{"id":"W4285069906","doi":"10.20517/ir.2022.13","title":"Motion planning and tracking control of unmanned underwater vehicles: technologies, challenges and prospects","year":2022,"lang":"en","type":"article","venue":"Intelligence & Robotics","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Unmanned underwater vehicle; Motion planning; Underwater; Remotely operated underwater vehicle; Tracking (education); Trajectory; Motion control; Tracking system; Computer science; Engineering; Systems engineering; Robot; Mobile robot; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003947158,0.0003191972,0.0003521905,0.00040598,0.0002504567,0.0009704317,0.0004947211,0.0005958808,0.0006524617],"category_scores_gemma":[0.0003607671,0.0001639946,0.000201245,0.0006358905,0.000434528,0.001358125,0.0004781206,0.0005162991,0.0001890095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002497211,"about_ca_system_score_gemma":0.0004828007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001097307,"about_ca_topic_score_gemma":0.0009213437,"domain_scores_codex":[0.9997813,0.00004109633,0.00001344536,0.00003439289,0.0001094746,0.00002019984],"domain_scores_gemma":[0.9998178,0.00006693484,0.00003258186,0.00001047855,0.00005893913,0.00001331752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007397177,0.0001127017,0.001401157,0.001849532,0.0000420573,0.0002418606,0.0003187781,0.1089682,0.01450249,0.07527705,0.004219009,0.7929932],"study_design_scores_gemma":[0.00002718392,0.0008344278,0.002917941,0.000839788,0.00007249122,0.0005242988,0.000772311,0.7338989,0.01093059,0.07804251,0.1710361,0.0001034242],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.0257339,0.4195732,0.527459,0.002311135,0.0005313299,0.00006570519,0.00003794762,0.0002048303,0.02408298],"genre_scores_gemma":[0.50226,0.3677119,0.1150825,0.0005358987,0.001312477,0.0001404498,0.0001308725,0.00004065878,0.01278519],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.001097307,"threshold_uncertainty_score":0.002182722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04151603262413715,"score_gpt":0.2419281261417393,"score_spread":0.2004120935176021,"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."}}