{"id":"W4410887720","doi":"10.1109/syscon64521.2025.11014789","title":"Enhancing Robot Navigation in Crowded Spaces Through Systematic Strategy Selection","year":2025,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University; Queen's University","funders":"","keywords":"Selection (genetic algorithm); Computer science; Robot; Artificial intelligence; Mobile robot; Computer vision; Human–computer interaction","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":[0.0004617298,0.0001203351,0.0002308702,0.0001409605,0.00008528274,0.0002481857,0.000351628,0.00007245202,0.000002954571],"category_scores_gemma":[0.00008627686,0.0001072248,0.00002907047,0.001080765,0.00001252006,0.000675043,0.00006340501,0.0001371725,0.00003436519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001315072,"about_ca_system_score_gemma":0.0001139527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003826376,"about_ca_topic_score_gemma":0.00005858218,"domain_scores_codex":[0.9987422,0.0001445037,0.0003670967,0.0003196732,0.0001930532,0.0002334591],"domain_scores_gemma":[0.9993882,0.0001614287,0.00009616314,0.000257662,0.00007406031,0.00002255353],"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":[0.00001153206,0.0003095726,0.00516921,0.0166815,0.0001434162,0.00009896456,0.009235127,0.6000559,0.04965355,0.3151598,0.0006989795,0.002782452],"study_design_scores_gemma":[0.0003082867,0.00005516742,0.002641558,0.004628483,0.00001116245,0.00002366833,0.0004676763,0.9503679,0.0342954,0.006993688,0.000003049493,0.000203921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01170459,0.0001196275,0.9833885,0.0002938462,0.0003563146,0.0003247002,9.356927e-8,0.0002558015,0.003556497],"genre_scores_gemma":[0.7547483,0.000001820028,0.2440015,0.00009286885,0.00001759232,0.00003589764,0.000001526776,0.000004028269,0.001096419],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7430437,"threshold_uncertainty_score":0.4372502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01767172576120244,"score_gpt":0.288334335868557,"score_spread":0.2706626101073545,"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."}}