{"id":"W4416272762","doi":"10.18280/jesa.580916","title":"Efficient Trajectory Generation of Mobile Robot Based on Q-learning Algorithm","year":2025,"lang":"","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Trajectory; Mobile robot; Robot; Tracking (education); Algorithm design","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007705123,0.0005575553,0.001062042,0.0006573554,0.0006664635,0.0005693378,0.001092261,0.0009222395,0.002789679],"category_scores_gemma":[0.001635193,0.0004182802,0.0005349682,0.0007015193,0.0005901187,0.0006974563,0.0008134037,0.0006488594,0.0004545182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006110549,"about_ca_system_score_gemma":0.001666007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009179007,"about_ca_topic_score_gemma":0.004532432,"domain_scores_codex":[0.9996381,0.00009402279,0.00001821337,0.00009789065,0.00009535682,0.00005642845],"domain_scores_gemma":[0.9993644,0.0002863932,0.00005087108,0.00006006117,0.0002043916,0.00003383016],"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":[0.0001935074,0.000078759,0.001101741,0.0001029739,0.00004390364,0.0001071451,0.00007789639,0.7868432,0.005196102,0.007432189,0.001654486,0.1971681],"study_design_scores_gemma":[0.00001299435,0.00002880783,0.0000852305,0.000002715497,0.000003299316,0.00001430288,0.00000443003,0.9979978,0.0004340776,0.001223731,0.0001899691,0.000002621021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01495772,0.0001342276,0.9834411,0.0000785318,0.00003158166,0.00004969384,0.00002292716,0.0003844482,0.0008996787],"genre_scores_gemma":[0.5994599,0.0001638581,0.3971496,0.0001025035,0.00003178998,0.0002095415,0.0001973724,0.0000842642,0.002601084],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009179007,"threshold_uncertainty_score":0.01825112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02370247335797088,"score_gpt":0.2704277244282495,"score_spread":0.2467252510702787,"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."}}