{"id":"W4316661137","doi":"10.1109/tac.2023.3237484","title":"Local Topology Inference of Mobile Robotic Networks Under Formation Control","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Natural Science Foundation of China","keywords":"Unobservable; Estimator; Mobile robot; Topology (electrical circuits); Robot; Network topology; Range (aeronautics); Inference; Computer science; Convergence (economics); Control theory (sociology); Mathematics; Artificial intelligence; Control (management); 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005589632,0.0002853316,0.0006641086,0.0003797846,0.0001822971,0.00009404305,0.0007396351,0.0001952083,0.00007456507],"category_scores_gemma":[0.00002310544,0.0002692886,0.000241844,0.0008922666,0.000128976,0.0005306542,0.000004095686,0.0002191856,0.0003150339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001579097,"about_ca_system_score_gemma":0.0001147857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006953426,"about_ca_topic_score_gemma":0.0000612529,"domain_scores_codex":[0.9973281,0.0003502776,0.0009106898,0.0003903333,0.0004499448,0.0005706407],"domain_scores_gemma":[0.9972954,0.00123453,0.0003349555,0.0008043242,0.0001776764,0.0001531157],"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":[0.00002044244,0.0001356572,0.000007439597,0.0000436798,0.0001356228,0.000007675389,0.0001772866,0.9407962,0.0005830112,0.001825624,0.0001041734,0.05616322],"study_design_scores_gemma":[0.003925231,0.0002756461,0.0005471556,0.00007415997,0.0000882662,0.00001724954,0.0001339296,0.9939298,0.0003820932,0.0003637715,0.00003634721,0.0002263709],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002963545,0.00004609666,0.9928113,0.0006934301,0.001276513,0.001185532,0.00003500138,0.0009136267,0.00007498798],"genre_scores_gemma":[0.9985471,0.000009936174,0.0003976566,0.0003359273,0.00002649125,0.0005522422,0.000005922273,0.00001943354,0.0001052717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9955836,"threshold_uncertainty_score":0.9999759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01573479941456693,"score_gpt":0.2577132828098427,"score_spread":0.2419784833952758,"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."}}