{"id":"W4385059443","doi":"10.1109/aset56582.2023.10180627","title":"Control of Mobile Robots for Collision Avoidance","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Holonomic; Mobile robot; Robot; Model predictive control; Traverse; Collision avoidance; Computer science; Variety (cybernetics); Control (management); Robot control; Control engineering; Artificial intelligence; Collision; Engineering; Computer security","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":[0.00008728878,0.00005999712,0.0001470021,0.00005065531,0.00001817465,0.000004500911,0.00005359068,0.00003667556,0.000006987962],"category_scores_gemma":[0.00003456192,0.00005726767,0.00003482219,0.0001754341,0.000006069649,0.0000774584,0.000004440328,0.00002029302,0.00002140454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000213574,"about_ca_system_score_gemma":0.000004222055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002559539,"about_ca_topic_score_gemma":0.000003587486,"domain_scores_codex":[0.9995583,0.000005710188,0.0001771043,0.00007409876,0.00006346574,0.0001213651],"domain_scores_gemma":[0.9996601,0.0001238129,0.0000256927,0.0001132016,0.00005612331,0.00002112353],"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":[0.000008174576,0.000002334506,0.00003037546,0.00004775603,0.00001060274,1.614e-7,0.00002021396,0.9734272,0.02397399,0.0007021985,0.0006998702,0.001077109],"study_design_scores_gemma":[0.000853994,0.00003131063,0.00006952658,0.00001607594,0.000005000416,2.495366e-7,0.00002548882,0.9886329,0.007977007,0.0001506801,0.002173878,0.00006393318],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008007823,0.0001342456,0.9896875,0.00001413116,0.0002165109,0.0006551846,0.00002095253,0.0004638347,0.0007998426],"genre_scores_gemma":[0.9938539,0.00001839973,0.005109824,0.000008163167,0.0000393754,0.0003238698,0.000009717751,0.00002312579,0.0006135934],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9858461,"threshold_uncertainty_score":0.2335308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005919580328519398,"score_gpt":0.2233819162586205,"score_spread":0.2174623359301011,"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."}}