{"id":"W4402586310","doi":"10.1109/tits.2024.3453769","title":"Obstacle Avoidance for a Large-Scale High-Speed Underactuated AUV in Complex Environments","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Shanghai Jiao Tong University; National Natural Science Foundation of China","keywords":"Obstacle avoidance; Underactuation; Scale (ratio); Computer science; Collision avoidance; Obstacle; Control theory (sociology); Control engineering; Engineering; Artificial intelligence; Mobile robot; Physics; Control (management); Robot; Geography","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":[0.0001885026,0.0005007319,0.0003675293,0.0001722833,0.0004172042,0.0003448698,0.0004981763,0.000369291,0.0003413741],"category_scores_gemma":[0.0003020298,0.0001843543,0.0002695434,0.0001241142,0.0004665765,0.0004289596,0.000774092,0.0004645904,0.00006730647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002532479,"about_ca_system_score_gemma":0.0005781295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00415025,"about_ca_topic_score_gemma":0.002706739,"domain_scores_codex":[0.9998949,0.00001609888,0.00000475404,0.00002821161,0.00004052519,0.00001547563],"domain_scores_gemma":[0.9998943,0.00002774731,0.00003013327,0.00001353816,0.00002232434,0.00001201628],"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":[0.00005742461,0.0000269104,0.00116302,0.0001063334,0.00003180823,0.000180953,0.0002729751,0.898289,0.039358,0.005501458,0.0004011689,0.05461106],"study_design_scores_gemma":[0.000007699757,0.00009257724,0.0002655195,0.000003113785,0.000007180057,0.00002297208,0.00002449466,0.9960566,0.002184729,0.0007071084,0.0006236376,0.000004431912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1146391,0.0001786051,0.8829378,0.00009533895,0.00002864981,0.00002768115,0.000009332223,0.0002002666,0.001883175],"genre_scores_gemma":[0.9600072,0.00008770405,0.03849246,0.00002979285,0.0000126248,0.00004522068,0.00001784253,0.00001109713,0.001296077],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00415025,"threshold_uncertainty_score":0.008252144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04004288687547259,"score_gpt":0.2813557808184398,"score_spread":0.2413128939429672,"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."}}