{"id":"W3159907955","doi":"10.1109/crv52889.2021.00014","title":"Lidar Scan Registration Robust to Extreme Motions","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Iterative closest point; Robustness (evolution); Point cloud; Computer science; Computer vision; Odometry; Lidar; Artificial intelligence; Algorithm; Translation (biology); Robot; Mobile robot; Remote sensing; Geography","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":[0.001186688,0.0008137127,0.0008823327,0.001201547,0.0005648798,0.001118884,0.001034037,0.0009243931,0.001237588],"category_scores_gemma":[0.006479128,0.0006757363,0.0006252486,0.001630149,0.0008952266,0.00112441,0.002096422,0.0009228455,0.001276562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003959538,"about_ca_system_score_gemma":0.001183151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002670349,"about_ca_topic_score_gemma":0.002912505,"domain_scores_codex":[0.9973183,0.0003988915,0.0001047941,0.000529723,0.00145574,0.0001926472],"domain_scores_gemma":[0.9974412,0.0004553391,0.0003546144,0.001004188,0.0006781027,0.00006657468],"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":[0.0004541028,0.0000999356,0.006869603,0.00014595,0.0001432436,0.000419489,0.0003133341,0.4096101,0.1558343,0.004179757,0.004056048,0.4178741],"study_design_scores_gemma":[0.00003759223,0.0001362742,0.008558908,0.00001980193,0.0000341403,0.0007634097,0.0001521658,0.8928085,0.08850728,0.00385381,0.005049414,0.00007860963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1662638,0.0002907721,0.8237005,0.0002616142,0.00009933903,0.00008429082,0.000210455,0.004991764,0.004097431],"genre_scores_gemma":[0.736648,0.0002111851,0.2577547,0.0001374986,0.00005007258,0.00009946429,0.0007105475,0.0007015133,0.003687065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002670349,"threshold_uncertainty_score":0.006275833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04903984220823086,"score_gpt":0.2251147362953851,"score_spread":0.1760748940871543,"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."}}