{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002016986,0.0003974171,0.0003693408,0.0002036799,0.0002254209,0.0004761492,0.0005480136,0.0003674939,0.0006723595],"category_scores_gemma":[0.0005270882,0.0001960376,0.0002752694,0.0001662538,0.0005480053,0.0004994329,0.0006981182,0.000402699,0.0002318575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001640449,"about_ca_system_score_gemma":0.0002119464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006926038,"about_ca_topic_score_gemma":0.0007066338,"domain_scores_codex":[0.9997392,0.00003455546,0.00001071422,0.00004298733,0.0001537097,0.00001872573],"domain_scores_gemma":[0.9998602,0.00004715155,0.00002513762,0.00002740005,0.00003270749,0.000007506627],"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":[0.0001783908,0.0001056134,0.0009864242,0.0002799722,0.0000536454,0.000498144,0.0004201612,0.4363721,0.2156186,0.03162174,0.00105994,0.3128052],"study_design_scores_gemma":[0.00003269765,0.0002284588,0.0005660304,0.00001958682,0.00001381584,0.0002009247,0.00002940257,0.9722075,0.01673585,0.005773472,0.00417045,0.00002177641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01529807,0.0001688984,0.9824119,0.00004493204,0.00002042501,0.00001865691,0.000005594035,0.0002511767,0.00178029],"genre_scores_gemma":[0.7481555,0.0003594308,0.2482625,0.00005501063,0.00003451235,0.0001133378,0.00003696672,0.00003324821,0.002949566],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0006926038,"threshold_uncertainty_score":0.0022493,"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."}}