{"id":"W1662326029","doi":"10.3233/ifs-130957","title":"A novel fuzzy control algorithm for three-dimensional AUV path planning based on sonar model","year":2014,"lang":"en","type":"article","venue":"Journal of Intelligent & Fuzzy Systems","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Shanghai Municipal Education Commission; National Natural Science Foundation of China","keywords":"Sonar; Computer science; Motion planning; Algorithm; Fuzzy logic; Path (computing); Control (management); 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":[0.0003457682,0.0006325,0.000706583,0.0005325388,0.0006490051,0.0007117429,0.001136726,0.0009149462,0.00190756],"category_scores_gemma":[0.0004377976,0.0003119239,0.0005160265,0.0003993958,0.0004165556,0.0005393976,0.0005380884,0.0007743912,0.0003753461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005873162,"about_ca_system_score_gemma":0.0008695422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01132389,"about_ca_topic_score_gemma":0.006762567,"domain_scores_codex":[0.9997995,0.00002102119,0.00001269815,0.00006246831,0.00008056185,0.00002366446],"domain_scores_gemma":[0.999891,0.00002794765,0.00001331549,0.000006605002,0.0000531265,0.000007873944],"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":[0.0001175418,0.00006830998,0.0004231217,0.0002243942,0.0000655839,0.0002128068,0.0002231484,0.5915482,0.02379367,0.01857366,0.002955731,0.3617938],"study_design_scores_gemma":[0.0000223366,0.00004612561,0.00008451295,0.00001101766,0.0000112343,0.00004364586,0.00001171443,0.9951567,0.001640975,0.001298982,0.001663112,0.000009664092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003537239,0.0001656812,0.9944238,0.00004201913,0.00003968443,0.00003365675,0.00001462961,0.0002144224,0.001528943],"genre_scores_gemma":[0.4667194,0.0005751272,0.5253298,0.0001394026,0.00007485189,0.0004836881,0.0001268491,0.00006777944,0.006483038],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01132389,"threshold_uncertainty_score":0.02251595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03047809071087973,"score_gpt":0.2449528871165436,"score_spread":0.2144747964056639,"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."}}