Evangelos A. Theodorou

Orcid: 0000-0002-0834-5738

Affiliations:
  • Georgia Institute of Technology, Institute for Robotics and Intelligent Machines, Atlanta, GA, USA
  • University of Washington, Departments of Computer Science and Engineering, Seattle, WA, USA
  • University of Southern California, Los Angeles, Computational Learning and Motor Control Lab, CA, USA


According to our database1, Evangelos A. Theodorou authored at least 206 papers between 2007 and 2024.

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Bibliography

2024
Solving Feynman-Kac Forward-Backward SDEs Using McKean-Markov Branched Sampling.
IEEE Trans. Autom. Control., September, 2024

Low Frequency Sampling in Model Predictive Path Integral Control.
IEEE Robotics Autom. Lett., May, 2024

Social System Inference From Noisy Observations.
IEEE Trans. Comput. Soc. Syst., February, 2024

MPPI-Generic: A CUDA Library for Stochastic Optimization.
CoRR, 2024

Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups.
CoRR, 2024

React-OT: Optimal Transport for Generating Transition State in Chemical Reactions.
CoRR, 2024

Quantum State Generation with Structure-Preserving Diffusion Model.
CoRR, 2024

Generalized Maximum Entropy Differential Dynamic Programming.
CoRR, 2024

Scaling Robust Optimization for Multi-Agent Robotic Systems: A Distributed Perspective.
CoRR, 2024

Optimal Control of Granular Material.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

A robust differential Neural ODE Optimizer.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Generalized Schrödinger Bridge Matching.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Generative Modeling with Phase Stochastic Bridge.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Distributed Differential Dynamic Programming Architectures for Large-Scale Multiagent Control.
IEEE Trans. Robotics, December, 2023

Generalization of Safe Optimal Control Actions on Networked Multiagent Systems.
IEEE Trans. Control. Netw. Syst., March, 2023

Augmented Bridge Matching.
CoRR, 2023

Generative Modeling with Phase Stochastic Bridges.
CoRR, 2023

Barrier States Theory for Safety-Critical Multi-Objective Control.
CoRR, 2023

Differentiable Robust Model Predictive Control.
CoRR, 2023

Safe Importance Sampling in Model Predictive Path Integral Control.
CoRR, 2023

Distributed Hierarchical Distribution Control for Very-Large-Scale Clustered Multi-Agent Systems.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Mirror Diffusion Models for Constrained and Watermarked Generation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Momentum Multi-Marginal Schrödinger Bridge.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

MPOGames: Efficient Multimodal Partially Observable Dynamic Games.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

A Multi-step Dynamics Modeling Framework For Autonomous Driving In Multiple Environments.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

I<sup>2</sup>SB: Image-to-Image Schrödinger Bridge.
Proceedings of the International Conference on Machine Learning, 2023

Improved Exploration for Safety-Embedded Differential Dynamic Programming Using Tolerant Barrier States.
Proceedings of the 21st International Conference on Advanced Robotics, 2023

2022
Spatiotemporal Costmap Inference for MPC Via Deep Inverse Reinforcement Learning.
IEEE Robotics Autom. Lett., 2022

Learning Risk-Aware Costmaps for Traversability in Challenging Environments.
IEEE Robotics Autom. Lett., 2022

Safety Embedded Differential Dynamic Programming Using Discrete Barrier States.
IEEE Robotics Autom. Lett., 2022

Safety Embedded Control of Nonlinear Systems via Barrier States.
IEEE Control. Syst. Lett., 2022

Distributed Model Predictive Covariance Steering.
CoRR, 2022

Gaussian Process Barrier States for Safe Trajectory Optimization and Control.
CoRR, 2022

Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian.
CoRR, 2022

Distributed Differential Dynamic Programming Architectures for Large-Scale Multi-Agent Control.
CoRR, 2022

Safety in Augmented Importance Sampling: Performance Bounds for Robust MPPI.
CoRR, 2022

Multimodal Maximum Entropy Dynamic Games.
CoRR, 2022

Stochastic spatio-temporal optimization for control and co-design of systems in robotics and applied physics.
Auton. Robots, 2022

Decentralized Safe Multi-agent Stochastic Optimal Control using Deep FBSDEs and ADMM.
Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

Parameterized Differential Dynamic Programming.
Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

Deep Generalized Schrödinger Bridge.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Risk-sensitive MPCs with Deep Distributional Inverse RL for Autonomous Driving.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Trajectory Distribution Control for Model Predictive Path Integral Control using Covariance Steering.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Optimal-Horizon Model Predictive Control with Differential Dynamic Programming.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Maximum Entropy Differential Dynamic Programming.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Deep Graphic FBSDEs for Opinion Dynamics Stochastic Control.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Constrained Covariance Steering Based Tube-MPPI.
Proceedings of the American Control Conference, 2022

Barrier States Embedded Iterative Dynamic Game for Robust and Safe Trajectory Optimization.
Proceedings of the American Control Conference, 2022

2021
Discrete-Time Differential Dynamic Programming on Lie Groups: Derivation, Convergence Analysis, and Numerical Results.
IEEE Trans. Autom. Control., 2021

Schrödinger Approach to Optimal Control of Large-Size Populations.
IEEE Trans. Autom. Control., 2021

Robust Model Predictive Path Integral Control: Analysis and Performance Guarantees.
IEEE Robotics Autom. Lett., 2021

Leveraging Stochasticity for Open Loop and Model Predictive Control of Spatio-Temporal Systems.
Entropy, 2021

Improving Model Predictive Path Integral using Covariance Steering.
CoRR, 2021

Generalization of Safe Optimal Control Actions on Networked Multi-Agent Systems.
CoRR, 2021

Deep L<sup>1</sup> Stochastic Optimal Control Policies for Planetary Soft-landing.
CoRR, 2021

Distributed Algorithms for Linearly-Solvable Optimal Control in Networked Multi-Agent Systems.
CoRR, 2021

Variational Inference MPC using Tsallis Divergence.
Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Distributed Covariance Steering with Consensus ADMM for Stochastic Multi-Agent Systems.
Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Second-Order Neural ODE Optimizer.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adaptive Risk Sensitive Model Predictive Control with Stochastic Search.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Contraction ℒ<sub>1</sub>-Adaptive Control using Gaussian Processes.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Approximate Inverse Reinforcement Learning from Vision-based Imitation Learning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Constrained Differential Dynamic Programming Revisited.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Dynamic Game Theoretic Neural Optimizer.
Proceedings of the 38th International Conference on Machine Learning, 2021

Large-Scale Multi-Agent Deep FBSDEs.
Proceedings of the 38th International Conference on Machine Learning, 2021

DDPNOpt: Differential Dynamic Programming Neural Optimizer.
Proceedings of the 9th International Conference on Learning Representations, 2021

NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-end Learning and Control.
Proceedings of the 9th International Conference on Learning Representations, 2021

Forward-Backward Rapidly-Exploring Random Trees for Stochastic Optimal Control.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Receding Horizon Differential Dynamic Programming Under Parametric Uncertainty.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

HJB Based Optimal Safe Control using Control Barrier Functions.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Cooperative Path Integral Control for Stochastic Multi-Agent Systems.
Proceedings of the 2021 American Control Conference, 2021

Compositionality of Linearly Solvable Optimal Control in Networked Multi-Agent Systems.
Proceedings of the 2021 American Control Conference, 2021

2020
Aggressive Perception-Aware Navigation Using Deep Optical Flow Dynamics and PixelMPC.
IEEE Robotics Autom. Lett., 2020

Imitation learning for agile autonomous driving.
Int. J. Robotics Res., 2020

Multi-agent Deep FBSDE Representation For Large Scale Stochastic Differential Games.
CoRR, 2020

RL<sub>1</sub>-GP: Safe Simultaneous Learning and Control.
CoRR, 2020

Adaptive CVaR Optimization for Dynamical Systems with Path Space Stochastic Search.
CoRR, 2020

A Differential Game Theoretic Neural Optimizer for Training Residual Networks.
CoRR, 2020

Forward-Backward RRT: Branched Sampled FBSDEs for Stochastic Optimal Control.
CoRR, 2020

Non-convex Optimization via Adaptive Stochastic Search for End-to-End Learning and Control.
CoRR, 2020

$\mathcal{L}_1$-$\mathcal{GP}$: $\mathcal{L}_1$ Adaptive Control with Bayesian Learning.
CoRR, 2020

High-Relative Degree Stochastic Control Lyapunov and Barrier Functions.
CoRR, 2020

Differential Dynamic Programming Neural Optimizer.
CoRR, 2020

Deep Learning Tubes for Tube MPC.
CoRR, 2020

Deep Learning Tubes for Tube MPC.
Proceedings of the Robotics: Science and Systems XVI, 2020

Spatio-Temporal Stochastic Optimization: Theory and Applications to Optimal Control and Co-Design.
Proceedings of the Robotics: Science and Systems XVI, 2020

Feynman-Kac Neural Network Architectures for Stochastic Control Using Second-Order FBSDE Theory.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

L1-GP: L1 Adaptive Control with Bayesian Learning.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

ℒ1-Adaptive MPPI Architecture for Robust and Agile Control of Multirotors.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Bayesian Learning-Based Adaptive Control for Safety Critical Systems.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Constrained Sampling-based Trajectory Optimization using Stochastic Approximation.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Sampling-Based Nonlinear Stochastic Optimal Control for Neuromechanical Systems.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs.
Proceedings of the 4th Conference on Robot Learning, 2020

Stabilizing Optimal Density Control of Nonlinear Agents with Multiplicative Noise.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Nonlinear Covariance Control via Differential Dynamic Programming.
Proceedings of the 2020 American Control Conference, 2020

2019
On Mean Field Games for Agents With Langevin Dynamics.
IEEE Trans. Control. Netw. Syst., 2019

Numerical Trajectory Optimization for Stochastic Mechanical Systems.
SIAM J. Sci. Comput., 2019

Vision-Based High-Speed Driving With a Deep Dynamic Observer.
IEEE Robotics Autom. Lett., 2019

Stochastic Differential Games: A Sampling Approach via FBSDEs.
Dyn. Games Appl., 2019

Deep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective.
CoRR, 2019

Deep 2FBSDEs for Systems with Control Multiplicative Noise.
CoRR, 2019

Locally Weighted Regression Pseudo-Rehearsal for Online Learning of Vehicle Dynamics.
CoRR, 2019

Neural Network Architectures for Stochastic Control using the Nonlinear Feynman-Kac Lemma.
CoRR, 2019

Learning Deep Stochastic Optimal Control Policies Using Forward-Backward SDEs.
Proceedings of the Robotics: Science and Systems XV, 2019

Autonomous Hybrid Ground/Aerial Mobility in Unknown Environments.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Hierarchical optimization for Whole-Body Control of Wheeled Inverted Pendulum Humanoids.
Proceedings of the International Conference on Robotics and Automation, 2019

Early Failure Detection of Deep End-to-End Control Policy by Reinforcement Learning.
Proceedings of the International Conference on Robotics and Automation, 2019

Ensemble Bayesian Decision Making with Redundant Deep Perceptual Control Policies.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

The Science of Autonomy: A Holistic View at the Intersection of Learning, Control and Physics.
Proceedings of the 16th International Conference on Informatics in Control, 2019

Locally Weighted Regression Pseudo-Rehearsal for Adaptive Model Predictive Control.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Perceptual Attention-based Predictive Control.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Variational Optimization Based Reinforcement Learning for Infinite Dimensional Stochastic Systems.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Deep Forward-Backward SDEs for Min-max Control.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Information Theoretic Model Predictive Control on Jump Diffusion Processes.
Proceedings of the 2019 American Control Conference, 2019

Accelerating Imitation Learning with Predictive Models.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Information-Theoretic Model Predictive Control: Theory and Applications to Autonomous Driving.
IEEE Trans. Robotics, 2018

Efficient Reinforcement Learning via Probabilistic Trajectory Optimization.
IEEE Trans. Neural Networks Learn. Syst., 2018

Stochastic L1-optimal control via forward and backward sampling.
Syst. Control. Lett., 2018

Propagating Uncertainty through the tanh Function with Application to Reservoir Computing.
CoRR, 2018

Model-Based Imitation Learning with Accelerated Convergence.
CoRR, 2018

Safe end-to-end imitation learning for model predictive control.
CoRR, 2018

A mean-field game model for homogeneous flocking.
CoRR, 2018

MPC-Inspired Neural Network Policies for Sequential Decision Making.
CoRR, 2018

Stochastic optimal control via forward and backward stochastic differential equations and importance sampling.
Autom., 2018

Model-Based Stochastic Search for Large Scale Optimization of Multi-Agent UAV Swarms.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Robust Sampling Based Model Predictive Control with Sparse Objective Information.
Proceedings of the Robotics: Science and Systems XIV, 2018

Agile Autonomous Driving using End-to-End Deep Imitation Learning.
Proceedings of the Robotics: Science and Systems XIV, 2018

Semi-parametric Approaches to Learning in Model-Based Hierarchical Control of Complex Systems.
Proceedings of the 2018 International Symposium on Experimental Robotics, 2018

Best Response Model Predictive Control for Agile Interactions Between Autonomous Ground Vehicles.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Safe Learning of Quadrotor Dynamics Using Barrier Certificates.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Seizure Reduction using Model Predictive Control.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

Linearly Solvable Stochastic Optimal Control for Infinite-Dimensional Systems.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Path Integral Control on Lie Groups.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

A Fixed-Architecture Framework for Stochastic Nonlinear Controller Synthesis.
Proceedings of the 2018 Annual American Control Conference, 2018

A Stochastic Differential Equation Framework for Guiding Online User Activities in Closed Loop.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Agile Off-Road Autonomous Driving Using End-to-End Deep Imitation Learning.
CoRR, 2017

Autonomous Racing with AutoRally Vehicles and Differential Games.
CoRR, 2017

A Unifying Framework for Guiding Point Processes with Stochastic Intensity Functions.
CoRR, 2017

Aggressive Deep Driving: Model Predictive Control with a CNN Cost Model.
CoRR, 2017

Model predictive PseudoSpectral Optimal Control with semi-parametric dynamics.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Information theoretic MPC for model-based reinforcement learning.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Variational Policy for Guiding Point Processes.
Proceedings of the 34th International Conference on Machine Learning, 2017

Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control.
Proceedings of the 34th International Conference on Machine Learning, 2017

Evolving cost functions for model predictive control of multi-agent UAV combat swarms.
Proceedings of the Genetic and Evolutionary Computation Conference, 2017

Aggressive Deep Driving: Combining Convolutional Neural Networks and Model Predictive Control.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

Belief space stochastic control under unknown dynamics.
Proceedings of the 2017 American Control Conference, 2017

Stochastic control of systems with control multiplicative noise using second order FBSDEs.
Proceedings of the 2017 American Control Conference, 2017

2016
Steering Opinion Dynamics in Information Diffusion Networks.
CoRR, 2016

Adaptive Probabilistic Trajectory Optimization via Efficient Approximate Inference.
CoRR, 2016

Aggressive driving with model predictive path integral control.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Cross-entropy optimization for neuromodulation.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016

Stochastic Game Theoretic trajectory optimization in continuous time.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Differential Dynamic Programming for time-delayed systems.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Game-theoretic and risk-sensitive stochastic optimal control via forward and backward stochastic differential equations.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Spectral variational integrators for trajectory optimization under parametric uncertainties and stochastic disturbances.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Infinite dimensional control of doubly stochastic Jump Diffusions.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Nonlinear-nonquadratic optimal and inverse optimal control for stochastic dynamical systems.
Proceedings of the 2016 American Control Conference, 2016

Learning optimal control via forward and backward stochastic differential equations.
Proceedings of the 2016 American Control Conference, 2016

Stochastic Optimal Control using polynomial chaos variational integrators.
Proceedings of the 2016 American Control Conference, 2016

2015
Nonlinear Stochastic Control and Information Theoretic Dualities: Connections, Interdependencies and Thermodynamic Interpretations.
Entropy, 2015

Model Predictive Path Integral Control using Covariance Variable Importance Sampling.
CoRR, 2015

Model Based Reinforcement Learning with Final Time Horizon Optimization.
CoRR, 2015

Sample Efficient Path Integral Control under Uncertainty.
CoRR, 2015

Robust Trajectory Optimization: A Cooperative Stochastic Game Theoretic Approach.
Proceedings of the Robotics: Science and Systems XI, Sapienza University of Rome, 2015

Sample Efficient Path Integral Control under Uncertainty.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Game Theoretic continuous time Differential Dynamic Programming.
Proceedings of the American Control Conference, 2015

Data-driven differential dynamic programming using Gaussian processes.
Proceedings of the American Control Conference, 2015

2014
Model-based Path Integral Stochastic Control: A Bayesian Nonparametric Approach.
CoRR, 2014

Nonparametric Kullback-Leibler Stochastic Control.
CoRR, 2014

Probabilistic Differential Dynamic Programming.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Continuous-time differential dynamic programming with terminal constraints.
Proceedings of the 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2014

Nonparametric infinite horizon Kullback-Leibler stochastic control.
Proceedings of the 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2014

Information-theoretic stochastic optimal control via incremental sampling-based algorithms.
Proceedings of the 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2014

2013
From dynamic movement primitives to associative skill memories.
Robotics Auton. Syst., 2013

Time varying nonlinear Policy Gradients.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Convexity of optimal linear controller design.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

The δ - sensitivity and its application to stochastic optimal control of nonlinear diffusions.
Proceedings of the American Control Conference, 2013

Multi-robot active SLAM with relative entropy optimization.
Proceedings of the American Control Conference, 2013

Free energy based policy gradients.
Proceedings of the 2013 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2013

2012
Reinforcement Learning With Sequences of Motion Primitives for Robust Manipulation.
IEEE Trans. Robotics, 2012

Model-Free Reinforcement Learning of Impedance Control in Stochastic Environments.
IEEE Trans. Auton. Ment. Dev., 2012

Movement Segmentation and Recognition for Imitation Learning.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Tendon-Driven Variable Impedance Control Using Reinforcement Learning.
Proceedings of the Robotics: Science and Systems VIII, 2012

Tendon-driven control of biomechanical and robotic systems: A path integral reinforcement learning approach.
Proceedings of the IEEE International Conference on Robotics and Automation, 2012

Reduced dimensionality control for the ACT hand.
Proceedings of the IEEE International Conference on Robotics and Automation, 2012

Relative entropy and free energy dualities: Connections to Path Integral and KL control.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

Stochastic optimal control for nonlinear markov jump diffusion processes.
Proceedings of the American Control Conference, 2012

2011
Learning variable impedance control.
Int. J. Robotics Res., 2011

Learning motion primitive goals for robust manipulation.
Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

Movement segmentation using a primitive library.
Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

Learning to grasp under uncertainty.
Proceedings of the IEEE International Conference on Robotics and Automation, 2011

Skill learning and task outcome prediction for manipulation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2011

STOMP: Stochastic trajectory optimization for motion planning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2011

Reinforcement learning of impedance control in stochastic force fields.
Proceedings of the 1st International Conference on Development and Learning and on Epigenetic Robotics, 2011

Neuromuscular stochastic optimal control of a tendon driven index finger model.
Proceedings of the American Control Conference, 2011

Path integral control and bounded rationality.
Proceedings of the 2011 IEEE Symposium on Adaptive Dynamic Programming And Reinforcement Learning, 2011

2010
Learning Policy Improvements with Path Integrals.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

A Generalized Path Integral Control Approach to Reinforcement Learning.
J. Mach. Learn. Res., 2010

Variable Impedance Control - A Reinforcement Learning Approach.
Proceedings of the Robotics: Science and Systems VI, 2010

Reinforcement learning of motor skills in high dimensions: A path integral approach.
Proceedings of the IEEE International Conference on Robotics and Automation, 2010

Reinforcement learning of full-body humanoid motor skills.
Proceedings of the 10th IEEE-RAS International Conference on Humanoid Robots, 2010

Stochastic Differential Dynamic Programming.
Proceedings of the American Control Conference, 2010

2009
Path integral-based stochastic optimal control for rigid body dynamics.
Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2009

2007
A Kalman filter for robust outlier detection.
Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 29, 2007

Learning an Outlier-Robust Kalman Filter.
Proceedings of the Machine Learning: ECML 2007, 2007


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