{"id":"W3182194800","doi":"10.1109/crv52889.2021.00017","title":"Mobile Manipulation in Unknown Environments with Differential Inverse Kinematics Control","year":2021,"lang":"en","type":"article","venue":"","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto","funders":"","keywords":"Workspace; Inverse kinematics; Kinematics; Trajectory; Computer science; Mobile manipulator; Controller (irrigation); Mobile robot; Differential (mechanical device); Omnidirectional antenna; Control engineering; Robot kinematics; Control theory (sociology); Artificial intelligence; Robot; 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":[],"consensus_categories":[],"category_scores_codex":[0.00002214984,0.00006927238,0.0001036574,0.00002883185,0.00001138114,0.00002227582,0.00002385262,0.00003419132,0.0006401024],"category_scores_gemma":[0.000002344038,0.00005801265,0.0000131151,0.00005107053,0.00000615236,0.00005444765,0.000004674495,0.00004213854,0.00006496462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004359744,"about_ca_system_score_gemma":0.000005435249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000803437,"about_ca_topic_score_gemma":0.0002930376,"domain_scores_codex":[0.9995795,0.00001469514,0.0001447975,0.00007365448,0.00009321167,0.00009408579],"domain_scores_gemma":[0.9998424,0.000009563755,0.000009697825,0.0001009182,0.000005532506,0.0000318544],"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":[0.00001837533,0.0001875888,0.02366166,0.0001593153,0.0001176207,0.00006706435,0.001782179,0.868862,0.09811711,0.003794204,0.000730129,0.002502782],"study_design_scores_gemma":[0.002218238,0.00003541094,0.01445961,0.00003467325,0.00001637798,0.00001137598,0.0003605952,0.973679,0.005434718,0.00001861375,0.00354556,0.000185848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8823367,0.00002923233,0.1105825,0.00001022605,0.0001585432,0.0002073282,0.000001723169,0.0000735917,0.006600135],"genre_scores_gemma":[0.9980225,0.000008914342,0.0006218886,0.00002958408,0.00003156384,0.00003059239,0.00001539389,0.00001171388,0.001227827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1156858,"threshold_uncertainty_score":0.7008672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00771380206632481,"score_gpt":0.1835706160947278,"score_spread":0.175856814028403,"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."}}