{"id":"W4210436559","doi":"10.23919/jsee.2021.000123","title":"Experimental study of path planning problem using EMCOA for a holonomic mobile robot","year":2021,"lang":"en","type":"article","venue":"Journal of Systems Engineering and Electronics","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Motion planning; Holonomic; Mobile robot; Computer science; Path (computing); Genetic algorithm; Shortest path problem; Any-angle path planning; Mathematical optimization; Occupancy grid mapping; Grid; Robot; Artificial intelligence; Mathematics; Theoretical computer science","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":[0.0007098601,0.0007448168,0.0005368614,0.0005482994,0.0004512833,0.0002359029,0.0006801148,0.0006485967,0.003297976],"category_scores_gemma":[0.002292998,0.000157321,0.000268218,0.0004840162,0.0004208283,0.0006714705,0.0004966432,0.0005761822,0.0003859572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002723015,"about_ca_system_score_gemma":0.0004638435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002177723,"about_ca_topic_score_gemma":0.002132643,"domain_scores_codex":[0.9996214,0.0001306792,0.00002383178,0.00008112684,0.00007530807,0.00006761634],"domain_scores_gemma":[0.9983615,0.0009523406,0.0001083668,0.0002444306,0.0002393305,0.00009390237],"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":[0.002156058,0.002516853,0.004383968,0.001736478,0.0001314889,0.0006190477,0.0005190937,0.7236757,0.075118,0.005364262,0.002298131,0.181481],"study_design_scores_gemma":[0.0001062293,0.002706711,0.003087357,0.00003949129,0.00002711935,0.0001236241,0.0003216017,0.9567176,0.03349372,0.001410663,0.001937957,0.0000279452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8433276,0.0006002025,0.1442652,0.0001854879,0.000137974,0.0002224357,0.0002951482,0.001156021,0.009809929],"genre_scores_gemma":[0.9440441,0.0001818337,0.05348467,0.00002912893,0.000008478426,0.0001697844,0.0002904664,0.00003888447,0.001752734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003297976,"threshold_uncertainty_score":0.01103288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01993231418441986,"score_gpt":0.2642990255092885,"score_spread":0.2443667113248686,"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."}}