{"id":"W2980723633","doi":"10.4236/pos.2019.104004","title":"Simultaneous Localization and Mapping Solutions Using Monocular and Stereo Visual Sensors with Baseline Scaling System","year":2019,"lang":"en","type":"article","venue":"Positioning","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Humber Polytechnic","funders":"","keywords":"Monocular; Simultaneous localization and mapping; Computer vision; Artificial intelligence; Computer science; Trajectory; Stereo cameras; Stereopsis; Stereo camera; Scale (ratio); Geography; Mobile robot; Robot; Physics; Cartography","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":[0.0003997024,0.0007577795,0.000615254,0.0008755049,0.0003988932,0.0007888712,0.0007097452,0.0006348453,0.002008536],"category_scores_gemma":[0.0009268196,0.0004139624,0.0004048053,0.00105171,0.000291821,0.001254545,0.001480101,0.0004971758,0.0007908948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004102314,"about_ca_system_score_gemma":0.001020343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003357073,"about_ca_topic_score_gemma":0.004351659,"domain_scores_codex":[0.9990608,0.0001085882,0.0000353094,0.0002030976,0.0004733406,0.0001190145],"domain_scores_gemma":[0.9996384,0.00002621451,0.00005329691,0.00007624468,0.0001776125,0.00002828335],"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":[0.0004869952,0.000140984,0.003254319,0.0004810442,0.0001116087,0.000282413,0.0004420204,0.04490394,0.2339976,0.006699916,0.006388456,0.7028108],"study_design_scores_gemma":[0.0002061731,0.001116758,0.01608575,0.0001207104,0.000127219,0.001111984,0.0008087243,0.7528452,0.1656002,0.01142102,0.05034202,0.0002142573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04633039,0.0007773745,0.9431875,0.0001849371,0.0002168635,0.00007726586,0.0002416778,0.003395458,0.005588531],"genre_scores_gemma":[0.6053751,0.0004239049,0.3890593,0.0001550254,0.00006560882,0.0001367261,0.0004617537,0.0001146106,0.004207976],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003357073,"threshold_uncertainty_score":0.006719172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007697140086513329,"score_gpt":0.1952717395560032,"score_spread":0.1875745994694899,"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."}}