{"id":"W3128530779","doi":"10.1109/tac.2021.3086329","title":"Obstacle Avoidance via Hybrid Feedback","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"European Research Council; Natural Sciences and Engineering Research Council of Canada; Vetenskapsrådet","keywords":"Obstacle avoidance; Controller (irrigation); Control theory (sociology); Position (finance); Collision avoidance; Computer science; Control (management); Mathematics; Artificial intelligence; Mobile robot; Robot","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":[0.0001713538,0.0004728999,0.0004194161,0.0002914709,0.0003898368,0.0005616677,0.0007619195,0.0005593003,0.001399374],"category_scores_gemma":[0.0002990057,0.0002127672,0.0003252042,0.0001979472,0.0005200526,0.0005152205,0.001105011,0.0004251287,0.0002200266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002797113,"about_ca_system_score_gemma":0.0003042424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002354583,"about_ca_topic_score_gemma":0.001807946,"domain_scores_codex":[0.9998831,0.00001782092,0.000004765245,0.00003026339,0.00004339259,0.00002064339],"domain_scores_gemma":[0.9998569,0.00006034881,0.0000205763,0.00001269293,0.00003666269,0.00001263943],"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":[0.0002339475,0.00008294417,0.0007042077,0.0002216408,0.00007623481,0.0003407428,0.0003314612,0.8032827,0.04838164,0.02380919,0.001574892,0.1209603],"study_design_scores_gemma":[0.00002251539,0.000110183,0.0001152433,0.000007855693,0.000009957535,0.00004316644,0.00002046902,0.992084,0.003093893,0.003371438,0.001109776,0.00001152072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04098633,0.0003858657,0.9535812,0.00009266854,0.00007656628,0.00002499493,0.00001932912,0.0005607153,0.004272348],"genre_scores_gemma":[0.9596509,0.0001868683,0.03660442,0.000075767,0.00002412459,0.00007853923,0.00002750227,0.00002068897,0.003331203],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002354583,"threshold_uncertainty_score":0.004681706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01170842460176454,"score_gpt":0.2304376578128424,"score_spread":0.2187292332110778,"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."}}