{"id":"W4206679640","doi":"10.1109/icar53236.2021.9659458","title":"RPV-SLAM: Range-augmented Panoramic Visual SLAM for Mobile Mapping System with Panoramic Camera and Tilted LiDAR","year":2021,"lang":"en","type":"article","venue":"2021 20th International Conference on Advanced Robotics (ICAR)","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Optech (Canada); York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Simultaneous localization and mapping; Lidar; Computer vision; Artificial intelligence; Computer science; Robustness (evolution); Global Positioning System; Inertial measurement unit; Visualization; Mobile robot; Remote sensing; Geography; Robot","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003055749,0.0006289353,0.0006463606,0.0005941899,0.0003625531,0.0006493163,0.001184352,0.0006624827,0.004081211],"category_scores_gemma":[0.0005906153,0.0003817877,0.0004568857,0.0006126366,0.0002669618,0.000973005,0.001575639,0.0006675619,0.001855325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002802201,"about_ca_system_score_gemma":0.000822337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002528183,"about_ca_topic_score_gemma":0.002372165,"domain_scores_codex":[0.999581,0.00004926173,0.00002281647,0.00009439774,0.0001845868,0.00006792201],"domain_scores_gemma":[0.9998268,0.00001242322,0.00001896631,0.00005831014,0.00006648497,0.00001704737],"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":[0.000382747,0.0001556766,0.002058493,0.0004762115,0.0001074715,0.0004830451,0.0002205461,0.04658546,0.1320804,0.006211156,0.0213518,0.789887],"study_design_scores_gemma":[0.0002218402,0.0007035524,0.005158568,0.00006886544,0.00006882565,0.001062932,0.000129073,0.8418362,0.07621425,0.00434758,0.07007357,0.0001147069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02326629,0.0005865987,0.956355,0.0001342653,0.0001795523,0.0001483901,0.0003469819,0.01345723,0.005525602],"genre_scores_gemma":[0.5865074,0.0004500548,0.4018308,0.0002937547,0.00009295948,0.0003609528,0.001801899,0.0003882284,0.008273927],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004081211,"threshold_uncertainty_score":0.01365304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01614371442149937,"score_gpt":0.2508958642812701,"score_spread":0.2347521498597708,"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."}}