{"id":"W4416097723","doi":"10.48550/arxiv.2505.04978","title":"Robust Model-Based In-Hand Manipulation with Integrated Real-Time Motion-Contact Planning and Tracking","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centers for Disease Control and Prevention; Tsinghua University; National Natural Science Foundation of China; Canadian Institute for Advanced Research","keywords":"Robustness (evolution); Motion planning; Key (lock); Robot; Online model; Robotics; Robotic hand; Tracking (education)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001894946,0.0003504718,0.0003853284,0.0004077107,0.0001012549,0.000132962,0.000121439,0.0003001931,0.00003718222],"category_scores_gemma":[0.00003368185,0.0003550737,0.00004904367,0.0002313828,0.00002257459,0.0001730018,0.00005205012,0.0008072825,0.000008563587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001866076,"about_ca_system_score_gemma":0.00006992507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001706668,"about_ca_topic_score_gemma":0.0000785701,"domain_scores_codex":[0.9987311,0.00005689321,0.000385064,0.0004251571,0.0001437267,0.0002580865],"domain_scores_gemma":[0.9994069,0.00007538567,0.0001074362,0.0002729433,0.00007200428,0.00006530436],"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":[0.00002338655,0.000009098276,0.2566985,0.0001749751,0.00002844605,0.00001049866,0.0003903068,0.7415606,0.0006980171,0.00001878827,0.00001224083,0.0003751252],"study_design_scores_gemma":[0.0003836329,0.0000106928,0.3050715,0.0008430088,0.00002935633,0.0000011987,0.00004203455,0.6931381,0.000210764,0.00001579934,0.000008646792,0.00024533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7027901,0.0001028771,0.2946597,0.00002822986,0.0001064629,0.0002574287,0.000002455859,0.0002946225,0.00175817],"genre_scores_gemma":[0.9968567,0.00001735511,0.002415893,0.00002532719,0.00005077068,0.0000319658,0.000291109,0.00005566677,0.0002552462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2940666,"threshold_uncertainty_score":0.9998901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0618746124324452,"score_gpt":0.2557028011252395,"score_spread":0.1938281886927943,"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."}}