{"id":"W4378220299","doi":"10.1002/asjc.3120","title":"Distributed dynamic matrix control with constrained optimization for collision and obstacle avoidance of simulated multiple quadcopters","year":2023,"lang":"en","type":"article","venue":"Asian Journal of Control","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Collision avoidance; Obstacle avoidance; Computer science; Control theory (sociology); Collision; Obstacle; Control (management); Mathematical optimization; Mathematics; Mobile robot; Robot; Artificial intelligence","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":[0.0008787657,0.0002517073,0.000765115,0.0002771625,0.0001290034,0.0001463879,0.0005511191,0.0001107063,0.000003249255],"category_scores_gemma":[0.0005751428,0.0002059876,0.0001713435,0.0006259378,0.000120276,0.000598901,0.00002588236,0.0001582042,0.000002865869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008679773,"about_ca_system_score_gemma":0.0001956245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006180796,"about_ca_topic_score_gemma":0.000005074884,"domain_scores_codex":[0.9976394,0.0002101843,0.0009910623,0.0002914123,0.0004550769,0.0004128523],"domain_scores_gemma":[0.9964566,0.0008812565,0.001239875,0.0003321902,0.0008700503,0.0002200769],"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":[0.001375894,0.00009030411,0.002509685,0.00007760821,0.0004166081,0.00007306667,0.0002549995,0.9877952,0.003775733,0.0004927845,0.0001420041,0.00299611],"study_design_scores_gemma":[0.0249271,0.0007314892,0.003264103,0.000195745,0.0001143654,0.00008136023,0.0002605655,0.9698694,0.0001581558,0.00007819675,0.0001185389,0.0002010121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04593071,0.0002065297,0.9499739,0.001992952,0.0002645976,0.001051137,0.0004896849,0.00008125998,0.000009239516],"genre_scores_gemma":[0.992286,0.000009572822,0.007528279,0.00004528698,0.00003459107,0.00001609701,0.00003703669,0.00002213051,0.00002101751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9463553,"threshold_uncertainty_score":0.8399932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005512750932837378,"score_gpt":0.2349233184506516,"score_spread":0.2294105675178142,"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."}}