{"id":"W2090947154","doi":"10.1109/icar.2013.6766547","title":"Human Motion Behaviour Aware Planner (HMBAP) for path planning in dynamic human environments","year":2013,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Planner; Robot; Motion planning; Obstacle; Obstacle avoidance; Computer science; Motion (physics); Trajectory; Path (computing); Social robot; Feature (linguistics); Artificial intelligence; Human–robot interaction; Work (physics); Human–computer interaction; Mobile robot; Human motion; Robot control; Engineering; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002561093,0.0002221494,0.0002177238,0.0001971945,0.0002338746,0.0001567768,0.0007082903,0.000126378,0.00003491627],"category_scores_gemma":[0.00001007909,0.0002118476,0.00005887523,0.0001301444,0.00003140731,0.0006203951,0.0001824969,0.0001888957,0.0001041065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001492407,"about_ca_system_score_gemma":0.00001176603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002177944,"about_ca_topic_score_gemma":0.000004903472,"domain_scores_codex":[0.9982224,0.00005454917,0.0003670668,0.0005679689,0.0002812374,0.0005068303],"domain_scores_gemma":[0.9992002,0.00003870382,0.0001206876,0.0005088237,0.00001768673,0.0001138793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001209589,0.002369361,0.7249815,0.0001951478,0.0001407865,0.0005123329,0.01363318,0.13218,0.04568782,0.01116574,0.0231336,0.04598839],"study_design_scores_gemma":[0.0008520085,0.0001717538,0.5130407,0.00007030913,0.000006159548,0.00001276266,0.0001633347,0.4834881,0.0002098095,0.001566165,0.00004729513,0.0003716268],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3067768,0.00001446213,0.6918626,0.000129139,0.0001900212,0.0005436626,0.000005858451,0.0001572956,0.0003201131],"genre_scores_gemma":[0.9296796,3.03955e-7,0.06798045,0.0001196991,0.00003558736,0.000173337,0.00007389981,0.00002216697,0.001914985],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6238822,"threshold_uncertainty_score":0.8638893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02248731947305596,"score_gpt":0.2838549771682687,"score_spread":0.2613676576952128,"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."}}