{"id":"W2073158407","doi":"10.2514/6.2010-8425","title":"Safe Path Planning in the Presence of Large Communication Delays Using Tube Model Predictive Control","year":2010,"lang":"en","type":"article","venue":"AIAA Guidance, Navigation, and Control Conference","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Model predictive control; Computer science; Control (management); Path (computing); Motion planning; Control theory (sociology); Tube (container); Engineering; Computer network; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007536695,0.00021449,0.0003569107,0.00008943932,0.0001722801,0.00006281753,0.0003813917,0.0001522191,0.000003087774],"category_scores_gemma":[0.0001463383,0.0001894486,0.00004009002,0.0002422889,0.0001383945,0.0005165147,0.00002254507,0.0004117747,7.715969e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000357818,"about_ca_system_score_gemma":0.00007844029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005154012,"about_ca_topic_score_gemma":0.00004634104,"domain_scores_codex":[0.998472,0.0001643035,0.000604441,0.0002329819,0.0002358297,0.0002904216],"domain_scores_gemma":[0.9985145,0.000363664,0.0002101752,0.000494053,0.0003696507,0.00004793227],"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":[0.00008289695,0.00003317334,0.01569104,0.00006645295,0.00004937034,0.000001463506,0.002090639,0.9209386,0.03960597,0.02090568,0.0000296573,0.0005050697],"study_design_scores_gemma":[0.002713215,0.00002525193,0.009005289,0.0002793327,0.00004698728,0.00000608319,0.0004117199,0.9831667,0.0001618931,0.003930632,0.00008447558,0.0001684064],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.232687,0.001051335,0.7643173,0.00007225364,0.00009641398,0.000692789,0.00007108753,0.00006161734,0.0009501478],"genre_scores_gemma":[0.9968726,0.00005936246,0.002715571,0.0000970979,0.00003764629,0.0001617045,0.00002498621,0.00002279876,0.000008234064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7641855,"threshold_uncertainty_score":0.7725489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01022996016647421,"score_gpt":0.2466899399133905,"score_spread":0.2364599797469163,"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."}}