{"id":"W2081493644","doi":"10.1163/156855307781035664","title":"An evolutionary algorithm for simultaneous localization and mapping (SLAM) of mobile robots","year":2007,"lang":"en","type":"article","venue":"Advanced Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland","keywords":"Simultaneous localization and mapping; Robustness (evolution); Robot; Computer science; Heuristics; Mobile robot; Artificial intelligence; Algorithm; Evolutionary algorithm; Computer vision; Genetic algorithm; Machine learning","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":[0.0006361906,0.0005801728,0.0006611985,0.0005985977,0.000550767,0.0004762216,0.0008522795,0.0009866458,0.001066925],"category_scores_gemma":[0.001948406,0.000334314,0.0005121307,0.0006569861,0.000524212,0.0008021318,0.0008786966,0.0008656486,0.0002302535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003590908,"about_ca_system_score_gemma":0.0006559998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001576488,"about_ca_topic_score_gemma":0.001680989,"domain_scores_codex":[0.9996362,0.00008588751,0.00001888815,0.00007671129,0.0001469024,0.00003534642],"domain_scores_gemma":[0.999681,0.0001706091,0.00003001895,0.00003006055,0.00007055077,0.00001782508],"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":[0.0000714351,0.0001014946,0.001030787,0.00009904926,0.00008450272,0.0001532133,0.0001951595,0.5210747,0.009423234,0.02551993,0.001804215,0.4404424],"study_design_scores_gemma":[0.00002910057,0.00006075865,0.0001952666,0.000008509405,0.00001442755,0.00007576319,0.00001737398,0.9891501,0.001372865,0.005988174,0.003078244,0.000009434426],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005901623,0.0000973362,0.9929294,0.00005967091,0.00003009262,0.00002018016,0.000008984713,0.0001458733,0.0008069183],"genre_scores_gemma":[0.14423,0.000153317,0.8531597,0.00006406863,0.00002990724,0.0001780745,0.0000615715,0.00005447939,0.002068887],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001576488,"threshold_uncertainty_score":0.003569186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006765387331309362,"score_gpt":0.2361221896195198,"score_spread":0.2293568022882104,"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."}}