{"id":"W2068261665","doi":"10.1007/s11768-005-0012-7","title":"Vision-based formation control of mobile robots","year":2005,"lang":"en","type":"article","venue":"Journal of Control Theory and Applications","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Mobile robot; Obstacle; Obstacle avoidance; Robot; Computer science; Tilt (camera); Computer vision; Artificial intelligence; Control (management); Variation (astronomy); Motion control; Computational intelligence; Motion (physics); Control theory (sociology); Control engineering; Simulation; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002857107,0.000343748,0.0005300337,0.0003358496,0.0004266109,0.0005997064,0.0007177448,0.0004739137,0.0007573684],"category_scores_gemma":[0.0009173917,0.0002883812,0.0003021141,0.0002352257,0.0006305556,0.0004977695,0.0008588364,0.0004882954,0.0001589841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003852129,"about_ca_system_score_gemma":0.0006977844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004924611,"about_ca_topic_score_gemma":0.004124529,"domain_scores_codex":[0.9998587,0.00002580162,0.000004973001,0.00002964479,0.00005493433,0.000025795],"domain_scores_gemma":[0.9997783,0.00005687444,0.00004184566,0.00001909508,0.00008012608,0.00002377536],"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":[0.0003756219,0.0001457224,0.000673254,0.0001184215,0.00005927197,0.0001208894,0.0002100931,0.7763475,0.03781451,0.02033497,0.002165051,0.1616347],"study_design_scores_gemma":[0.00003090587,0.0001076652,0.000267482,0.00000524644,0.00000828067,0.00002398409,0.00001378584,0.9911862,0.00308722,0.004425825,0.0008356101,0.000007791829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08946859,0.001159318,0.8995503,0.0003256972,0.0003120455,0.00005373975,0.00002527083,0.0004050866,0.00869986],"genre_scores_gemma":[0.9729782,0.0001923255,0.02462231,0.00004839585,0.00003212007,0.00003290188,0.00002429892,0.00001811911,0.00205139],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004924611,"threshold_uncertainty_score":0.009791911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004628164306200594,"score_gpt":0.24654046272106,"score_spread":0.2419122984148595,"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."}}