{"id":"W2161029404","doi":"","title":"A practical approach to control and self-localization of an omni-directional mobile robot","year":2008,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Odometry; Mobile robot; Robot; Computer science; Artificial intelligence; Orientation (vector space); Position (finance); Computer vision; Soccer robot; Control (management); Control engineering; Robot control; Control theory (sociology); Engineering; Mathematics","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":[0.00007029199,0.00008490356,0.0001275601,0.00007005047,0.00005064298,0.00001151651,0.00002589252,0.00006409224,0.00001686956],"category_scores_gemma":[0.00002097375,0.00008126126,0.00001774565,0.0001535632,0.00001951011,0.0001172046,0.000005434432,0.00004760888,0.000003978321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002356708,"about_ca_system_score_gemma":0.00001709755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000232629,"about_ca_topic_score_gemma":0.000004115831,"domain_scores_codex":[0.9994313,0.00002700335,0.0001660831,0.000128991,0.0001395955,0.0001070815],"domain_scores_gemma":[0.9996791,0.00003529925,0.00001629616,0.00009734194,0.00007326803,0.00009862713],"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":[0.00001047957,0.0001668427,0.0003376687,0.00002267952,0.00002033841,0.000001195369,0.0001577924,0.9962376,0.001073641,0.001249426,0.0005260169,0.000196322],"study_design_scores_gemma":[0.0003606676,0.00009468603,0.0007826526,0.000002667222,0.00001336698,0.00004345043,0.00004291288,0.9954148,0.002154893,0.0000185451,0.0009716577,0.00009968092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03775116,0.00001972595,0.9582776,0.00001922156,0.00005467593,0.0002336765,0.000003015032,0.0001982406,0.003442701],"genre_scores_gemma":[0.9252613,0.0000249627,0.07449683,0.00007542362,0.00004463995,0.00002179887,0.0000197007,0.00001805109,0.00003734897],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8875101,"threshold_uncertainty_score":0.3313738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01369302494915145,"score_gpt":0.2305144501251497,"score_spread":0.2168214251759982,"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."}}