{"id":"W4311452201","doi":"10.1016/j.mechmachtheory.2022.105201","title":"A novel multi-point trajectory generator for robotic manipulators based on piecewise motion profile and series-parallel analytical strategy","year":2022,"lang":"en","type":"article","venue":"Mechanism and Machine Theory","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Trajectory; Piecewise; Jerk; Control theory (sociology); Series (stratigraphy); Computer science; Generator (circuit theory); Position (finance); Point (geometry); Overshoot (microwave communication); Point-to-point; Motion (physics); Mathematics; Artificial intelligence; Acceleration; Control (management); Mathematical analysis; Physics","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":[0.0005277981,0.0002772022,0.0002905886,0.0001416172,0.000263166,0.00003686404,0.000102375,0.0000753757,0.000198956],"category_scores_gemma":[0.00001988451,0.000264099,0.00007375158,0.00009362133,0.00002683892,0.00008587843,0.00005897912,0.000225586,0.000001555215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006604342,"about_ca_system_score_gemma":0.0000237967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008941678,"about_ca_topic_score_gemma":0.00000971646,"domain_scores_codex":[0.9989066,0.00007050809,0.0002542638,0.0003094012,0.0001517173,0.0003075628],"domain_scores_gemma":[0.9994941,0.00006579958,0.00004289728,0.0002259206,0.00001824985,0.000153082],"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":[0.0001181371,0.0001001546,0.000002539591,0.00009886586,0.00002762991,0.000003996634,0.00007385594,0.5602806,0.004808144,0.4334585,0.00001956528,0.001008105],"study_design_scores_gemma":[0.001441931,0.0005113888,0.0000550262,0.000009059137,0.0000692785,0.00002752424,0.0002105844,0.9713145,0.0003762922,0.02567539,0.00001274704,0.0002962181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008352982,0.000129387,0.9900166,0.00003724695,0.0003622045,0.0006312588,0.0001233063,0.0001842456,0.0001627251],"genre_scores_gemma":[0.9021732,0.0000193971,0.09640183,0.0001749713,0.00007093018,0.0002831367,0.0001502424,0.0001052085,0.0006210558],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8938202,"threshold_uncertainty_score":0.9999811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02065859125866982,"score_gpt":0.2190283969647933,"score_spread":0.1983698057061234,"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."}}