{"id":"W4383875147","doi":"10.1109/icat57854.2023.10171197","title":"Vision-guided Unified Task and Motion Planning for Multiple Robots in Cluttered Environments","year":2023,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Workspace; Motion planning; Computer science; Robot; Task (project management); Scheduling (production processes); Automotive industry; Motion (physics); Robot kinematics; Robotic arm; Artificial intelligence; Mobile robot; Distributed computing; Real-time computing; Human–computer interaction; Engineering; Systems 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":[0.0006248096,0.0007137178,0.0006905135,0.0005794526,0.0005808043,0.0005542603,0.001173938,0.0006968002,0.0008890057],"category_scores_gemma":[0.001216644,0.0005264409,0.0006438856,0.0006406954,0.001020196,0.00098458,0.0015857,0.0006369135,0.0001835993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007366756,"about_ca_system_score_gemma":0.001561596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007486748,"about_ca_topic_score_gemma":0.009461898,"domain_scores_codex":[0.9996141,0.00007690927,0.00001985314,0.0001118134,0.0001003111,0.00007699632],"domain_scores_gemma":[0.9995715,0.0001681349,0.00008484724,0.0000618719,0.00006640514,0.00004727592],"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":[0.00007241311,0.00002943661,0.0002603052,0.00004688267,0.00001984515,0.00007653003,0.0001044581,0.9465786,0.006704384,0.005451234,0.0003385449,0.04031736],"study_design_scores_gemma":[0.000008227121,0.00003895254,0.0001180303,0.000003304823,0.000004672622,0.00001262395,0.00002159655,0.9936329,0.001356822,0.004498552,0.0002996542,0.00000471791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0172853,0.00008700675,0.9815422,0.00003563314,0.000007974223,0.00002854593,0.00001737391,0.0003170753,0.0006789343],"genre_scores_gemma":[0.6367942,0.0001177698,0.3610712,0.0000505817,0.00001210082,0.0001729042,0.0001145306,0.0001020248,0.001564751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007486748,"threshold_uncertainty_score":0.01488638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04820163388764171,"score_gpt":0.3024940930785046,"score_spread":0.2542924591908629,"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."}}