publications

2024

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    Learning a Generalizable Trajectory Sampling Distribution for Model Predictive Control
    Thomas Power, and Dmitry Berenson
    IEEE Transactions on Robotics, 2024
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    Constrained Stein Variational Trajectory Optimization
    Thomas Power, and Dmitry Berenson
    IEEE Transactions on Robotics (Conditionally Accepted), 2024

2023

  1. Task-space Kernels for Diverse Stein Variational MPC
    Madhav Shekhar Sharma , Thomas Power, and Dmitry Berenson
    In IROS 2023 Workshop on Differentiable Probabilistic Robotics: Emerging Perspectives on Robot Learning , 2023
  2. Sampling Constrained Trajectories Using Composable Diffusion Models
    Thomas Power, Rana Soltani-Zarrin , Soshi Iba , and 1 more author
    In IROS 2023 Workshop on Differentiable Probabilistic Robotics: Emerging Perspectives on Robot Learning , 2023

2022

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    Variational Inference MPC using Normalizing Flows and Out-of-Distribution Projection
    Thomas Power, and Dmitry Berenson
    In Robotics: Science and Systems , 2022
  2. Improving Sample-based MPC with Normalizing Flows & Out-of-distribution Projection
    Thomas Power, and Dmitry Berenson
    In Planning with Implicit Neural Representations of Geometry Workshop, ICRA , 2022

2021

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    Keep It Simple: Data-Efficient Learning for Controlling Complex Systems With Simple Models
    Thomas Power, and Dmitry Berenson
    IEEE Robotics and Automation Letters, 2021
  2. Variational Inference MPC for Robot Motion with Normalizing Flows
    Thomas Power, and Dmitry Berenson
    In Robot Learning Workshop, NeurIPS , 2021

2020

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    Learning When to Trust a Dynamics Model for Planning in Reduced State Spaces
    Dale McConachie , Thomas Power, Peter Mitrano , and 1 more author
    IEEE Robotics and Automation Letters, 2020
  2. Data-efficient Control from Images by Learning How to Use a Simple Model
    Thomas Power, and Dmitry Berenson
    In Machine Learning for Planning in Planning and Control of Robot Motion Workshop, ICRA , 2020