{"id":"W2890965859","doi":"10.3390/s18092952","title":"An Autonomous Vehicle Navigation System Based on Inertial and Visual Sensors","year":2018,"lang":"en","type":"article","venue":"Sensors","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Heilongjiang Province; China Scholarship Council","keywords":"Inertial measurement unit; Inertial navigation system; Gyroscope; Navigation system; Computer science; Reliability (semiconductor); Wind triangle; Computer vision; Artificial intelligence; Inertial frame of reference; Engineering; Simulation; Robot; Mobile robot; Aerospace engineering","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":[0.0001831641,0.0004797443,0.0004855488,0.000442251,0.0003800975,0.0004355656,0.0007695258,0.0005295562,0.001144304],"category_scores_gemma":[0.0003422615,0.0002893258,0.0002403492,0.0004237224,0.0001837932,0.0006872909,0.0006328328,0.0003184036,0.0005844699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002302668,"about_ca_system_score_gemma":0.0007688884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003718614,"about_ca_topic_score_gemma":0.004725352,"domain_scores_codex":[0.9996778,0.0000256771,0.00001193665,0.00009343915,0.000163973,0.00002720095],"domain_scores_gemma":[0.9998128,0.00001799804,0.00002211864,0.00001750498,0.0001071177,0.00002245087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000367391,0.0001649149,0.006204559,0.0004943562,0.0001134683,0.0003848688,0.0002382826,0.01438367,0.3889258,0.005253559,0.00832436,0.5751448],"study_design_scores_gemma":[0.0003986597,0.00239277,0.02612586,0.0001561737,0.0004113271,0.002457373,0.0001896251,0.6352822,0.2110411,0.005204136,0.1160926,0.0002482574],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09201962,0.001715905,0.8883516,0.0002349188,0.0005446474,0.0002322909,0.0003337056,0.005335543,0.01123177],"genre_scores_gemma":[0.7701355,0.0007091015,0.2146602,0.0002539561,0.0001528409,0.0002701384,0.0005051604,0.00005219949,0.0132609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003718614,"threshold_uncertainty_score":0.007393956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004866560607590487,"score_gpt":0.2206329853136157,"score_spread":0.2157664247060252,"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."}}