{"id":"W2790355435","doi":"10.1109/robio.2017.8324674","title":"Adaptive backstepping control approach for the trajectory tracking of mobile manipulators","year":2017,"lang":"en","type":"article","venue":"","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Backstepping; Control theory (sociology); Mobile manipulator; Kinematics; Mobile robot; Controller (irrigation); Trajectory; Control engineering; Torque; Computer science; Motion control; Adaptive control; Nonholonomic system; Robot end effector; Engineering; Robot; Control (management); Artificial intelligence","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":[0.0002264257,0.0001363373,0.0002463637,0.00003237874,0.0002134456,0.0000555806,0.0003630616,0.00006607904,0.00001455864],"category_scores_gemma":[0.00002766281,0.00009666007,0.0001635932,0.00001845416,0.00005912606,0.0001525525,0.00002083948,0.00009792504,0.000001400299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002625744,"about_ca_system_score_gemma":0.00001070886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004249624,"about_ca_topic_score_gemma":0.00003995644,"domain_scores_codex":[0.9993274,0.000008223085,0.0002130276,0.0001353374,0.0001005734,0.0002154098],"domain_scores_gemma":[0.9991808,0.0002140666,0.00007524688,0.000439502,0.00005187395,0.00003850669],"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":[0.00004180196,0.00002639622,0.0004456541,0.00007312685,0.0002141468,4.46974e-7,0.0001385179,0.9517978,0.001921046,0.002060618,0.00009442429,0.04318605],"study_design_scores_gemma":[0.001063734,0.00004564255,0.006012928,0.00001328712,0.00005651617,0.000001468432,0.0002901618,0.9918866,0.0002270379,0.00007572556,0.0001959934,0.0001309709],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01625502,0.0009933801,0.9702075,0.00001737122,0.0003141888,0.00111393,0.00002129612,0.0001224269,0.01095492],"genre_scores_gemma":[0.9968143,0.00002124436,0.002632722,0.00001315452,0.0001115347,0.0002531766,0.000001881039,0.00002930376,0.0001227345],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9805592,"threshold_uncertainty_score":0.3941683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02138383286053579,"score_gpt":0.2301704704165066,"score_spread":0.2087866375559708,"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."}}