{"id":"W2077247700","doi":"10.1007/s10846-010-9399-6","title":"Sensor Fusion for SLAM Based on Information Theory","year":2010,"lang":"en","type":"article","venue":"Journal of Intelligent & Robotic Systems","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Sensor fusion; Robustness (evolution); Artificial intelligence; Extended Kalman filter; Entropy (arrow of time); Computer science; Simultaneous localization and mapping; Robot; Fusion; Kalman filter; Covariance matrix; Covariance intersection; Covariance; Computer vision; Soft sensor; Data mining; Algorithm; Mathematics; Mobile robot","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":[0.0008157666,0.0001612134,0.0002744931,0.0003119436,0.00006123671,0.0001094023,0.0001469057,0.0001369447,0.00003029599],"category_scores_gemma":[0.000251534,0.000127013,0.0001594511,0.0001259573,0.00001722411,0.0001956223,0.00000507706,0.0002576004,0.00003732487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008321252,"about_ca_system_score_gemma":0.00003908145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000322623,"about_ca_topic_score_gemma":0.000001489505,"domain_scores_codex":[0.9985724,0.0000479032,0.0007976987,0.00006417002,0.0003306381,0.0001871806],"domain_scores_gemma":[0.9987026,0.0003163204,0.0002723605,0.000191325,0.0004082508,0.0001091025],"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":[0.00006430602,0.00003026438,0.0000627968,0.0001687937,0.00003133092,0.000002517867,0.0001315013,0.9887179,0.00251238,0.004479703,0.001022707,0.002775823],"study_design_scores_gemma":[0.000364583,0.0002365938,0.00007194333,0.0002155293,0.00003936249,0.00004105735,0.0002714215,0.9879256,0.004676914,0.0001320844,0.005878153,0.0001467469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01359478,0.00006541696,0.9792451,0.00007654978,0.005811834,0.0003539981,0.00000421401,0.00004778261,0.0008003442],"genre_scores_gemma":[0.9953868,0.00002628553,0.003833551,0.0000896392,0.0005343767,0.000006228312,0.00001424219,0.00003050408,0.00007834043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.981792,"threshold_uncertainty_score":0.5179441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0101187013543867,"score_gpt":0.2195665614672084,"score_spread":0.2094478601128217,"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."}}