{"id":"W2121601507","doi":"","title":"A fault tolerant state estimation framework with application to UGV navigation in complex terrain","year":2011,"lang":"en","type":"article","venue":"International Conference on Information Fusion","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; AUG Signals (Canada)","funders":"","keywords":"Computer science; Sensor fusion; Kinematics; Fault detection and isolation; Terrain; Asynchronous communication; Fault tolerance; State (computer science); Artificial intelligence; Real-time computing; Algorithm; Actuator; Distributed computing","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":[0.0005336031,0.0006740264,0.0007161525,0.0005225517,0.0005169311,0.0008992382,0.0008935257,0.0007153664,0.001143476],"category_scores_gemma":[0.001725012,0.0003101486,0.0004540103,0.0006260292,0.0005959558,0.0009984561,0.000872943,0.000907903,0.0003010345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005953775,"about_ca_system_score_gemma":0.000794771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009150895,"about_ca_topic_score_gemma":0.005286359,"domain_scores_codex":[0.9996868,0.00005462046,0.00001716717,0.00008117418,0.0001296861,0.00003054232],"domain_scores_gemma":[0.9996762,0.0001283054,0.000057294,0.00003740457,0.00008417249,0.00001664951],"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":[0.00003683384,0.0000203448,0.0003247952,0.00004097943,0.00002512717,0.00008138122,0.00006901671,0.8779267,0.002539185,0.03145227,0.0007657635,0.08671755],"study_design_scores_gemma":[0.000002982312,0.00001391547,0.00007094983,0.00000277401,0.000003187806,0.00001508394,0.000005681952,0.9931495,0.0004298149,0.005516523,0.0007835801,0.000006113934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001549532,0.00006801759,0.9978147,0.00003627961,0.00001041045,0.000006635511,0.00001732117,0.0001922131,0.0003047732],"genre_scores_gemma":[0.5660308,0.0005654148,0.4294084,0.00008343306,0.0001104822,0.0001530021,0.0002830256,0.0001072468,0.003258065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009150895,"threshold_uncertainty_score":0.01819527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03237048624936621,"score_gpt":0.2817280471768246,"score_spread":0.2493575609274584,"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."}}