{"id":"W3201588370","doi":"10.1109/lra.2022.3189165","title":"Robust Visual Teach and Repeat for UGVs Using 3D Semantic Maps","year":2022,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer vision; Computer science; Artificial intelligence; Robot; Path (computing); Orientation (vector space); Point cloud; Pose; Orb (optics); Simultaneous localization and mapping; Mobile robot; Image (mathematics); Mathematics","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":[0.0006506401,0.00192499,0.001472144,0.001441397,0.0007460695,0.001008457,0.002096408,0.001076992,0.002068424],"category_scores_gemma":[0.001684305,0.0006756258,0.001209543,0.001004687,0.0008324673,0.001525003,0.002633734,0.001721162,0.001439789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009053978,"about_ca_system_score_gemma":0.001838309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009554343,"about_ca_topic_score_gemma":0.0124105,"domain_scores_codex":[0.9991678,0.00009563027,0.00002092285,0.0002158752,0.0003187481,0.0001810334],"domain_scores_gemma":[0.9994259,0.00009303491,0.0000789461,0.0001770682,0.0001734862,0.00005163172],"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":[0.0003473226,0.0001377856,0.001619629,0.0001740126,0.0001163522,0.0001838187,0.0002915004,0.214018,0.02689572,0.007564609,0.006069095,0.7425822],"study_design_scores_gemma":[0.00005583953,0.000158337,0.001103922,0.00002454844,0.0000290942,0.0001373886,0.0002476967,0.9616258,0.01957359,0.009922886,0.007068374,0.00005244358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01990909,0.0001588928,0.9711828,0.00008144663,0.00005853705,0.0001006796,0.0001346085,0.006653835,0.001720068],"genre_scores_gemma":[0.3552904,0.0001750555,0.6387308,0.0001557928,0.00004681828,0.0002121787,0.001211115,0.0008594393,0.003318457],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009554343,"threshold_uncertainty_score":0.01899749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01952947418004371,"score_gpt":0.2235774631809574,"score_spread":0.2040479890009137,"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."}}