{"id":"W2138044639","doi":"10.1080/00207170412331317738","title":"Autonomous mobile robot model predictive control","year":2004,"lang":"en","type":"article","venue":"International Journal of Control","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Model predictive control; Control theory (sociology); Linearization; Mobile robot; Slippage; Smoothness; Inclined plane; Controller (irrigation); Obstacle avoidance; Motion planning; Control engineering; Engineering; Collision avoidance; Computer science; Simulation; Robot; Control (management); Artificial intelligence; Mathematics; Nonlinear system; Collision","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":[0.0001471039,0.0005263296,0.0006006386,0.0001523578,0.0002660686,0.0005819405,0.0006799378,0.0005327716,0.001463578],"category_scores_gemma":[0.0003327974,0.0001625506,0.0002728691,0.0002818658,0.000349301,0.0004023709,0.0004606257,0.0007479339,0.000475458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002122922,"about_ca_system_score_gemma":0.0003581195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002123807,"about_ca_topic_score_gemma":0.00146584,"domain_scores_codex":[0.9998331,0.00002901455,0.000004413426,0.00002770448,0.0000914884,0.00001425297],"domain_scores_gemma":[0.9999037,0.00002714713,0.00001290177,0.0000170295,0.00003310581,0.000006173397],"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":[0.00008860179,0.00006620095,0.0004079053,0.0003174038,0.00006179659,0.0002727449,0.0001181983,0.7661707,0.01937292,0.02798246,0.004674406,0.1804666],"study_design_scores_gemma":[0.00001368502,0.00009418824,0.0001384665,0.00001138958,0.00001166326,0.00004930319,0.00001002586,0.9825726,0.002788807,0.005373603,0.008927404,0.000008847739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01147409,0.001884048,0.9737829,0.0002362667,0.0002086837,0.00005260147,0.00005797921,0.001773096,0.01053031],"genre_scores_gemma":[0.8811253,0.002154709,0.1030486,0.0002109464,0.0001686949,0.0002380915,0.0002413126,0.00008727628,0.01272508],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002123807,"threshold_uncertainty_score":0.004896224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003324102189327507,"score_gpt":0.2093508354529938,"score_spread":0.2060267332636663,"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."}}