{"id":"W4317791239","doi":"10.2316/j.2023.206-0782","title":"MOBILE ROBOT DOCKING WITH OBSTACLE AVOIDANCE AND VISUAL SERVOING AVOIDANCE AND VISUAL SERVOING, 97-108.","year":2023,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Visual servoing; Obstacle avoidance; Computer vision; Computer science; Artificial intelligence; Mobile robot; Collision avoidance; Robot; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003568981,0.0001417996,0.0001814851,0.0002580723,0.0001725735,0.0004836533,0.0002163006,0.00003551583,0.000002398496],"category_scores_gemma":[0.00005973645,0.0001209882,0.00002933076,0.0002320228,0.00005436322,0.001534705,0.0002128491,0.0001908454,0.00000371655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004465424,"about_ca_system_score_gemma":0.00004621878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005086867,"about_ca_topic_score_gemma":0.000003814951,"domain_scores_codex":[0.9987055,0.00004201089,0.0003701259,0.0002257202,0.0004784153,0.0001782217],"domain_scores_gemma":[0.9989842,0.0001339416,0.0003921712,0.00006407987,0.0003226233,0.0001029426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000671931,0.0001189696,0.01364228,0.0001006825,0.0001409701,0.0002331731,0.00333836,0.2387296,0.01401688,0.003196589,0.000113154,0.7263021],"study_design_scores_gemma":[0.000724947,0.0002249357,0.01920222,0.0004150133,0.000009317398,0.0004208415,0.0002591922,0.9757519,0.001447257,0.001073618,0.0003070569,0.0001636541],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3740762,0.0004486223,0.6241904,0.0007913213,0.000336307,0.00006528832,0.000001015862,0.00006182099,0.0000289819],"genre_scores_gemma":[0.9303034,0.0004446656,0.06882435,0.0002018548,0.0001256811,0.000002127071,0.000002537799,0.00001222037,0.0000831853],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7370223,"threshold_uncertainty_score":0.4933757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009530988570629,"score_gpt":0.2935120022523039,"score_spread":0.2834166923665977,"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."}}