{"id":"W2192028265","doi":"10.1016/j.oceaneng.2015.08.061","title":"Precise trajectory control for an inspection class ROV","year":2015,"lang":"en","type":"article","venue":"Ocean Engineering","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":106,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Remotely operated underwater vehicle; Control theory (sociology); Controller (irrigation); Trajectory; Kalman filter; Kinematics; PID controller; Control engineering; Computer science; Lyapunov function; SIGNAL (programming language); Extended Kalman filter; Adaptive control; Control system; Engineering; Artificial intelligence; Mobile robot; Robot; Control (management)","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":[0.0003350347,0.0004720422,0.000438783,0.0002645671,0.0005745589,0.0005598032,0.000486966,0.0006993945,0.0009366531],"category_scores_gemma":[0.0007058393,0.0002611383,0.0002405578,0.0002711169,0.0005998491,0.0003466696,0.0007751586,0.0005302287,0.0001777656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004722943,"about_ca_system_score_gemma":0.0007343913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0143036,"about_ca_topic_score_gemma":0.007906786,"domain_scores_codex":[0.9997954,0.00002534081,0.000006931104,0.00006211541,0.0000693905,0.00004089174],"domain_scores_gemma":[0.9997421,0.0000512737,0.00006038937,0.0000379065,0.00008951139,0.00001874079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004621409,0.00005938096,0.001407432,0.00009246123,0.00002714808,0.0002631261,0.000325545,0.880303,0.05080579,0.005878525,0.001160717,0.05921479],"study_design_scores_gemma":[0.00001888798,0.0002245303,0.0008605833,0.000004290202,0.000005098079,0.00001972046,0.00002568723,0.9957527,0.001796646,0.0006866058,0.0005974153,0.000007856955],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.245502,0.000187306,0.7458383,0.0003404341,0.0001097127,0.00006551775,0.00007725453,0.0005524725,0.007327033],"genre_scores_gemma":[0.9912847,0.00002452736,0.006737062,0.00001386167,0.000007127229,0.00002191814,0.00002242303,0.00001129066,0.001877105],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0143036,"threshold_uncertainty_score":0.02844065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02711062792788049,"score_gpt":0.2182002104106245,"score_spread":0.191089582482744,"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."}}