{"id":"W2989164579","doi":"10.1007/s10846-019-01110-1","title":"Bi-objective Motion Planning Approach for Safe Motions: Application to a Collaborative Robot","year":2019,"lang":"en","type":"article","venue":"Journal of Intelligent & Robotic Systems","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Workspace; Motion planning; Task (project management); Computer science; Robot; Path (computing); Motion (physics); Field (mathematics); Human–robot interaction; Artificial intelligence; Human–computer interaction; Simulation; Control engineering; Systems engineering; Engineering; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001688612,0.0002937091,0.0006906657,0.0006276314,0.0001472977,0.0002963823,0.001031514,0.0001467349,0.000001970506],"category_scores_gemma":[0.0002935091,0.0002531054,0.0001894853,0.001142957,0.00002413021,0.0006142494,0.0001033581,0.0002799595,0.00008751914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005114328,"about_ca_system_score_gemma":0.0002318308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002447201,"about_ca_topic_score_gemma":2.218154e-7,"domain_scores_codex":[0.9969358,0.0002459708,0.001170423,0.0005041622,0.0007197864,0.0004237859],"domain_scores_gemma":[0.9962675,0.0003636861,0.001127595,0.0005627808,0.001423145,0.0002552731],"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":[0.00003222974,0.0001532851,0.0007133871,0.00009395238,0.0001323582,0.000005593358,0.002791033,0.9882732,0.0009729604,0.0034954,0.0005557204,0.002780901],"study_design_scores_gemma":[0.0004792243,0.0008499044,0.001244947,0.0004403853,0.00004373838,0.0002773416,0.0026316,0.9923497,0.0008400871,0.0002235688,0.0003176458,0.000301825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008418615,0.0007708189,0.9928452,0.0002333708,0.002560366,0.002149466,0.000005138688,0.0000611386,0.0005325958],"genre_scores_gemma":[0.4639269,0.0000102227,0.5348989,0.00008843138,0.0004996974,0.0001428502,0.000009512245,0.00003167498,0.0003919028],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.463085,"threshold_uncertainty_score":0.9999921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02500903731164935,"score_gpt":0.2877288817725395,"score_spread":0.2627198444608902,"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."}}