{"id":"W4384787996","doi":"10.1109/tcst.2023.3292466","title":"Energy-Efficient Integrated Motion Planning and Control for Unmanned Surface Vessels","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Control Systems Technology","topic":"Maritime Navigation and Safety","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"Motion control; Motion planning; Energy (signal processing); Unmanned surface vehicle; Motion (physics); Control (management); Computer science; Aerospace engineering; Control engineering; Engineering; Physics; Robot; Artificial intelligence; Marine engineering","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":[0.0003409967,0.0006720758,0.0005572553,0.0003084498,0.0003295719,0.0006336174,0.0006815724,0.0004258578,0.001227655],"category_scores_gemma":[0.0005509523,0.0003850589,0.0003765144,0.000494339,0.0004484656,0.0009337812,0.0008514857,0.0007605695,0.0001579846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003962859,"about_ca_system_score_gemma":0.0009839085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005440578,"about_ca_topic_score_gemma":0.004928938,"domain_scores_codex":[0.9996848,0.0000436999,0.00001087984,0.0000654652,0.0001439952,0.000051188],"domain_scores_gemma":[0.999826,0.0000653874,0.0000352193,0.000018753,0.00004106491,0.00001363103],"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":[0.00005238494,0.00002873953,0.0002230709,0.00005195844,0.00001875994,0.00006282346,0.00003576314,0.9390273,0.004385579,0.00623224,0.000496755,0.04938468],"study_design_scores_gemma":[0.000003045512,0.00002578165,0.00009602772,0.000002224518,0.000003168976,0.000007742466,0.000004799714,0.9976414,0.000631957,0.001103043,0.0004784373,0.000002328861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01430139,0.000392189,0.9821629,0.00008317053,0.0000305948,0.0000204239,0.00002532855,0.0002105699,0.002773522],"genre_scores_gemma":[0.9254065,0.00036776,0.0716857,0.00004748008,0.00003864502,0.0000724547,0.00009206792,0.00004067652,0.002248692],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005440578,"threshold_uncertainty_score":0.01081783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009034951597113238,"score_gpt":0.2197279254346726,"score_spread":0.2106929738375593,"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."}}