{"id":"W4400971924","doi":"10.2316/j.2024.206-1045","title":"SIMULTANEOUS LOCALISATION AND MAPPING (SLAM) TECHNIQUE IN REAL TIME: AN INTRODUCTION OF DIK-SLAM, 490-503.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Simultaneous localization and mapping; Computer science; Artificial intelligence; Robot; Mobile robot","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":[0.0008874231,0.0007698422,0.0006905938,0.001954834,0.0003472766,0.001552137,0.001271322,0.001180984,0.005483018],"category_scores_gemma":[0.001214481,0.0007020961,0.0006581794,0.003352951,0.001062563,0.002487394,0.001029768,0.001546076,0.006897335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005724036,"about_ca_system_score_gemma":0.0006383738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001639211,"about_ca_topic_score_gemma":0.001997599,"domain_scores_codex":[0.9991703,0.0001014218,0.00006887968,0.0001915709,0.0004204321,0.00004738932],"domain_scores_gemma":[0.9995053,0.0001190606,0.00002657987,0.00008948831,0.0002387475,0.00002077357],"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":[0.00006751509,0.00005084418,0.000528434,0.0006699215,0.00005690413,0.0001549977,0.0001051532,0.008056703,0.02255784,0.02542535,0.01937745,0.9229488],"study_design_scores_gemma":[0.00002447032,0.0002714056,0.002621397,0.0004284323,0.00007610072,0.002567972,0.0001864289,0.09997823,0.02927559,0.04485343,0.8195215,0.0001950809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001328406,0.02443692,0.9580222,0.0004918101,0.001294166,0.00005013942,0.0001751741,0.001579654,0.01262155],"genre_scores_gemma":[0.03964947,0.05094243,0.861299,0.0006132191,0.001695124,0.0001242086,0.001089823,0.0006546635,0.04393205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005483018,"threshold_uncertainty_score":0.01834255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006572418939268274,"score_gpt":0.2335330161741303,"score_spread":0.226960597234862,"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."}}