{"id":"W4230231983","doi":"10.3390/books978-3-0365-0345-5","title":"Visual Servoing in Robotics","year":2021,"lang":"en","type":"book","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Science and ICT, South Korea; National Research Foundation of Korea; Korea Institute for Advancement of Technology; Iran Telecommunication Research Center; Ministry of Trade, Industry and Energy; Government of Jiangsu Province; National Natural Science Foundation of China; Institute for Information and Communications Technology Promotion; China Postdoctoral Science Foundation; National Research Foundation","keywords":"Visual servoing; Artificial intelligence; Computer vision; Robotics; Computer science; Robot; Visual control; Teleoperation; Image processing; Image (mathematics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002921548,0.001453927,0.001051151,0.001342018,0.0007719694,0.002388408,0.001169558,0.001558237,0.02756037],"category_scores_gemma":[0.0007828548,0.0004823451,0.0004433193,0.002374645,0.001304382,0.002504371,0.00118433,0.002218579,0.02562985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102478,"about_ca_system_score_gemma":0.0006839917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009321154,"about_ca_topic_score_gemma":0.001192412,"domain_scores_codex":[0.9994362,0.00006920726,0.00002360171,0.0001144103,0.0003199028,0.0000366402],"domain_scores_gemma":[0.9997337,0.000109469,0.00001811369,0.00003555191,0.00007571666,0.00002738928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004399934,0.00005153392,0.00009911357,0.001459459,0.00002122365,0.0001377939,0.0003470427,0.004019871,0.003786523,0.1625622,0.2627336,0.5647376],"study_design_scores_gemma":[0.000004392249,0.00002675044,0.0001243748,0.0002327502,0.000003938633,0.0002194673,0.00003544878,0.0009114404,0.0003928703,0.02565432,0.9723825,0.00001172078],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.001423414,0.2535749,0.07353893,0.002085366,0.006465059,0.0001280644,0.0003013169,0.002101948,0.660381],"genre_scores_gemma":[0.01980417,0.158402,0.05610837,0.002079968,0.00350411,0.000214728,0.0007061728,0.0007082507,0.7584721],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02756037,"threshold_uncertainty_score":0.09219855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01374506684287886,"score_gpt":0.2867563747984914,"score_spread":0.2730113079556126,"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."}}