{"id":"W2103466148","doi":"10.1109/icma.2005.1626634","title":"Using multiple view geometry within extended Kalman filter framework for simultaneous localization and map-building","year":2006,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer vision; Simultaneous localization and mapping; Extended Kalman filter; Artificial intelligence; Monocular; Novelty; Computer science; Kalman filter; Robotics; Monocular vision; Mobile robot; Structure from motion; Robot; Stereopsis; Motion (physics)","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":[0.0004245484,0.000564845,0.0007290533,0.0003804136,0.0002191748,0.0005629202,0.0007314532,0.0005824921,0.000776168],"category_scores_gemma":[0.001129337,0.0003457297,0.0006758586,0.0005975403,0.0003902346,0.001386492,0.0008173761,0.0005153092,0.0003954983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002663643,"about_ca_system_score_gemma":0.0006049566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003725059,"about_ca_topic_score_gemma":0.004048556,"domain_scores_codex":[0.9995938,0.0001143346,0.00001902371,0.00008489203,0.0001508636,0.00003705611],"domain_scores_gemma":[0.9996979,0.0001089446,0.0000427677,0.00007547769,0.000064669,0.0000101839],"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":[0.0001407517,0.00003723904,0.001207872,0.0002119178,0.0001686691,0.0003010935,0.0001721203,0.5179635,0.02914886,0.03164803,0.002382182,0.4166178],"study_design_scores_gemma":[0.00003184764,0.0001056013,0.0005897591,0.00001107657,0.00005256751,0.0001711692,0.00002226086,0.9746821,0.006645029,0.01067025,0.006986658,0.00003164425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002138424,0.0001260564,0.9970992,0.00003440372,0.00001656066,0.000004089556,0.00001066198,0.0002571612,0.0003134911],"genre_scores_gemma":[0.2849978,0.0006703315,0.7128063,0.00006089516,0.00007174246,0.00006698934,0.0001498916,0.00006797267,0.001108136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003725059,"threshold_uncertainty_score":0.007406712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01771060573663981,"score_gpt":0.2512278082434635,"score_spread":0.2335172025068236,"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."}}