{"id":"W3191656955","doi":"10.1109/icc42927.2021.9500370","title":"Simple and Efficient Algorithm for Drone Path Planning","year":2021,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Drone; Motion planning; Computer science; Software deployment; Path (computing); Travelling salesman problem; Computation; Metric (unit); Energy consumption; Real-time computing; Task (project management); Simple (philosophy); Algorithm; Artificial intelligence; Engineering; Robot; Computer network; Operations management; Systems engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.000240574,0.0001156162,0.0001586287,0.00004531715,0.0001505856,0.0001555349,0.0002434271,0.00004683516,0.000005859486],"category_scores_gemma":[0.00005935348,0.0001068354,0.00003615899,0.0002023004,0.00002213833,0.0000975229,0.000232255,0.00007202628,0.000009355847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002041516,"about_ca_system_score_gemma":0.00007140521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007540805,"about_ca_topic_score_gemma":1.195835e-7,"domain_scores_codex":[0.9988729,0.00002833536,0.0001623785,0.0004334688,0.000183197,0.0003197069],"domain_scores_gemma":[0.9992113,0.0002093585,0.0000416,0.0003354701,0.00008710325,0.0001152065],"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":[0.000004423803,0.0002947082,0.0014679,0.00007123258,0.0000926584,0.000760257,0.003157763,0.04143082,0.001929778,0.02379615,0.01511229,0.911882],"study_design_scores_gemma":[0.0003920792,0.00005367489,0.001369248,0.00001802182,0.000004641238,0.00008388001,0.00009002227,0.993004,0.001655235,0.0008627884,0.002308999,0.0001574017],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002583851,0.0003560295,0.9954568,0.0002644566,0.0002838058,0.0001184715,0.000006843341,0.0001805147,0.000749217],"genre_scores_gemma":[0.0150753,0.00000245718,0.9838392,0.0003525968,0.00007495979,0.00001780144,0.00001160866,0.000009309456,0.0006168063],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9515732,"threshold_uncertainty_score":0.435662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02152452679349274,"score_gpt":0.2736884696438729,"score_spread":0.2521639428503802,"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."}}