{"id":"W2804588044","doi":"10.3390/mi9050249","title":"Motion Constraints and Vanishing Point Aided Land Vehicle Navigation","year":2018,"lang":"en","type":"article","venue":"Micromachines","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; University of Calgary","keywords":"GNSS applications; Computer science; Odometry; Computer vision; Extended Kalman filter; Heading (navigation); Artificial intelligence; Inertial navigation system; Robustness (evolution); Reference frame; Kalman filter; Precise Point Positioning; Inertial measurement unit; Frame (networking); Global Positioning System; Geodesy; Mathematics; Orientation (vector space); Geography; Robot; Mobile robot","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001912952,0.0007210445,0.0006482187,0.0005211987,0.0002488702,0.0004247935,0.0007451863,0.0003492724,0.001418791],"category_scores_gemma":[0.001066092,0.0003283716,0.0003576098,0.0006347604,0.0004964439,0.0009414738,0.0007545994,0.000522822,0.0003530054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003415522,"about_ca_system_score_gemma":0.000624406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01244885,"about_ca_topic_score_gemma":0.006949476,"domain_scores_codex":[0.9997668,0.00004424488,0.000009455553,0.00006058549,0.00009123402,0.00002772679],"domain_scores_gemma":[0.9997476,0.00008987028,0.00005936336,0.00003333268,0.00005917018,0.00001077191],"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":[0.0001101945,0.00001870271,0.0009251903,0.0001493794,0.00003657199,0.000163001,0.0001307325,0.8324094,0.01034536,0.01885277,0.001179889,0.1356787],"study_design_scores_gemma":[0.000005396937,0.00002934634,0.0003923024,0.000006861203,0.000004834738,0.00002090218,0.000008304114,0.9937612,0.001860207,0.002414865,0.001485646,0.00001013559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0137577,0.0002861017,0.9845898,0.00004132809,0.00002394338,0.00001365065,0.00006669568,0.0002845331,0.0009362928],"genre_scores_gemma":[0.8471983,0.0006545292,0.1449796,0.0000512938,0.00006555986,0.0001119562,0.0004600649,0.00015223,0.006326315],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01244885,"threshold_uncertainty_score":0.0247528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006032438093860567,"score_gpt":0.2033172677304014,"score_spread":0.1972848296365408,"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."}}