{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005130146,0.0005993808,0.0006369186,0.0003182674,0.0004397901,0.0005023623,0.000585341,0.0004030975,0.001117948],"category_scores_gemma":[0.0009783016,0.0002268123,0.0003328381,0.0002071439,0.0004907206,0.0003115388,0.0009175565,0.0005162263,0.00009223985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005038314,"about_ca_system_score_gemma":0.0006588695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006193377,"about_ca_topic_score_gemma":0.003110992,"domain_scores_codex":[0.9997564,0.0000702088,0.000008836337,0.00005202192,0.00005934198,0.00005323822],"domain_scores_gemma":[0.999393,0.0002530137,0.0001246468,0.00004144092,0.0001337686,0.0000540919],"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":[0.00005945134,0.00002706511,0.0002601953,0.00002103232,0.00001403022,0.00005339847,0.00003121515,0.9884384,0.003558272,0.001432684,0.0001096687,0.005994521],"study_design_scores_gemma":[0.000006201072,0.0000400752,0.00005535168,8.267417e-7,0.000001468739,0.00000327857,0.000005244739,0.9992813,0.0002967506,0.0002446345,0.00006339853,0.000001438777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2709755,0.00017824,0.7239848,0.0001992556,0.0000523257,0.00008404169,0.00002933185,0.000227716,0.004268801],"genre_scores_gemma":[0.9900162,0.00002275849,0.009364329,0.00001242415,0.000003699901,0.00003628544,0.000009216005,0.000005454989,0.0005296516],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006193377,"threshold_uncertainty_score":0.01231462,"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."}}