{"id":"W1519987888","doi":"10.1109/robot.2003.1241566","title":"A neural network based torque controller for collision-free navigation of mobile robots","year":2004,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Windsor; University of Guelph","funders":"","keywords":"Mobile robot; Robot; Artificial neural network; Torque; Controller (irrigation); Computer science; Control theory (sociology); Nonholonomic system; Robot control; Collision; Lyapunov stability; Control engineering; Lyapunov function; Engineering; Artificial intelligence; Control (management); Nonlinear system","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":[0.000226736,0.0004764893,0.0003479273,0.000279129,0.0003545872,0.0004075858,0.0008033296,0.0005045052,0.001090475],"category_scores_gemma":[0.0005374725,0.0001727011,0.0002133785,0.0002164334,0.000332268,0.0004222035,0.0003315791,0.0005038495,0.0003174452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003591755,"about_ca_system_score_gemma":0.0004286747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003188769,"about_ca_topic_score_gemma":0.003828593,"domain_scores_codex":[0.9998631,0.00001401805,0.00000879405,0.00003143539,0.00006266662,0.00001984932],"domain_scores_gemma":[0.9998186,0.00004076536,0.00003151702,0.00001200548,0.00008477187,0.00001248269],"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":[0.0002661756,0.0001797442,0.0008231543,0.0003971191,0.0001004781,0.0004323239,0.0001269623,0.5408224,0.08616554,0.009827662,0.003323341,0.3575351],"study_design_scores_gemma":[0.00003763204,0.0001254874,0.000354068,0.00001158031,0.00002628989,0.00009173938,0.000008012423,0.9879715,0.007600112,0.0009419945,0.002816642,0.00001496221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01862031,0.0008508115,0.9757065,0.0001202291,0.0002701686,0.00004495083,0.00002262021,0.0008772551,0.003487213],"genre_scores_gemma":[0.8916121,0.0005802778,0.1018478,0.0001582342,0.0001192785,0.0001356112,0.00007086606,0.00005015896,0.005425668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003188769,"threshold_uncertainty_score":0.006340384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01369573831321058,"score_gpt":0.2560953095281433,"score_spread":0.2423995712149327,"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."}}