{"id":"W4415748036","doi":"10.1109/lra.2025.3627071","title":"Quantum Machine Learning and Grover's Algorithm for Quantum Optimization of Robotic Manipulators","year":2025,"lang":"","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"National Natural Science Foundation of China","keywords":"Quantum machine learning; Kinematics; Oracle; Robotics; Parameterized complexity; Quantum; Quantum algorithm; Robot; Dimensionality reduction","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":[0.0007826892,0.0003069689,0.0006222877,0.000383274,0.0004983121,0.0007541713,0.001038105,0.0007682102,0.001853488],"category_scores_gemma":[0.002148938,0.0002201074,0.0003806895,0.0005012995,0.001597033,0.001460139,0.0009556941,0.001330847,0.000265938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000898991,"about_ca_system_score_gemma":0.0008190333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00170474,"about_ca_topic_score_gemma":0.001890819,"domain_scores_codex":[0.9996638,0.0001378005,0.00001266999,0.00004452689,0.0001063627,0.00003479458],"domain_scores_gemma":[0.9995933,0.0002073786,0.00002478817,0.0001023215,0.00005114745,0.00002108762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004319812,0.00003899678,0.0002536373,0.00005146314,0.00001882468,0.00003838517,0.00007711525,0.4187191,0.002514226,0.5225479,0.001408887,0.05428818],"study_design_scores_gemma":[0.000006981426,0.00001393592,0.00005232636,0.000004112922,0.000001554259,0.000009368518,0.00000593499,0.9212238,0.0006417212,0.07724099,0.0007937613,0.000005414651],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02026535,0.0002737341,0.9726133,0.000447533,0.00003907812,0.00002811017,0.00003220487,0.0003567238,0.005943971],"genre_scores_gemma":[0.6048927,0.0003820371,0.3910249,0.0002407861,0.00007103715,0.0001399328,0.00009117393,0.0001295549,0.003027882],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001853488,"threshold_uncertainty_score":0.006522655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009307229253889743,"score_gpt":0.23742717849079,"score_spread":0.2281199492369002,"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."}}