{"id":"W2157044659","doi":"10.1109/robot.2000.844838","title":"3D motion tracking of a mobile robot in a natural environment","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; Trajectory; Mobile robot; Kalman filter; Tracking (education); Representation (politics); Extended Kalman filter; Motion (physics); Robot; Motion estimation; Tracking system","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":[0.0000554641,0.00004451972,0.00006568183,0.00005838681,0.0000152424,0.00001398654,0.0001591577,0.00001054439,0.0001396737],"category_scores_gemma":[0.000005991018,0.00003797709,0.00001973936,0.0001060007,0.00001252199,0.0003854996,0.00006738217,0.00005924391,0.00002987827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002572528,"about_ca_system_score_gemma":0.000001124768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006331944,"about_ca_topic_score_gemma":0.000001223208,"domain_scores_codex":[0.9995112,0.00001368107,0.000125565,0.0001416058,0.0001074989,0.0001004448],"domain_scores_gemma":[0.9997711,0.00001577983,0.00003084302,0.0001587344,0.000005345959,0.00001819689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[4.005836e-7,0.00006479869,0.0002573292,0.000002489565,6.991138e-7,0.000002654204,0.0004854471,0.006498675,0.006276746,0.0004866205,0.00002510268,0.985899],"study_design_scores_gemma":[0.0001752354,0.00002077353,0.002870689,0.000010578,3.129286e-7,0.000003527672,0.00003087595,0.9901189,0.005967663,0.0001676107,0.0005804498,0.00005333728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007564093,0.0002939928,0.9900841,0.0001538761,0.00006265605,0.00007310758,7.103763e-8,0.00003043536,0.001737665],"genre_scores_gemma":[0.8554324,0.00002296457,0.1441562,0.00008769077,0.000004614106,0.000003546978,1.13685e-7,0.000001775679,0.0002906688],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9858457,"threshold_uncertainty_score":0.1548661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.016178660917099,"score_gpt":0.241896139146871,"score_spread":0.225717478229772,"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."}}