{"id":"W3025490466","doi":"10.3390/rs12101564","title":"Navigation Engine Design for Automated Driving Using INS/GNSS/3D LiDAR-SLAM and Integrity Assessment","year":2020,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Ministry of Science and Technology","keywords":"Lidar; GNSS applications; Computer science; Simultaneous localization and mapping; Odometry; Odometer; Robustness (evolution); Sensor fusion; Inertial navigation system; Inertial measurement unit; Global Positioning System; Satellite system; Ranging; Artificial intelligence; Real-time computing; Computer vision; Remote sensing; Robot; Mobile robot; Inertial frame of reference; Geography","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":[0.0003999435,0.0005540739,0.0004497225,0.0005398657,0.0004043897,0.0006328826,0.0008233904,0.0005614127,0.001781709],"category_scores_gemma":[0.0005581354,0.00034289,0.0004815131,0.0002246596,0.0001671861,0.0007234332,0.0006101822,0.0004107225,0.0008368551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003225419,"about_ca_system_score_gemma":0.001100276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003331983,"about_ca_topic_score_gemma":0.003144721,"domain_scores_codex":[0.999554,0.00003137596,0.00002691602,0.00007088181,0.0002719301,0.00004489973],"domain_scores_gemma":[0.9997209,0.00002220499,0.00003708772,0.0000252649,0.000178476,0.00001610225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003330339,0.0001788716,0.006285325,0.0003704471,0.0001461201,0.0003242478,0.0002482659,0.3123839,0.2404172,0.00814487,0.002965225,0.4282026],"study_design_scores_gemma":[0.00004572474,0.0003447529,0.002541134,0.00001517148,0.00006960385,0.0001791829,0.00004312019,0.9544235,0.0322683,0.001028438,0.009008003,0.00003311649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02594292,0.0001412897,0.9688881,0.00007129212,0.00005138232,0.0001001748,0.0000413428,0.001418895,0.003344532],"genre_scores_gemma":[0.7811397,0.0001679562,0.2136041,0.0000776239,0.00003039384,0.0001594063,0.0002006577,0.0001081332,0.004512184],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003331983,"threshold_uncertainty_score":0.006625175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03994417171798145,"score_gpt":0.2792352074873567,"score_spread":0.2392910357693752,"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."}}