{"id":"W2091151762","doi":"10.1115/detc2009-87500","title":"Simplified Tele-Operation of Mobile-Manipulator Systems Using Knowledge of Their Singular Configurations","year":2009,"lang":"en","type":"article","venue":"Volume 3: ASME/IEEE 2009 International Conference on Mechatronic and Embedded Systems and Applications; 20th Reliability, Stress Analysis, and Failure Prevention Conference","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Mobile manipulator; Joystick; Position (finance); Computer science; Parallel manipulator; Control theory (sociology); Robot end effector; Simple (philosophy); Serial manipulator; Orientation (vector space); Base (topology); State (computer science); Ideal (ethics); Control engineering; Manipulator (device); Control (management); Mobile robot; Algorithm; Engineering; Artificial intelligence; Simulation; Robot; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004255699,0.0003250407,0.0007098258,0.000353035,0.0001618299,0.0002237205,0.0002268843,0.0002097856,0.00008926687],"category_scores_gemma":[0.00001809986,0.0003018193,0.0001521545,0.000280335,0.0001282694,0.0002615143,0.00003381514,0.0002022051,0.00000194107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005507293,"about_ca_system_score_gemma":0.0001056211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002206519,"about_ca_topic_score_gemma":0.0001465421,"domain_scores_codex":[0.9978987,0.0001326336,0.0009608965,0.0005189804,0.0002601115,0.0002286555],"domain_scores_gemma":[0.9983363,0.00009530324,0.0003828813,0.0004003147,0.0006492233,0.000135954],"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":[0.0001055812,0.0007663228,0.002978244,0.001149697,0.001723141,8.917266e-7,0.0009873456,0.6274906,0.03014534,0.2938535,0.000122088,0.04067719],"study_design_scores_gemma":[0.0004581845,0.0001396446,0.001511719,0.0002642992,0.0003261357,0.000005537533,0.001321515,0.9932853,0.0002034635,0.001764768,0.0004306747,0.0002887489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2862988,0.003097526,0.7066194,0.00009207826,0.0002222874,0.001653994,0.0009606596,0.0001020584,0.0009531788],"genre_scores_gemma":[0.9977407,0.0009766585,0.0004305526,0.000003659063,0.00008911198,0.0002233779,0.0003104498,0.00001387913,0.0002115983],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7114419,"threshold_uncertainty_score":0.9999434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01781326012651316,"score_gpt":0.2738505421402245,"score_spread":0.2560372820137113,"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."}}