{"id":"W4386453623","doi":"10.1109/access.2023.3312062","title":"A Robust Keyframe-Based Visual SLAM for RGB-D Cameras in Challenging Scenarios","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Artificial intelligence; Computer science; RGB color model; Computer vision; Simultaneous localization and mapping; Bundle adjustment; Benchmark (surveying); Visual odometry; Robot; Image (mathematics); Mobile robot","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000138389,0.0001569822,0.0001850701,0.0003203666,0.00006542969,0.0001101517,0.0001937351,0.000111255,0.00001787638],"category_scores_gemma":[0.00003886834,0.0001722763,0.00005768245,0.0004845792,0.00001468468,0.0001653672,0.00001461663,0.0001286369,0.00003026083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007653502,"about_ca_system_score_gemma":0.00002524398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008298737,"about_ca_topic_score_gemma":0.0001410552,"domain_scores_codex":[0.9990408,0.00001543575,0.0002371135,0.0002081433,0.0001259605,0.0003725707],"domain_scores_gemma":[0.9995869,0.0001204129,0.00002610058,0.0001589374,0.0000476386,0.00006000088],"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":[0.000009903187,0.00002132998,0.0007605635,0.0001748305,0.00001112072,0.00001080452,0.00009000966,0.9937676,0.0007948483,0.00005305956,0.002992167,0.0013138],"study_design_scores_gemma":[0.0006352784,0.00002387654,0.0008446052,0.000092302,0.000007805254,4.186075e-7,0.00002999189,0.9924206,0.004222535,0.0000533751,0.001455615,0.0002135723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4347001,0.0002630558,0.56207,0.0003699062,0.001089798,0.0005728572,0.00001385638,0.0007542526,0.0001662353],"genre_scores_gemma":[0.9988486,0.00008280942,0.0003471723,0.0002887523,0.0001659204,0.00008899337,0.0000576217,0.00007307928,0.00004706919],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5641485,"threshold_uncertainty_score":0.7025222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06123051471271258,"score_gpt":0.2992148280745933,"score_spread":0.2379843133618807,"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."}}