{"id":"W4402215436","doi":"10.1109/tro.2024.3454417","title":"Anytime Replanning of Robot Coverage Paths for Partially Unknown Environments","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Robot; Mobile robot; Computer science; Artificial intelligence; Computer vision","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":[0.0004456264,0.000925105,0.0006744704,0.0003963337,0.0005356161,0.0004618721,0.001101116,0.0005569771,0.0013528],"category_scores_gemma":[0.001276618,0.0004188264,0.000667091,0.0002931539,0.0005952079,0.0006344966,0.0009454754,0.0007401006,0.0002069043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000706716,"about_ca_system_score_gemma":0.0009513552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00581003,"about_ca_topic_score_gemma":0.008695919,"domain_scores_codex":[0.9994951,0.0001162492,0.00001417239,0.0001087359,0.0001702258,0.00009540705],"domain_scores_gemma":[0.9994647,0.0002486229,0.0001109451,0.00007475812,0.0000629002,0.00003809753],"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":[0.0001420395,0.00004571792,0.0005284122,0.00007553911,0.00003640865,0.0001276653,0.0001599228,0.9361193,0.007967172,0.002423886,0.0007584156,0.0516155],"study_design_scores_gemma":[0.00001984859,0.00008211343,0.000302979,0.000007638256,0.00001285465,0.00004997326,0.00005474511,0.9920815,0.003864423,0.001737325,0.001776071,0.00001042652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05086264,0.0002224805,0.9449617,0.0001186084,0.00002401247,0.00006415209,0.00005674385,0.001286311,0.002403377],"genre_scores_gemma":[0.6774563,0.0002078436,0.3180074,0.00009790786,0.00002165175,0.0001542215,0.0002737292,0.0003007947,0.00348026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00581003,"threshold_uncertainty_score":0.01155239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02351335133019631,"score_gpt":0.2632614115300703,"score_spread":0.239748060199874,"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."}}