{"id":"W4407948601","doi":"10.1109/lra.2025.3546106","title":"DR-MPC: Deep Residual Model Predictive Control for Real-World Social Navigation","year":2025,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Christian Studies; University of Toronto","funders":"","keywords":"Model predictive control; Residual; Control (management); Computer science; Artificial intelligence; Algorithm","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":[0.0005209826,0.0007784824,0.0005304837,0.0002444679,0.0002894877,0.0005142449,0.001255156,0.0006802208,0.00187603],"category_scores_gemma":[0.001713025,0.000378568,0.0003663275,0.0001977361,0.0007319287,0.0006406594,0.001151224,0.001552764,0.0004576138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005480152,"about_ca_system_score_gemma":0.001101245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01130035,"about_ca_topic_score_gemma":0.01083935,"domain_scores_codex":[0.9997824,0.00004614002,0.000008780769,0.00006138064,0.00006188577,0.00003946321],"domain_scores_gemma":[0.9995306,0.0001913709,0.00006630838,0.00006439866,0.0001031279,0.00004427816],"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":[0.00005525506,0.0000405264,0.0004668011,0.00003715073,0.00002144985,0.00004249626,0.00004241787,0.9545035,0.00195193,0.003483007,0.001616524,0.03773887],"study_design_scores_gemma":[0.000003641907,0.00001168509,0.0000290136,0.000001883999,0.000001428535,0.00000289015,0.000001894561,0.9986559,0.0002389241,0.0008307961,0.0002202689,0.000001709844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01843623,0.0002830444,0.9746956,0.000291868,0.00008396824,0.00003224391,0.00007601418,0.002666407,0.003434689],"genre_scores_gemma":[0.9060342,0.0001636403,0.08964685,0.000235145,0.00003975731,0.00009985134,0.0001888668,0.000134708,0.003456981],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01130035,"threshold_uncertainty_score":0.02246916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02431091020796528,"score_gpt":0.3480323701422947,"score_spread":0.3237214599343294,"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."}}