{"id":"W2282557618","doi":"10.5220/0005535802670274","title":"HybridSLAM: A Robust Algorithm for Simultaneous Localization and Mapping","year":2015,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Carleton University","funders":"","keywords":"Robustness (evolution); Computer science; Algorithm; Process (computing); Fusion; Simultaneous localization and mapping; Sensor fusion; Artificial intelligence; Path (computing); Mobile robot; 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":[0.00007092839,0.00008519714,0.0000898447,0.00005175635,0.00003437151,0.00004242157,0.00002924125,0.00004531115,0.000005608426],"category_scores_gemma":[0.00004616219,0.00008383372,0.00001475754,0.00009140582,0.00001216828,0.00005809057,0.000007359351,0.0000273347,0.000005104908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000342713,"about_ca_system_score_gemma":0.000008836471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001060626,"about_ca_topic_score_gemma":0.000006082143,"domain_scores_codex":[0.9995579,0.000005974895,0.0001260178,0.0001033689,0.00007587038,0.0001309312],"domain_scores_gemma":[0.9996967,0.00004884922,0.00001105004,0.00007297822,0.00008905627,0.00008140734],"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":[0.000001150804,0.000004677342,0.00002341764,0.00002208475,0.00000784799,0.000002417102,0.00009464381,0.9625043,0.00003851132,0.0002878822,0.001589038,0.03542408],"study_design_scores_gemma":[0.0003662218,0.00002693519,0.000002731509,0.000009592353,0.000006983957,0.000006878932,0.0001249232,0.9902084,0.0003705786,0.0002732672,0.008483892,0.0001195828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001144768,0.0001190383,0.9971525,0.00002883029,0.0001608556,0.0001848411,0.00000502341,0.0002189106,0.0009852387],"genre_scores_gemma":[0.731553,0.00007117453,0.266872,0.0002296713,0.0002401313,0.00002175459,0.000139473,0.00007973226,0.0007930128],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7304083,"threshold_uncertainty_score":0.341864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02536030064920578,"score_gpt":0.2111836759703959,"score_spread":0.1858233753211901,"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."}}