{"id":"W4365129215","doi":"10.1109/tmech.2023.3263108","title":"Noncollocated Proprioceptive Sensing for Lightweight Flexible Robotic Manipulators","year":2023,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Serial manipulator; Kinematics; Computer science; Encoder; Actuator; Control engineering; Robotic arm; Context (archaeology); Redundancy (engineering); Workspace; Kinematic chain; Robot end effector; Robot; Mobile manipulator; Flexibility (engineering); Control theory (sociology); Simulation; Parallel manipulator; Engineering; Artificial intelligence; Control (management); Mobile robot","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":[0.0002554827,0.0004300597,0.0002341445,0.0002090216,0.0001772393,0.0003165175,0.0007732279,0.000281496,0.001122139],"category_scores_gemma":[0.0006291551,0.000177645,0.0001513112,0.000150014,0.0003575651,0.0005015535,0.0005238561,0.000253685,0.0002666397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001966501,"about_ca_system_score_gemma":0.0002800961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003340741,"about_ca_topic_score_gemma":0.0006254635,"domain_scores_codex":[0.9996892,0.00003839653,0.00001658909,0.00004468226,0.0001946327,0.00001650111],"domain_scores_gemma":[0.9996715,0.0001038668,0.0001069214,0.00004715012,0.00005444088,0.00001621552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002389865,0.00006245523,0.0005463876,0.0003433885,0.00001806109,0.0002695344,0.0001799583,0.02720462,0.8251172,0.005741776,0.0004734601,0.1398041],"study_design_scores_gemma":[0.0001448145,0.002842036,0.005491602,0.00009974874,0.00004766425,0.001569058,0.00009588499,0.5674366,0.3939345,0.006377777,0.02184369,0.0001165074],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08961333,0.0005593225,0.9070857,0.00007529146,0.00006396237,0.00004983062,0.0000278657,0.0004706272,0.002054001],"genre_scores_gemma":[0.81606,0.000284608,0.1808756,0.00005730784,0.00003940942,0.0000729137,0.0000473778,0.00002373104,0.002539078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001122139,"threshold_uncertainty_score":0.00375396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03122274842751886,"score_gpt":0.2551749758532721,"score_spread":0.2239522274257532,"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."}}