{"id":"W2077489572","doi":"10.1109/cdc.2014.7039636","title":"A class of rendezvous controllers for underactuated thrust-propelled rigid bodies","year":2014,"lang":"en","type":"article","venue":"","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Rendezvous; Underactuation; Control theory (sociology); Thrust; Robustness (evolution); Integrator; Computer science; Inner loop; Rigid body; Loop (graph theory); Controller (irrigation); Engineering; Mathematics; Physics; Aerospace engineering; Control (management); Artificial intelligence; Classical mechanics","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":[],"consensus_categories":[],"category_scores_codex":[0.0006698282,0.0002236235,0.0005635832,0.0001166885,0.0001094759,0.000133968,0.0009490371,0.0001008847,0.0000449723],"category_scores_gemma":[0.0003922051,0.0001720896,0.000204318,0.0001680448,0.00006410183,0.000295719,0.0001187461,0.00008325522,0.0001112744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005924861,"about_ca_system_score_gemma":0.00008280098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001028523,"about_ca_topic_score_gemma":0.00006070325,"domain_scores_codex":[0.9980459,0.0001491841,0.0005754693,0.0004597105,0.000337214,0.000432587],"domain_scores_gemma":[0.9978148,0.0006177902,0.0003202399,0.0007877904,0.0003406378,0.0001187215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000724035,0.0007019459,0.0005905206,0.0003123595,0.001152074,0.000009988646,0.0015875,0.004647749,0.02704577,0.8073313,0.09103062,0.06486613],"study_design_scores_gemma":[0.008431708,0.0003817407,0.0002747968,0.00004089762,0.00004330419,0.000006129416,0.0001272863,0.9391633,0.004280059,0.003845813,0.04302913,0.0003757887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001649874,0.0000719221,0.9691231,0.001890821,0.0005584891,0.000964375,0.00002259965,0.000303342,0.02541546],"genre_scores_gemma":[0.9884799,0.000003581025,0.00866823,0.0003396053,0.00006466148,0.00009363708,0.00001779714,0.00001560463,0.002316974],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9868301,"threshold_uncertainty_score":0.7017609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01875055563962277,"score_gpt":0.242783176831705,"score_spread":0.2240326211920822,"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."}}