{"id":"W4301905934","doi":"10.48550/arxiv.1609.06662","title":"On Efficient Computation of Shortest Dubins Paths Through Three\\n Consecutive Points","year":2016,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heading (navigation); Midpoint; Shortest path problem; Discretization; Path (computing); Computation; Mathematical optimization; Mathematics; Point (geometry); Motion planning; Computer science; Control theory (sociology); Algorithm; Geometry; Robot; Artificial intelligence; Combinatorics; Engineering; Mathematical analysis","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":[0.0008129067,0.001044524,0.001271326,0.0005671554,0.0004477256,0.0001305982,0.002834656,0.0007016354,0.00005230488],"category_scores_gemma":[0.0002743919,0.00107839,0.000594232,0.001374785,0.001096775,0.00042956,0.002400549,0.00105314,0.0005688578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007827271,"about_ca_system_score_gemma":0.0009004099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002116401,"about_ca_topic_score_gemma":0.000009384972,"domain_scores_codex":[0.9936936,0.000661266,0.0009646306,0.003058975,0.0005546878,0.001066827],"domain_scores_gemma":[0.9933426,0.001476393,0.001651982,0.002169774,0.0009616481,0.0003975826],"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":[0.0001729728,0.0007057847,0.002286301,0.0000972455,0.0002909818,0.0009577535,0.001805946,0.8009214,0.00006069813,0.1915386,0.0001361675,0.001026081],"study_design_scores_gemma":[0.001836964,0.0006875045,0.007788504,0.002053237,0.0001959352,0.00002861054,0.0001753367,0.8971479,0.0004615812,0.08856341,0.0000150027,0.001045994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2303379,0.00005121567,0.7614697,0.000172527,0.002150512,0.0008874669,0.0001595514,0.0001832639,0.004587827],"genre_scores_gemma":[0.9895052,0.00006524962,0.0098598,0.0001297294,0.00009981328,0.00000188095,0.00002651516,0.00005329651,0.0002584727],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7591673,"threshold_uncertainty_score":0.9991666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08489988401970419,"score_gpt":0.2146759317623997,"score_spread":0.1297760477426955,"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."}}