{"id":"W2149803537","doi":"10.1109/ccece.2009.5090208","title":"Non-time based motion control for multiple intelligent vehicles","year":2009,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Automation; Computer science; Control engineering; Controller (irrigation); Motion control; Intelligent control; Robot; Tracking (education); Mobile robot; Control (management); Motion (physics); Robot control; Track (disk drive); Robot kinematics; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000340885,0.0004683372,0.0002837386,0.0002545524,0.0003599361,0.0004965996,0.000788489,0.000362267,0.0009373932],"category_scores_gemma":[0.000677942,0.000140178,0.0002985599,0.0001640956,0.0004107843,0.0005467547,0.0004111748,0.0004334197,0.0001821277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004210419,"about_ca_system_score_gemma":0.000444035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001503335,"about_ca_topic_score_gemma":0.001498255,"domain_scores_codex":[0.9996226,0.00006468521,0.00002031706,0.00008315319,0.0001752516,0.00003399792],"domain_scores_gemma":[0.9996399,0.00008697768,0.0001020085,0.00003570456,0.000111148,0.0000242717],"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":[0.0003166637,0.0001250258,0.0009730405,0.0002719901,0.0001001559,0.0004040076,0.0002840936,0.5866396,0.07978894,0.05874103,0.001823485,0.270532],"study_design_scores_gemma":[0.00003664362,0.0002176651,0.0002785522,0.000007881852,0.00001882855,0.00008909221,0.00001596207,0.9837047,0.006360918,0.004167445,0.005091227,0.00001114682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01491043,0.0002809004,0.9823449,0.00007485953,0.0001074114,0.00002460621,0.0000068777,0.0002241202,0.002025827],"genre_scores_gemma":[0.889523,0.0003486501,0.103331,0.00009814695,0.0000686282,0.0001212833,0.00005055035,0.00003089586,0.006427764],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001503335,"threshold_uncertainty_score":0.00313592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0168023028529482,"score_gpt":0.2465078576173534,"score_spread":0.2297055547644052,"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."}}