{"id":"W4386902776","doi":"10.1109/mra.2023.3310858","title":"Synthesis, Design, and Experimental Validation of an Agile Wrist for Enhanced Grasping and Manipulation in Cluttered Environments: An Experimental Evaluation With a Challenging Pick-and-Place Task","year":2023,"lang":"en","type":"article","venue":"IEEE Robotics & Automation Magazine","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Agile software development; Task (project management); SMT placement equipment; Computer science; Trajectory; Robot; Artificial intelligence; Computer vision; Wrist; Human–computer interaction; Simulation; Motion (physics); Engineering; Systems engineering; Software engineering","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":[0.0007986047,0.0008514058,0.0005653085,0.0005772854,0.0002343353,0.0006733955,0.0009491764,0.0009547058,0.001775326],"category_scores_gemma":[0.001316763,0.0003166074,0.0003841461,0.0002902339,0.0005199728,0.000491683,0.0005891717,0.000376234,0.0007892979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001387532,"about_ca_system_score_gemma":0.0004577294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002670911,"about_ca_topic_score_gemma":0.0002884387,"domain_scores_codex":[0.9995728,0.00005944158,0.00004419742,0.00009270509,0.000178471,0.00005229717],"domain_scores_gemma":[0.9988911,0.0002481462,0.0001503772,0.0002257043,0.0003040563,0.0001807027],"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":[0.0008358299,0.00079895,0.001736269,0.001791444,0.00009320548,0.0009625768,0.0005871507,0.02679043,0.8311986,0.001437047,0.001115853,0.1326526],"study_design_scores_gemma":[0.0005991781,0.02374313,0.012658,0.0002658673,0.0003373153,0.002257948,0.0005596392,0.1749352,0.7559536,0.0009965395,0.02747606,0.0002175435],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3913223,0.0008946497,0.5990866,0.000166703,0.0002911202,0.001191808,0.0002561787,0.001897012,0.00489363],"genre_scores_gemma":[0.7450066,0.0005330588,0.2498685,0.00007804719,0.0000218949,0.0007008195,0.000198402,0.0001339606,0.003458796],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001775326,"threshold_uncertainty_score":0.005939066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03672385142810874,"score_gpt":0.2866734344541836,"score_spread":0.2499495830260749,"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."}}