{"id":"W4389682523","doi":"10.23977/acss.2023.071011","title":"Overview of Visual SLAM Technology: From Traditional to Deep Learning Methods","year":2023,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Simultaneous localization and mapping; Artificial intelligence; Field (mathematics); Computer science; Robot; Mobile robot; Computer vision; Robotics; Deep learning; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002136076,0.00009190541,0.0002426757,0.0002090296,0.00002597787,0.0000210762,0.00006821168,0.00006163454,0.000003950668],"category_scores_gemma":[0.00001126958,0.00009022024,0.00002194265,0.000386628,0.00001621931,0.00008425894,0.00002276047,0.00008143874,0.000004597819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001398927,"about_ca_system_score_gemma":0.000003174742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001096578,"about_ca_topic_score_gemma":0.000005360737,"domain_scores_codex":[0.9992833,0.00006892128,0.0002738779,0.0001479839,0.00009898129,0.0001269909],"domain_scores_gemma":[0.9996167,0.0002196144,0.00003397859,0.00006874035,0.00002847435,0.00003246059],"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":[0.000001458649,0.00000629385,0.0007726137,0.0001106099,0.0000120605,0.000003768796,0.0001285098,0.913567,0.001454192,0.001321253,0.00002040702,0.08260184],"study_design_scores_gemma":[0.0001288412,0.00007059558,0.000680968,0.000240515,0.000003501019,0.000001817135,0.00005551052,0.9940723,0.0005782518,0.001210653,0.002854383,0.0001026445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06453556,0.01165088,0.9229657,0.00002204585,0.000517061,0.0001134146,0.000005121972,0.0001357902,0.00005439919],"genre_scores_gemma":[0.9687533,0.001652536,0.02936684,0.00001796016,0.0001382642,0.00001940621,0.00002597797,0.00001861695,0.000007082084],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9042178,"threshold_uncertainty_score":0.3679075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04190430055431723,"score_gpt":0.3261015575190513,"score_spread":0.2841972569647341,"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."}}