{"id":"W2528263515","doi":"10.1109/mesa.2016.7587184","title":"Cooperative control of multiple UAVs for forest fire monitoring and detection","year":2016,"lang":"en","type":"article","venue":"","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Control reconfiguration; Trajectory; Frame (networking); Computer science; Cartesian coordinate system; Fire control; Fire detection; Controller (irrigation); Mode (computer interface); Tracking (education); Real-time computing; Reference frame; Search and rescue; Control theory (sociology); Mobile robot; Robot; Simulation; Control (management); Engineering; Artificial intelligence; Telecommunications","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":[0.0002805796,0.0004437585,0.0003127896,0.0001896915,0.0002931296,0.000328288,0.0006078036,0.0002477376,0.0004479177],"category_scores_gemma":[0.00038791,0.0001434391,0.0002839012,0.0001365604,0.0002404156,0.0002869651,0.0004575889,0.000285045,0.00009745894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001972258,"about_ca_system_score_gemma":0.0002839351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002069963,"about_ca_topic_score_gemma":0.001980508,"domain_scores_codex":[0.9998336,0.00002923644,0.00000773371,0.00005723868,0.00004362728,0.00002857242],"domain_scores_gemma":[0.9998509,0.00003398474,0.00004397789,0.00002096602,0.00003072726,0.0000194593],"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":[0.0003335238,0.000166222,0.00269095,0.0001276144,0.00007527261,0.0005033617,0.0002951095,0.7358071,0.08013727,0.006211452,0.0006689897,0.1729831],"study_design_scores_gemma":[0.00002345837,0.0002434249,0.0005093293,0.000003939892,0.00001650199,0.00004829663,0.00003280804,0.9934307,0.004090073,0.0007308309,0.000865435,0.000005223498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1596796,0.0002672074,0.8360347,0.00006416276,0.00006365288,0.00004398405,0.00001241148,0.0003092372,0.003525069],"genre_scores_gemma":[0.9821417,0.00006184691,0.01685764,0.000009735875,0.000009583372,0.00002979766,0.000009607054,0.000003428086,0.0008766055],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002069963,"threshold_uncertainty_score":0.00411582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01563105978540066,"score_gpt":0.2339789277284071,"score_spread":0.2183478679430065,"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."}}