{"id":"W2062632572","doi":"10.1109/ccece.2008.4564507","title":"Leader-follower formation control for a team of mobile robots using an acoustic array","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Omnidirectional antenna; Mobile robot; Robot; Computer science; Controller (irrigation); Kinematics; Control theory (sociology); Range (aeronautics); Nonholonomic system; Control (management); Engineering; Artificial intelligence; Antenna (radio); Physics; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00009115983,0.000269791,0.0003511692,0.0003384716,0.0001191775,0.00009126352,0.0001853675,0.0001554702,0.0000124585],"category_scores_gemma":[0.0000208736,0.0002876062,0.00005592735,0.0002499399,0.00003992567,0.0003720024,0.000006795755,0.0002321186,0.000001911503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001569189,"about_ca_system_score_gemma":0.000194406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001609092,"about_ca_topic_score_gemma":0.0003270018,"domain_scores_codex":[0.9987447,0.000004515346,0.0003313962,0.0002586036,0.000160354,0.0005004387],"domain_scores_gemma":[0.999111,0.00003978028,0.00005603015,0.00009102168,0.0003038576,0.0003983356],"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":[0.00007618946,0.0001556316,0.001199845,0.0007833723,0.0001847834,0.00001063119,0.004375043,0.8075913,0.1280219,0.03193825,0.0005085031,0.02515447],"study_design_scores_gemma":[0.0005210994,0.0003228495,0.000434893,0.00008336696,0.00002412172,0.00004379659,0.00005558664,0.9966422,0.001275467,0.0001210542,0.0001433304,0.0003322175],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3057211,0.0000551156,0.6932542,0.00002565651,0.000112662,0.0004008243,0.00002317945,0.0001458786,0.0002613802],"genre_scores_gemma":[0.9953699,0.00004799972,0.004267482,0.00007737181,0.00009713013,0.00007541393,0.00001276391,0.00003450109,0.00001740746],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6896489,"threshold_uncertainty_score":0.9999576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02337474366153486,"score_gpt":0.2110875525489611,"score_spread":0.1877128088874262,"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."}}