{"id":"W2783352722","doi":"10.1109/iris.2017.8250138","title":"Consistent multirobot localization using heuristically tuned extended Kalman filter","year":2017,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Kalman filter; Probabilistic logic; Computer science; Consistency (knowledge bases); Extended Kalman filter; Interdependence; Simultaneous localization and mapping; Robot; Artificial intelligence; Filter (signal processing); Mobile robot; Computer vision","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":[0.0007799976,0.0005544088,0.000903467,0.0003808785,0.0004625632,0.000587162,0.0009903371,0.0007374195,0.0005939849],"category_scores_gemma":[0.002241225,0.0003763337,0.0004114147,0.0004142972,0.0005951424,0.0008717917,0.0009282964,0.0006281317,0.0002141837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005243871,"about_ca_system_score_gemma":0.0008039131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003488854,"about_ca_topic_score_gemma":0.003581784,"domain_scores_codex":[0.999356,0.0001675986,0.00003509457,0.0001618886,0.0002097569,0.00006956862],"domain_scores_gemma":[0.9993318,0.0002729753,0.0001302303,0.0001271009,0.0001104832,0.00002748951],"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":[0.00007993595,0.00002652055,0.000533128,0.00003397139,0.00003803566,0.0001021461,0.00007581049,0.9308636,0.008955515,0.004227003,0.0004922452,0.05457202],"study_design_scores_gemma":[0.00001948386,0.00003239198,0.00017833,0.000003326055,0.000009569137,0.00002781222,0.00000917792,0.9956011,0.001664432,0.002003713,0.0004404248,0.00001026313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007289979,0.00004848072,0.9918765,0.00002342375,0.00001137094,0.00001316443,0.000006587818,0.0002996796,0.0004307869],"genre_scores_gemma":[0.7931477,0.00008602033,0.2056182,0.00006093115,0.00002393439,0.00007687361,0.00004917838,0.00004636848,0.000890727],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003488854,"threshold_uncertainty_score":0.006937146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03505667857566544,"score_gpt":0.2618054551430305,"score_spread":0.2267487765673651,"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."}}