{"id":"W4206746675","doi":"10.1109/access.2021.3136226","title":"Survey of RPAS Autonomous Control Systems Using Artificial Intelligence","year":2021,"lang":"en","type":"article","venue":"IEEE Access","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; British Columbia Institute of Technology","funders":"University of Mumbai; British Columbia Institute of Technology; Northeastern University","keywords":"Computer science; Field (mathematics); Autonomy; Control (management); Control system; Systems engineering; Artificial intelligence; Engineering; Electrical 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":[0.0002990646,0.0001268236,0.0003056976,0.0000733966,0.00005345516,0.00004335564,0.0003274148,0.0001813476,0.00003538397],"category_scores_gemma":[0.00005631297,0.0001389796,0.00004325785,0.0003451977,0.00007396813,0.0001629657,0.00003556399,0.0001938454,0.00001802489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006378403,"about_ca_system_score_gemma":0.00008714981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004471011,"about_ca_topic_score_gemma":0.0002459511,"domain_scores_codex":[0.9990165,0.00007044432,0.0004155727,0.000173983,0.00009326362,0.0002302664],"domain_scores_gemma":[0.9993038,0.0001361524,0.00006862068,0.0003148365,0.0001376964,0.00003890071],"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":[0.00002069288,0.0000621693,0.009886732,0.0001358258,0.0001596466,0.00006623616,0.00007107092,0.9503109,0.01580646,0.004329564,0.00004928935,0.01910141],"study_design_scores_gemma":[0.00009097224,0.00001374943,0.01188671,0.00003777911,0.00002850789,0.00002348541,0.00004018705,0.8379641,0.1488804,0.0007400508,0.00006852233,0.0002255779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6611292,0.0008121913,0.3361482,0.00001638239,0.001053804,0.0001101291,0.00004777045,0.0002698571,0.0004124924],"genre_scores_gemma":[0.9997424,0.00002253014,0.0001185966,0.00001468422,0.00005380797,0.000007239973,0.000006175623,0.0000227101,0.00001184108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3386132,"threshold_uncertainty_score":0.5667422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0674397583161026,"score_gpt":0.2996011143758428,"score_spread":0.2321613560597402,"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."}}