{"id":"W4221112862","doi":"10.3390/drones6040085","title":"Simultaneous Localization and Mapping (SLAM) and Data Fusion in Unmanned Aerial Vehicles: Recent Advances and Challenges","year":2022,"lang":"en","type":"article","venue":"Drones","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Simultaneous localization and mapping; Artificial intelligence; Computer vision; Odometry; Sensor fusion; Computer science; Kalman filter; Robotics; Extended Kalman filter; Search and rescue; Fuse (electrical); Photogrammetry; Object (grammar); Scalability; Robot; Mobile robot; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002625457,0.0006313668,0.001024148,0.001653519,0.0004681806,0.001995803,0.001233855,0.001261759,0.001102602],"category_scores_gemma":[0.003136328,0.0005457152,0.0006924529,0.003960173,0.001147657,0.004183753,0.00206677,0.001406209,0.0005183489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007374855,"about_ca_system_score_gemma":0.001099834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001599525,"about_ca_topic_score_gemma":0.001284546,"domain_scores_codex":[0.9981133,0.0004509955,0.0001429982,0.0003297392,0.0008461643,0.0001168019],"domain_scores_gemma":[0.9970735,0.001472919,0.0002815824,0.0002457599,0.0008408423,0.00008534172],"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":[0.00006856443,0.00007089273,0.001819976,0.002703975,0.0001092384,0.0001062172,0.0004048523,0.01920813,0.004711547,0.03264487,0.004631578,0.9335202],"study_design_scores_gemma":[0.00004144797,0.00086536,0.007557964,0.002434863,0.0002583889,0.001391183,0.003232474,0.3207114,0.02073729,0.1128202,0.5296375,0.0003118377],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01431286,0.4646408,0.5047922,0.003872875,0.0009532906,0.00008504969,0.00009241763,0.0004750173,0.01077558],"genre_scores_gemma":[0.2983724,0.4270261,0.2657724,0.001217287,0.002492004,0.0001779623,0.0004307363,0.0001490824,0.004362063],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.002625457,"threshold_uncertainty_score":0.0138849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02938577811892392,"score_gpt":0.2340428110544115,"score_spread":0.2046570329354876,"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."}}