{"id":"W4388709207","doi":"10.23977/jaip.2023.060705","title":"Research on Robot Path Planning Based on Simulated Annealing Algorithm","year":2023,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence Practice","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Shortest path problem; Motion planning; Simulated annealing; Constrained Shortest Path First; Crossover; Computer science; K shortest path routing; Mathematical optimization; Correctness; Shortest Path Faster Algorithm; Any-angle path planning; Yen's algorithm; MATLAB; Path (computing); Algorithm; Robot; Mathematics; Dijkstra's algorithm; Artificial intelligence; Theoretical computer science; Graph","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01119834,0.0002507809,0.0003681604,0.001449629,0.0005250798,0.0006030538,0.001532473,0.0001708584,0.00001439961],"category_scores_gemma":[0.006799776,0.000223129,0.0001495373,0.003417728,0.000101492,0.001240895,0.0001701252,0.001950335,0.0007337709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002099725,"about_ca_system_score_gemma":0.0004207225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003897316,"about_ca_topic_score_gemma":1.750495e-7,"domain_scores_codex":[0.9941773,0.001151106,0.001069708,0.0005063234,0.002297541,0.0007980391],"domain_scores_gemma":[0.9868906,0.009915227,0.0007832425,0.0006630966,0.001438432,0.0003094356],"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":[0.0001657312,0.0002149238,0.00001000519,0.000006439892,0.00002842306,0.002243358,0.001015304,0.8423795,0.0002865331,0.001321016,0.000933117,0.1513956],"study_design_scores_gemma":[0.00007946945,0.001619314,0.00008316991,0.0004074472,0.00001489321,0.0001104393,0.001757526,0.9849939,0.006152567,0.002820767,0.001737563,0.000222979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00229902,0.00006350429,0.9877014,0.006523995,0.001974931,0.0001797947,0.000002835151,0.0001726031,0.001081969],"genre_scores_gemma":[0.4581434,0.00004976108,0.538905,0.001493104,0.001235093,0.000005249401,0.000004427498,0.00005733474,0.0001066384],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4558444,"threshold_uncertainty_score":0.9431385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2319650491379905,"score_gpt":0.4655164877539756,"score_spread":0.2335514386159852,"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."}}