{"id":"W4298223224","doi":"","title":"Path following control of unmanned quadrotor helicopter with obstacle avoidance capability","year":2017,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Obstacle avoidance; Collision avoidance; Path (computing); Computer science; Obstacle; Remotely operated underwater vehicle; Control (management); Aeronautics; Aerospace engineering; Mobile robot; Engineering; Computer network; Artificial intelligence; Robot; Computer security; Geography","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":[0.004101119,0.0002111368,0.0003478348,0.00007067744,0.0006655148,0.0004205698,0.002541048,0.00008680591,0.000008972313],"category_scores_gemma":[0.001605012,0.0001919703,0.0001375529,0.0001820625,0.0002692758,0.0006371283,0.0004007114,0.000217542,0.00002106296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006058758,"about_ca_system_score_gemma":0.0001654754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008523118,"about_ca_topic_score_gemma":0.0001461724,"domain_scores_codex":[0.9964546,0.001697737,0.000386346,0.0006096712,0.000482341,0.0003692819],"domain_scores_gemma":[0.9936605,0.0009849964,0.0005759479,0.003677306,0.0009382809,0.0001629514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001216973,0.002610107,0.5848425,0.0004521819,0.0005129094,0.0001626493,0.04340706,0.00107228,0.0362609,0.1819172,0.0003866646,0.1482538],"study_design_scores_gemma":[0.005027742,0.000008217322,0.3535732,0.002785488,0.00006951028,0.00004064017,0.0001619431,0.5015072,0.1317274,0.002849167,0.001191147,0.001058391],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2121681,0.0001438958,0.7787114,0.003601288,0.000154384,0.0003232411,0.00001167208,0.0001429016,0.004743167],"genre_scores_gemma":[0.7861118,0.000005653012,0.2130952,0.00004752655,0.000008057185,0.00003136682,0.000005934404,0.00001381937,0.0006806114],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5739438,"threshold_uncertainty_score":0.7828323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01093786917581477,"score_gpt":0.2251751425091364,"score_spread":0.2142372733333216,"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."}}