Residual Dynamics Learning

Ask about this topic

Overview

Residual dynamics learning studies how to correct an approximate physics model using the differences between its predictions and real or simulated behavior. Common approaches learn these corrections with neural networks, Gaussian processes, sparse system identification, or Koopman models, often preserving physical structure and updating online as conditions change. The resulting models are used in settings such as robot control, model predictive control, vehicle navigation, and sim-to-real transfer, with evaluation on trajectory tracking, long-horizon prediction, and contact or disturbance tasks. A central challenge is balancing expressive corrections that generalize across changing conditions with models that remain interpretable, data-efficient, and fast enough for real-time control.

Latest papers

CardsList

28 papers7 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

  1. Sensitivity-Orthogonal Residual Learning for Adaptive Sideslip and Cornering Stiffness Estimation

    Oct 20, 2026Kyoungtae Ji, Dongyeol Won, Kyoungseok HanVehicle DynamicsResidual Dynamics Learning

    Department of Automotive Engineering, Hanyang University, Seoul, South Korea · Department of Automotive Engineering (Automotive-Computer Convergence), Hanyang University, Seoul, South Korea

  2. Contact-UAN: Unsupervised Actuator Networks as a Residual World Model for Humanoid Control

    Oct 13, 2026Nolan Fey, Khai Nguyen, Yash Prabhu +2Humanoid Robot ControlHumanoid Robot Locomotion

    Improbable AI Lab, MIT

  3. Scalable Identification of Physics-Based and Neural Dynamics from Partial Measurements

    Oct 12, 2026Yibo Zhou, Johannes KöhlerNonlinear System IdentificationSystem Identification

    Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden · Department of Mechanical Engineering, Imperial College London, London, United Kingdom

  4. RACER: Residual-Adaptive Closed-Loop Estimation for Sampling-Based Planning in Wheeled-Quadruped Racing

    Oct 5, 2026Yuxiang Liu, Marla Eisman, Lizhi Yang +2Residual Dynamics LearningSim-to-Real Transfer

    University of California, Berkeley, CA, USA. · California Institute of Technology, Pasadena, CA, USA.

  5. Optimal Control with Learned Critics under Unmodeled State Dependencies

    Oct 4, 2026Philipp Schoch, Markus RyllResidual Dynamics LearningRobot Dynamics Learning

    Autonomous Aerial Systems Lab Technical University of Munich

  6. Simulation-Free Learning of Population Dynamics with Wasserstein Lagrangian Residuals

    Oct 2, 2026Fedor Sergeev, Markus Heinonen, Daniel Waxman +4Dynamical SystemsResidual Dynamics Learning

    Basis Research Institute · ETH Zurich · Helmholtz AI +2

  7. EMPIRIC: Experiment-Driven Learning of Residual World Models for Robot Planning

    Sep 28, 2026Yichao Liang, Amber Li, Dat Nguyen +13World Models for RoboticsResidual Dynamics Learning

    Basis Research Institute · University of Cambridge · Carnegie Mellon University +6

  8. Task-Oriented Active Learning of Residual Dynamics for Model Predictive Path Integral Control

    Sep 16, 2026Nobuaki Aoki, Hojin Lee, Stefan Sosnowski +1Residual LearningResidual Dynamics Learning

    Chair of Information-oriented Control (ITR), Department of Electrical and Computer Engineering, Technical University of Munich, Munich, Germany · Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University of Munich, Munich, Germany

  9. Calibrate Once, Fly Any Team: Residual-Grounded Low-Fidelity Training for Cooperative Drone Swarms

    Sep 15, 2026Maxim Mednikov, Oren GalAerial RoboticsSwarm Robotics

    Swarm & AI Lab (SAIL), University of Haifa, Israel

  10. Control-Oriented Learning for Dynamic Tracking and Stability Analysis of Soft Pneumatic Actuators

    Aug 25, 2026Nithin S. Kumar, Eric J. BarthExtended Dynamic Mode DecompositionSoft Pneumatic Actuators

    Department of Mechanical Engineering, Vanderbilt University, Nashville TN 37215

  11. NeSAM: Neuro-Symbolic Kinodynamics with Soil Adaptation for Off-Road Mobility

    Aug 21, 2026Chenhui Pan, Tong Xu, Francesco Cancelliere +1Terrain-Aware Robot LocomotionRobot Dynamics Learning

    Department of Computer Science, George Mason University, USA · Department of Electrical, Electronic and Computer Engineering, University of Catania, Italy

  12. Learning Physics-Guided Residual Dynamics for Deformable Object Simulation

    Jul 15, 2026Shivansh Patel, Kaifeng Zhang, Sanjay Pokkali +2Residual LearningResidual Dynamics Learning

    UIUC · Columbia University

  13. Flatness-Preserving Residual Learning for Real-Time Tight Quadrotor Formation Flight

    Jul 14, 2026Pei-An Hsieh, Fengjun Yang, Nikolai Matni +1Multi-Robot Formation ControlResidual Dynamics Learning

    1GRASP Laboratory, University of Pennsylvania, PA, USA

  14. Continual Robot Policy Learning via Variational Neural Dynamics

    Jun 25, 2026Jiaxu Xing, Zhiyuan Zhu, Yunfan Ren +4Robot Policy LearningRobot Policy Adaptation

    Robotics and Perception Group, University of Zurich

  15. Physics-Aware Sparse Learning and Selective Online Adaptation for Euler-Lagrange Robot Dynamics

    Jun 8, 2026Rishabh Dev Yadav, Samaksh Ujjawal, Sihao Sun +2Robotic ControlRobot Dynamics Identification

    Department of Computer Science, The University of Manchaster, U.K. · Department of Cognitive Robotics, Delft University of Technology, Netherlands · International Institute of Information Technology Hyderabad. +1

  16. Learning Cross-Coupled and Regime Dependent Dynamics for Aerial Manipulation

    May 14, 2026Rishabh Dev Yadav, Samaksh Ujjawal, Shivansh Pratap Singh +4Aerial RoboticsOnline System Identification

    Department of Computer Science, The University of Manchaster, U.K. · Department of Cognitive Robotics, Delft University of Technology, Netherlands · International Institute of Information Technology Hyderabad. +1

  17. Energy-based Regularization for Learning Residual Dynamics in Neural MPC for Omnidirectional Aerial Robots

    Apr 16, 2026Johannes Kübel, Henrik Krauss, Jinjie Li +1Aerial RoboticsResidual Dynamics Learning

    DRAGON Lab, Department of Mechanical Engineering, The University of Tokyo, Tokyo 113-8656, Japan · Department of Advanced Interdisciplinary Studies, The University of Tokyo, Tokyo 153-8904, Japan

  18. RK-MPC: Residual Koopman Model Predictive Control for Quadruped Locomotion in Offroad Environments

    Apr 5, 2026Sriram S. K. S. Narayanan, Umesh VaidyaModel Predictive ControlQuadruped Locomotion

    Department of Mechanical Engineering, Clemson University, Clemson, SC 29630, USA

  19. Model Predictive Path Integral PID Control for Learning-Based Path Following

    Mar 31, 2026Teruki Kato, Koshi Oishi, Seigo ItoNonlinear MPCResidual Dynamics Learning

    Toyota Central R&D Labs., Inc., Nagakute 480-1192, Japan

  20. RAFL: Generalizable Sim-to-Real of Soft Robots with Residual Acceleration Field Learning

    Mar 23, 2026Dong Heon Cho, Boyuan ChenSynthetic-to-Real Domain AdaptationResidual Dynamics Learning

    Department of Computer Science, Duke University, 308 Research Dr., Durham, 27705, NC, USA · Department of Mechanical Engineering and Material Science, 121 Hudson Hall, Durham, 27708, NC, USA · Department of Electrical and Computer Engineering, 100 Science Dr., Durham, 27708, NC, USA

  21. ResNets of All Shapes and Sizes: Convergence of Training Dynamics in the Large-scale Limit

    Mar 18, 2026Louis-Pierre Chaintron, Lénaïc Chizat, Javier MaassDynamical Mean-Field TheoryNeural Network Training Dynamics

    École Polytechnique Fédérale de Lausanne (EPFL), Institute of Mathematics, 1015 Lausanne, Switzerland.

  22. Real-Time Online Learning for Model Predictive Control using a Spatio-Temporal Gaussian Process Approximation

    Mar 18, 2026Lars Bartels, Amon Lahr, Andrea Carron +1Model Predictive ControlGaussian Processes

    Institute for Dynamic Systems and Control, ETH Zürich, CH-8092 Zürich, Switzerland.

  23. Vision-Augmented On-Track System Identification for Autonomous Racing via Attention-Based Priors and Iterative Neural Correction

    Mar 10, 2026Zhiping Wu, Cheng Hu, Yiqin Wang +2Nonlinear System IdentificationVehicle Dynamics

    State Key Laboratory of Industrial, Zhejiang University, Hangzhou 310027, China

  24. Adaptive SINDy: Residual Force System Identification Based UAV Disturbance Rejection

    Mar 9, 2026Fawad Mehboob, Amir Atef Habel, Roohan Ahmed Khan +3Disturbance RejectionRobust Control

    Intelligent Space Robotics Laboratory, Center for Digital Engineering, Skolkovo Institute of Science and Technology, Moscow, Russia.

  25. STRIDE: Structured Lagrangian and Stochastic Residual Dynamics via Flow Matching

    Mar 9, 2026Prakrut Kotecha, Ganga Nair B, Shishir KolathayaLagrangian Neural NetworksRobot Dynamics Learning

    the Robert Bosch Center for Cyber-Physical Systems, Indian Institute of Science, Bengaluru · the Robert Bosch Center for Cyber-Physical Systems and the Department of Computer Science & Automation, Indian Institute of Science, Bengaluru

  26. Physics-infused Learning for Aerial Manipulator in Winds and Near-Wall Environments

    Mar 8, 2026Yiming Zhang, Junyi GengAerial ManipulationRobust Control

    The Pennsylvania State University, University Park, PA 16802

  27. TEFL: Prediction-Residual-Guided Rolling Forecasting for Multi-Horizon Time Series

    Feb 26, 2026Xiannan Huang, Shen Fang, Shuhan Qiu +3Time Series ForecastingResidual Dynamics Learning

    Key Laboratory of Road and Traffic Engineering, Ministry of Education Tongji University, Shanghai China · Research Center for Scientific Data Hub, Zhejiang Lab, Hangzhou, China · The College of Computer Science, Tongji University, Shanghai China

  28. Nonplanar Model Predictive Control for Autonomous Vehicles with Recursive Sparse Gaussian Process Dynamics

    Feb 18, 2026Ahmad Amine, Kabir Puri, Viet-Anh Le +1Model Predictive ControlResidual Dynamics Learning

    Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA