{"id":"W2971925930","doi":"10.1109/cdc40024.2019.9029915","title":"Robotic Coverage for Continuous Mapping Ahead of a Moving Vehicle","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Curvature; Plan (archaeology); Path (computing); Computer science; Cover (algebra); Set (abstract data type); Simple (philosophy); Class (philosophy); Simulation; Engineering; Artificial intelligence; Mathematics; Geometry; 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":[0.0003498511,0.0004282897,0.000340688,0.0003215224,0.0003221947,0.0003652831,0.0005027194,0.0004924046,0.001173871],"category_scores_gemma":[0.001956175,0.0002586665,0.000276771,0.0003474841,0.0006644093,0.0008781006,0.0008546057,0.0003882344,0.0001997499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004565626,"about_ca_system_score_gemma":0.000358278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002390209,"about_ca_topic_score_gemma":0.001875744,"domain_scores_codex":[0.9997439,0.00005979805,0.000007489373,0.00006095722,0.00008491279,0.00004295487],"domain_scores_gemma":[0.9992805,0.000463226,0.00009265695,0.00007891384,0.00004354505,0.00004110882],"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":[0.0001110903,0.00002631674,0.001115476,0.0000809789,0.00002139328,0.0002641852,0.0002007886,0.9337217,0.01281696,0.01507723,0.0005536369,0.03601015],"study_design_scores_gemma":[0.00001505351,0.00009121569,0.0006148117,0.000006094175,0.000006922584,0.0001148383,0.0000657955,0.9855022,0.002993493,0.009153612,0.001427881,0.000008004877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1830434,0.0002645557,0.8126985,0.000131532,0.00001648796,0.00003438386,0.00007270891,0.000355586,0.003382828],"genre_scores_gemma":[0.9269707,0.0001237226,0.07139132,0.00002168949,0.00001259413,0.00004902067,0.0001013376,0.00003996146,0.001289657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002390209,"threshold_uncertainty_score":0.004752576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03306253037631292,"score_gpt":0.264984412469957,"score_spread":0.2319218820936441,"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."}}