{"id":"W2083841567","doi":"10.1109/iros.2006.282068","title":"Real-time 3D Collision Avoidance Method for Safe Human and Robot Coexistence","year":2006,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Robot; Collision avoidance; Computer science; Collision; Workspace; Collision detection; Simulation; Monte Carlo localization; Robot kinematics; Artificial intelligence; Computer vision; Algorithm; Mobile robot","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":[0.0003512974,0.000498121,0.0004902273,0.0004193216,0.0004002181,0.0004845502,0.001061535,0.0006176282,0.003578597],"category_scores_gemma":[0.0006118797,0.0003044957,0.0003822967,0.0002910272,0.0003572544,0.0004582522,0.0006531345,0.000561566,0.000693388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000399484,"about_ca_system_score_gemma":0.0006909368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001239332,"about_ca_topic_score_gemma":0.001538526,"domain_scores_codex":[0.9996734,0.00004847626,0.000009692237,0.0000457988,0.0002016245,0.00002108861],"domain_scores_gemma":[0.9997467,0.00007647564,0.00003047206,0.00004465425,0.00008202261,0.00001957184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002586192,0.0001193177,0.0004748636,0.0002040196,0.00007012974,0.0003180491,0.0002856886,0.2199695,0.08225587,0.03751638,0.009896851,0.6486307],"study_design_scores_gemma":[0.00003696288,0.00008119292,0.0002622885,0.00001230415,0.00001439282,0.0003547464,0.00002606173,0.9616279,0.01459932,0.004854016,0.0180943,0.00003648096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002480493,0.00008426895,0.9958671,0.00003373352,0.00003602845,0.000015677,0.00001005666,0.0005660186,0.000906502],"genre_scores_gemma":[0.1301145,0.000133151,0.8649929,0.00006339536,0.0000275943,0.000202123,0.00006756592,0.0001061606,0.004292588],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003578597,"threshold_uncertainty_score":0.01197159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0196356233383397,"score_gpt":0.3013723164955982,"score_spread":0.2817366931572585,"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."}}