{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000777406,0.0009183629,0.0006788077,0.001502322,0.0003859526,0.001934342,0.001354079,0.001355477,0.002437254],"category_scores_gemma":[0.001369792,0.0006342034,0.0006560799,0.002182029,0.0008785923,0.002651334,0.00168252,0.002046538,0.001486707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001066506,"about_ca_system_score_gemma":0.001279549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004276756,"about_ca_topic_score_gemma":0.002509783,"domain_scores_codex":[0.9993995,0.00009843856,0.00004407763,0.000141506,0.0002569733,0.00005943615],"domain_scores_gemma":[0.9995055,0.0001467094,0.00004285327,0.0000637373,0.0002012842,0.00003988384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008258372,0.00007855852,0.001180937,0.001097657,0.0001014546,0.0001087299,0.000128591,0.03297982,0.005441987,0.04952713,0.01449311,0.8947793],"study_design_scores_gemma":[0.00005117026,0.0003198007,0.003020624,0.001016819,0.0001288385,0.0008062183,0.0002100101,0.4553284,0.01635766,0.1763594,0.3462184,0.000182714],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.002392024,0.05261573,0.931216,0.001518125,0.000538513,0.00007093247,0.0002026999,0.001084878,0.01036104],"genre_scores_gemma":[0.1730426,0.1299918,0.6706997,0.002327454,0.002103327,0.0004160278,0.001394478,0.0006234743,0.01940098],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004276756,"threshold_uncertainty_score":0.008503735,"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."}}