{"id":"W2112323931","doi":"10.1109/mfi.1994.398459","title":"Local path planning in dynamic environments with uncertainty","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Obstacle; Motion planning; Acceleration; Path (computing); Mobile robot; Computer science; Collision; Robot; Function (biology); Mathematical optimization; Collision avoidance; Obstacle avoidance; Simulation; Artificial intelligence; Mathematics; Computer security; Geography; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001258081,0.000134385,0.0001344053,0.00008918542,0.00004776581,0.00004569119,0.0004926485,0.00004727319,0.00002927239],"category_scores_gemma":[0.000006358494,0.0001048152,0.00001639753,0.0002440266,0.00005344585,0.0002422108,0.0001067283,0.0001598881,0.0001571319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001351962,"about_ca_system_score_gemma":0.000009865623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004485669,"about_ca_topic_score_gemma":0.000002823257,"domain_scores_codex":[0.9988095,0.00004043964,0.0001558034,0.0003689774,0.0002823426,0.0003429601],"domain_scores_gemma":[0.9994372,0.00005332569,0.00004233026,0.0003813442,0.000004093668,0.00008176976],"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":[0.000005550514,0.0001650155,0.0125301,0.000006363338,0.00001505203,0.0009017058,0.002126985,0.9349644,0.00007456206,0.0007641107,0.0005978858,0.04784827],"study_design_scores_gemma":[0.0004026066,0.00009373191,0.01395815,0.00004066693,0.000001285426,0.00004485892,0.00007010885,0.9847134,0.00002104612,0.000091911,0.0003997868,0.0001623886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01089025,0.00007034541,0.9848462,0.0002647165,0.00006989152,0.00008749335,5.719695e-7,0.00009859984,0.00367195],"genre_scores_gemma":[0.8365697,0.000003604493,0.1619759,0.0002132644,0.000005943581,0.000008584612,0.000001649117,0.000007708006,0.001213653],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8256794,"threshold_uncertainty_score":0.427424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0146182439192195,"score_gpt":0.2216201006394983,"score_spread":0.2070018567202788,"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."}}