{"id":"W4396242229","doi":"10.3390/drones8050173","title":"VizNav: A Modular Off-Policy Deep Reinforcement Learning Framework for Vision-Based Autonomous UAV Navigation in 3D Dynamic Environments","year":2024,"lang":"en","type":"article","venue":"Drones","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reinforcement learning; Modular design; Computer science; Artificial intelligence; Computer vision; Human–computer interaction","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":[0.000369546,0.0001949092,0.0001890449,0.0002802633,0.0001297122,0.0001975661,0.0004383802,0.0001313401,0.000005704443],"category_scores_gemma":[0.000123486,0.0002004016,0.00007143824,0.0004135681,0.00003809258,0.0003219371,0.00009332057,0.0002871997,0.0001000539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004061743,"about_ca_system_score_gemma":0.0001428087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004490165,"about_ca_topic_score_gemma":8.760924e-7,"domain_scores_codex":[0.9983742,0.0000636109,0.0003308899,0.0005204555,0.0003119855,0.0003989088],"domain_scores_gemma":[0.9991392,0.0002918931,0.0000847617,0.0003930548,0.00001335421,0.00007777128],"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":[0.000004509885,0.00003015357,0.0001099335,0.00005391952,0.00001283389,0.00003655354,0.001052595,0.924567,0.0004195306,0.003148718,0.000008145339,0.07055609],"study_design_scores_gemma":[0.000243446,0.0001680439,0.001152665,0.0003679522,0.000006996694,0.0000055631,0.00002490186,0.9922377,0.0001940931,0.003683248,0.001701567,0.0002138114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008088293,0.0003900754,0.9894429,0.0009849339,0.0004368566,0.0003767603,0.000001709838,0.0002263173,0.00005211929],"genre_scores_gemma":[0.6619376,0.000009719229,0.337369,0.0001074392,0.00006901064,0.0001152305,0.00005402966,0.00002396755,0.0003140198],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6538493,"threshold_uncertainty_score":0.8172139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00849846114815495,"score_gpt":0.283281631093629,"score_spread":0.274783169945474,"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."}}