{"id":"W1975611521","doi":"10.1109/icra.2012.6224927","title":"Kinematic control and posture optimization of a redundantly actuated quadruped robot","year":2012,"lang":"en","type":"article","venue":"","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; McGill University","funders":"","keywords":"Robot; Kinematics; Inverse kinematics; Robot locomotion; Control engineering; Terrain; Computer science; Actuator; Robotics; Robot kinematics; Hexapod; Robot control; Simulation; Artificial intelligence; Control theory (sociology); Engineering; Control (management); Mobile robot","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008749399,0.00009007817,0.0001732448,0.00004858193,0.00001707822,0.00001213893,0.00003850373,0.00005451173,0.0002019962],"category_scores_gemma":[0.0000262217,0.00007282507,0.00002596492,0.00008080091,0.00001536579,0.0001304368,0.000005140565,0.00005000999,0.000008898118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001071811,"about_ca_system_score_gemma":0.000004104907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006791158,"about_ca_topic_score_gemma":0.000001360997,"domain_scores_codex":[0.9995226,0.00002033289,0.0001835141,0.00005168895,0.00007682462,0.0001449876],"domain_scores_gemma":[0.9997288,0.00003736589,0.00002744011,0.000100773,0.00003225371,0.00007336672],"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":[0.00001794697,0.00005690743,0.0008056543,0.00008801115,0.0001075473,4.940803e-7,0.0005098124,0.9750826,0.01993079,0.001044907,0.0002958053,0.002059544],"study_design_scores_gemma":[0.00145156,0.00002345659,0.005345766,0.00002041656,0.00005051296,0.00001229836,0.00008060045,0.9921429,0.0007155486,0.00001617025,0.00002777744,0.0001130665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01491438,0.0003582614,0.9798465,0.0002395323,0.000154485,0.0002824316,0.000002224316,0.0001986322,0.004003563],"genre_scores_gemma":[0.9913092,0.00001952398,0.008408603,0.00007626197,0.00003326702,0.000008208492,0.00000477814,0.00001464341,0.0001255297],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9763948,"threshold_uncertainty_score":0.296972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005060271858620591,"score_gpt":0.1886808621071586,"score_spread":0.183620590248538,"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."}}