{"id":"W1970881414","doi":"10.1109/icar.2013.6766521","title":"Pseudo-linear measurement approach for heterogeneous multi-robot relative localization","year":2013,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Memorial University of Newfoundland","keywords":"Initialization; Extended Kalman filter; Robot; Computer science; Kalman filter; Filter (signal processing); Nonlinear system; Monte Carlo method; Computer vision; Control theory (sociology); Frame (networking); Artificial intelligence; Algorithm; Mathematics","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":[0.0004763312,0.0005597472,0.0004005544,0.0005640927,0.0002903205,0.0004885982,0.0008770896,0.0005330693,0.001268308],"category_scores_gemma":[0.001365696,0.0002488175,0.0004428139,0.0006182867,0.0005883732,0.001108798,0.0009209175,0.0006586133,0.0005887948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003216683,"about_ca_system_score_gemma":0.0005090577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001344255,"about_ca_topic_score_gemma":0.001363392,"domain_scores_codex":[0.9993944,0.0001941421,0.00002697036,0.0001068657,0.0002478949,0.00002968556],"domain_scores_gemma":[0.9995015,0.0001861319,0.00009722891,0.00008867597,0.0001117092,0.0000147072],"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":[0.0002014643,0.00008100478,0.00173766,0.0003769685,0.00009571376,0.0003575032,0.0003500046,0.4760002,0.06216064,0.02814884,0.001584917,0.4289051],"study_design_scores_gemma":[0.0000145627,0.0001442963,0.0005189886,0.00001087529,0.00001539508,0.000177438,0.00003130005,0.9811168,0.01163835,0.002990462,0.003316015,0.00002566655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002862415,0.00009705392,0.9962088,0.00003429082,0.00001934226,0.00001248341,0.000006177915,0.0002093707,0.0005500598],"genre_scores_gemma":[0.5623856,0.0003692805,0.4336766,0.0001229483,0.00006824452,0.0001426245,0.00009434978,0.00007430791,0.003065998],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001344255,"threshold_uncertainty_score":0.004242897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0456408313760546,"score_gpt":0.2283173728730253,"score_spread":0.1826765414969707,"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."}}