{"id":"W4238925767","doi":"10.32920/ryerson.14668500","title":"Real time autonomous collision avoidance for unmanned aerial vehicles","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Guidance and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Trajectory; Terrain; Obstacle; Computer science; Trajectory optimization; Obstacle avoidance; Collision avoidance; Flight planning; Aerospace engineering; Control theory (sociology); Control (management); Collision; Engineering; Artificial intelligence; Robot; Mobile robot; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001902656,0.0003254811,0.000232322,0.0001934606,0.0002848901,0.000457079,0.0004005042,0.0002600751,0.0007955359],"category_scores_gemma":[0.0005832176,0.0001705832,0.000228366,0.0001378856,0.0003280387,0.0003757499,0.0004665909,0.0003612142,0.0001400193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002394836,"about_ca_system_score_gemma":0.0004043639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002614436,"about_ca_topic_score_gemma":0.001997911,"domain_scores_codex":[0.9998735,0.00002820369,0.000004090966,0.00002154625,0.00005608053,0.00001661444],"domain_scores_gemma":[0.9998274,0.0000779879,0.0000326854,0.00001428565,0.00003573517,0.00001190839],"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":[0.00007989644,0.00003428715,0.0004832737,0.00008168122,0.00002212187,0.00009069976,0.00020126,0.8938427,0.01797576,0.01213369,0.0007888772,0.07426577],"study_design_scores_gemma":[0.000005187716,0.00004198363,0.0001102484,0.000003530354,0.000001691751,0.00001037942,0.00001812747,0.9967201,0.00101706,0.001369285,0.0006995601,0.000002716022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09245028,0.0003876412,0.9023753,0.0000745704,0.00005647237,0.00005350578,0.00001899384,0.0003586299,0.004224615],"genre_scores_gemma":[0.8772138,0.000242167,0.1176477,0.00003195538,0.00002184228,0.0001059982,0.0000449384,0.00004350697,0.004648123],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002614436,"threshold_uncertainty_score":0.005198419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009259748121594897,"score_gpt":0.2177712203547376,"score_spread":0.2085114722331427,"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."}}