{"id":"W1490276931","doi":"10.1109/crv.2015.38","title":"Safe Close-Proximity and Physical Human-Robot Interaction Using Industrial Robots","year":2015,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Robot; Computer science; Human–computer interaction; Motion planning; Human–robot interaction; Robot control; Simulation; Industrial robot; Control engineering; Motion (physics); Work (physics); Artificial intelligence; Engineering; Mobile robot; Mechanical engineering","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":[0.000367873,0.0005700073,0.0004151082,0.0002766523,0.0004485413,0.0003654384,0.0007187425,0.0006990174,0.001454789],"category_scores_gemma":[0.001040434,0.0002750483,0.0003334043,0.0001676647,0.0008313041,0.0004959404,0.001399843,0.0003611672,0.0003781511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001376451,"about_ca_system_score_gemma":0.0004105594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005514979,"about_ca_topic_score_gemma":0.0006132328,"domain_scores_codex":[0.9994267,0.0001207656,0.00002472589,0.0001006664,0.0002876286,0.0000395246],"domain_scores_gemma":[0.9996122,0.0001492423,0.00009417497,0.00006840903,0.00004587945,0.00003016349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005030585,0.0002175062,0.002405313,0.0003998019,0.00004355417,0.001768863,0.001101385,0.2990007,0.312411,0.01182233,0.001222421,0.3691041],"study_design_scores_gemma":[0.00006652495,0.001132635,0.00313409,0.00004763901,0.00002822319,0.001271236,0.0001852646,0.9067046,0.07210827,0.007839288,0.007430443,0.00005174905],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03987809,0.0001867751,0.9565817,0.00004016,0.00001726907,0.00004690028,0.000005524747,0.0006235869,0.002620041],"genre_scores_gemma":[0.8506488,0.0001862929,0.1450332,0.00004409178,0.00002192051,0.000122146,0.00002737277,0.00004775585,0.00386853],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001454789,"threshold_uncertainty_score":0.004866779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1949035837763937,"score_gpt":0.3314902517470571,"score_spread":0.1365866679706634,"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."}}