{"id":"W2901202142","doi":"10.3390/ijgi7110450","title":"Real-Time Efficient Exploration in Unknown Dynamic Environments Using MAVs","year":2018,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Trajectory; Payload (computing); Computer science; Real-time computing; Process (computing); Maximization; Time constraint; Task (project management); Path (computing); Constraint (computer-aided design); Real-time data; Dynamism; Trajectory optimization; Engineering; Mathematical optimization; Computer security; Systems engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007076171,0.0001227563,0.0001472342,0.0006646059,0.00006971785,0.0002255902,0.0008140801,0.00006690462,0.00002013736],"category_scores_gemma":[0.000112887,0.0001177263,0.00006042314,0.0002169884,0.00004536935,0.004974287,0.000136895,0.000154138,0.0002734022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005604465,"about_ca_system_score_gemma":0.0001123993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002832092,"about_ca_topic_score_gemma":8.322968e-7,"domain_scores_codex":[0.9979621,0.00006181422,0.0007902739,0.00009544553,0.0009031106,0.0001872415],"domain_scores_gemma":[0.9986183,0.00004705395,0.0007670648,0.000175345,0.0003236012,0.00006865236],"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":[0.0001863773,0.0002520235,0.000828481,0.00001466441,0.0001425079,0.00008653591,0.01278688,0.8809177,0.01348768,0.002955909,0.0006653596,0.08767586],"study_design_scores_gemma":[0.00072053,0.000110852,0.004661614,0.0001130018,0.000005565712,0.000159271,0.00008626778,0.9910836,0.001140423,0.0004069849,0.001388688,0.0001232552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1157335,0.000006368455,0.8810053,0.0005920776,0.00188751,0.00009517441,0.000004595973,0.00001741158,0.0006580609],"genre_scores_gemma":[0.8180729,0.00003769585,0.1813439,0.0002135812,0.0002323664,0.00000268458,0.0000270838,0.000007400825,0.0000623244],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7023395,"threshold_uncertainty_score":0.4800738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01102584283019968,"score_gpt":0.27078727262066,"score_spread":0.2597614297904603,"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."}}