Evangelos A. Theodorou

収録論文 48本 ・ フィジカルAI/ロボット学習

※arXiv著者名で収集。同姓同名の別人の論文が含まれる場合があります。

論文

• Beyond Pure Sampling: Hybrid Optimization Mechanisms for Non-Convex Model Predictive Control
  2026/6/1
• Deep-Unfolded Coordination
  2026/6/1
• Sampling-Based Control via Entropy-Regularized Optimal Transport
  2026/5/1
• Multistep Belief Space Dynamics Learning For Risk-Aware Control
  2026/5/1
• Fundamental Limits for Sensor-Based Control via the Gibbs Variational Principle
  2026/3/1
• cuNRTO: GPU-Accelerated Nonlinear Robust Trajectory Optimization
  2026/3/1
• Asynchronous Distributed Multi-Robot Motion Planning Under Imperfect Communication
  2025/11/1
• Scaling Robust Optimization for Swarms: A Distributed Perspective
  2025/8/1
• Nonlinear Robust Optimization for Planning and Control
  2025/4/1
• Barrier-Riccati Synthesis for Nonlinear Safe Control with Expanded Region of Attraction
  2025/4/1
• Dynamics Modeling using Visual Terrain Features for High-Speed Autonomous Off-Road Driving
  2024/12/1
• Operator Splitting Covariance Steering for Safe Stochastic Nonlinear Control
  2024/11/1
• MPPI-Generic: A CUDA Library for Stochastic Trajectory Optimization
  2024/9/1
• Low Frequency Sampling in Model Predictive Path Integral Control
  2024/4/1
• Scaling Robust Optimization for Multi-Agent Robotic Systems: A Distributed Perspective
  2024/2/1
• Differentiable Robust Model Predictive Control
  2023/8/1
• A Multi-step Dynamics Modeling Framework For Autonomous Driving In Multiple Environments
  2023/5/1
• Distributed Hierarchical Distribution Control for Very-Large-Scale Clustered Multi-Agent Systems
  2023/5/1
• Improved Exploration for Safety-Embedded Differential Dynamic Programming Using Tolerant Barrier States
  2023/3/1
• Gaussian Process Barrier States for Safe Trajectory Optimization and Control
  2022/12/1
• Distributed Model Predictive Covariance Steering
  2022/12/1
• MPOGames: Efficient Multimodal Partially Observable Dynamic Games
  2022/10/1
• Parameterized Differential Dynamic Programming
  2022/4/1
• Decentralized Safe Multi-agent Stochastic Optimal Control using Deep FBSDEs and ADMM
  2022/2/1
• Multimodal Maximum Entropy Dynamic Games
  2022/1/1
• Spatiotemporal Costmap Inference for MPC via Deep Inverse Reinforcement Learning
  2022/1/1
• Optimal-Horizon Model-Predictive Control with Differential Dynamic Programming
  2021/11/1
• Maximum Entropy Differential Dynamic Programming
  2021/10/1
• Learning Risk-aware Costmaps for Traversability in Challenging Environments
  2021/7/1
• Safety Embedded Differential Dynamic Programming Using Discrete Barrier States
  2021/5/1
• Distributed Algorithms for Linearly-Solvable Optimal Control in Networked Multi-Agent Systems
  2021/2/1
• Stochastic Spatio-Temporal Optimization for Control and Co-Design of Systems in Robotics and Applied Physics
  2021/2/1
• Adaptive Risk Sensitive Model Predictive Control with Stochastic Search
  2020/9/1
• Cooperative Path Integral Control for Stochastic Multi-Agent Systems
  2020/9/1
• Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs
  2020/9/1
• Approximate Inverse Reinforcement Learning from Vision-based Imitation Learning
  2020/4/1
• Deep Learning Tubes for Tube MPC
  2020/2/1
• Aggressive Perception-Aware Navigation using Deep Optical Flow Dynamics and PixelMPC
  2020/1/1
• Bayesian Learning-Based Adaptive Control for Safety Critical Systems
  2019/10/1
• Locally Weighted Regression Pseudo-Rehearsal for Online Learning of Vehicle Dynamics
  2019/5/1
• Perceptual Attention-based Predictive Control
  2019/4/1
• Learning Deep Stochastic Optimal Control Policies using Forward-Backward SDEs
  2019/2/1
• Vision-Based High Speed Driving with a Deep Dynamic Observer
  2018/12/1
• Ensemble Bayesian Decision Making with Redundant Deep Perceptual Control Policies
  2018/11/1
• Hierarchical Optimization for Whole-Body Control of Wheeled Inverted Pendulum Humanoids
  2018/10/1
• Autonomous Racing with AutoRally Vehicles and Differential Games
  2017/7/1
• Aggressive Deep Driving: Model Predictive Control with a CNN Cost Model
  2017/7/1
• Information Theoretic Model Predictive Control: Theory and Applications to Autonomous Driving
  2017/7/1