{"id":"W2923018352","doi":"10.1109/iros40897.2019.8968150","title":"Computing a Minimal Set of t-Spanning Motion Primitives for Lattice Planners","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Integer programming; Motion planning; Heuristics; Lattice (music); Integer lattice; Configuration space; Mathematics; Computer science; Algorithm; Linear programming; Tree traversal; Discrete mathematics; Theoretical computer science; Combinatorics; Topology (electrical circuits); Mathematical optimization; Robot; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008184353,0.0003241369,0.0005816317,0.0002400896,0.00007646628,0.0001412979,0.00135603,0.0002905394,0.000002036508],"category_scores_gemma":[0.0002109829,0.0003212787,0.0001928236,0.0001542647,0.00005355199,0.0001949672,0.00145393,0.0004041527,0.00001373508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006970223,"about_ca_system_score_gemma":0.0002192272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005470836,"about_ca_topic_score_gemma":3.473835e-7,"domain_scores_codex":[0.9976426,0.0001085424,0.0005619838,0.0008692956,0.0003808102,0.0004368105],"domain_scores_gemma":[0.9974548,0.0008055614,0.000618899,0.0007920092,0.0002464541,0.00008226568],"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":[0.00005638436,0.0001522139,0.005893242,0.002508633,0.0004442999,0.00002922275,0.01795776,0.906262,0.00054267,0.02157436,0.003075985,0.04150323],"study_design_scores_gemma":[0.0003956696,0.0001174473,0.004887831,0.0005420584,0.00002993936,0.00001271837,0.0001799499,0.9916848,0.0009062647,0.0007924717,0.00009332768,0.000357541],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0160566,0.00008667282,0.9784265,0.0003146336,0.001487887,0.0007396754,0.00004685789,0.0002677799,0.00257335],"genre_scores_gemma":[0.1948552,0.000001911044,0.8044405,0.00008099741,0.0001805672,0.00001443,0.00007318966,0.00002176603,0.000331464],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1787986,"threshold_uncertainty_score":0.9999239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06101737584296183,"score_gpt":0.3170134430720717,"score_spread":0.2559960672291099,"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."}}