{"id":"W3216729193","doi":"10.1002/rnc.5908","title":"Hybrid‐triggered formation tracking control of mobile robots without velocity measurements","year":2021,"lang":"en","type":"article","venue":"International Journal of Robust and Nonlinear Control","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Asynchronous communication; Control theory (sociology); Computer science; Transmission (telecommunications); Event (particle physics); Mobile robot; Observer (physics); Sampling (signal processing); Position (finance); Control (management); Relative velocity; Robot; Stability (learning theory); Real-time computing; Detector; Artificial intelligence; Computer network; Telecommunications","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":[0.000431706,0.0004900421,0.0003951393,0.0002225042,0.0002491508,0.000509215,0.000750732,0.0004010339,0.0005456897],"category_scores_gemma":[0.0007403469,0.0002061007,0.0003326668,0.0001872987,0.0004318772,0.0004787764,0.0006585442,0.0003668874,0.0000636295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002834579,"about_ca_system_score_gemma":0.0004753627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002398907,"about_ca_topic_score_gemma":0.00127386,"domain_scores_codex":[0.9997873,0.00004791599,0.000009732458,0.00006499995,0.00005480806,0.00003520434],"domain_scores_gemma":[0.9996372,0.0001107506,0.0001320828,0.00003012426,0.00006568171,0.00002414919],"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":[0.0002047187,0.00006095424,0.0009370585,0.0001049856,0.00005424827,0.0002611141,0.0001274249,0.9325454,0.02311091,0.01041617,0.0003305507,0.03184642],"study_design_scores_gemma":[0.00001340144,0.00006739516,0.0001221731,0.000001917192,0.000004445973,0.000009078905,0.000006733539,0.9980425,0.0009464101,0.0006360287,0.000146988,0.00000278375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1002007,0.0001577192,0.8973356,0.00006612423,0.00005296506,0.0000358742,0.0000192847,0.0001999262,0.001931857],"genre_scores_gemma":[0.9895973,0.00004249163,0.009420405,0.00001201783,0.000007929655,0.00003782839,0.0000101102,0.000003714684,0.0008683993],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002398907,"threshold_uncertainty_score":0.004769862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03374138308675026,"score_gpt":0.2706794668765874,"score_spread":0.2369380837898372,"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."}}