,"threshold_uncertainty_score":0.9998904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00803776246466502,"score_gpt":0.234342357870277,"score_spread":0.2263045954056119,"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."}}