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João Carvalho

Postdoctoral Researcher @ TU Darmstadt

Contact: joao@robot-learning.de

CV [03/2026] | Google Scholar | GitHub | LinkedIn | X

I am a Postdoctoral Researcher at the Intelligent Autonomous Systems (IAS) group from TU Darmstadt.
My research interests are developing machine learning and reinforcement learning algorithms for robot manipulation. I've developed algorithms that use deep generative models for visuomotor policies, motion planning and grasping, and on reinforcement learning methods to solve contact-rich tasks like insertions. In the past, I've also worked on sample efficient off-policy reinforcement learning algorithms, and on variance reduction techniques for policy gradients.


news

26 Jan 2026 Robot Path Planning via Flow Matching accepted at the German Robotics Conference.
16 Jul 2025 Motion Planning Diffusion accepted at T-RO.
14 Jul 2025 Model Tensor Planning accepted at TMLR.
14 Jun 2025 The learning chapter in Robotics Goes MOOC was finally published.
20 May 2025 Global Tensor Motion Planning accepted at RA-L.
13 Mar 2025 Four papers accepted at the German Robotics Conference.
01 Feb 2025 I started a new position as Postdoctoral Researcher at IAS.
17 Jan 2025 I’ve defended my Ph.D. thesis on Enhancing Robot Manipulation Skills through Learning.
01 May 2024 The ROBOSTRUCT project, supported by the Software Campus, has officially started.

key publications

Please visit Google Scholar for a complete list.

2025

  1. mpd-splines.png
    Motion Planning Diffusion: Learning and Adapting Robot Motion Planning With Diffusion Models
    João Carvalho, An T. Le, Piotr Kicki, Dorothea Koert, and Jan Peters
    IEEE T-RO, 2025
    PDF Website Code
  2. cube_mtp-akima.png
    Model Tensor Planning
    An Thai Le, Khai Nguyen, Minh Nhat Vu, João Carvalho, and Jan Peters
    TMLR, 2025
    PDF Website Code
  3. gtmp_spline_occupancy.png
    Global Tensor Motion Planning
    An T. Le, Kay Pompetzki, João Carvalho, Joe Watson, Julen Urain, and 3 more authors
    IEEE RA-L, 2025
    PDF Website Code

2024

  1. gdn.png
    Grasp Diffusion Network: Learning Grasp Generators from Partial Point Clouds with Diffusion Models in SO(3)xR3
    João Carvalho, An T. Le, Philipp Jahr, Qiao Sun, Julen Urain, and 2 more authors
    arXiv, 2024
    PDF Website
  2. actionflow.png
    ActionFlow: Equivariant, Accurate, and Efficient Policies with Spatially Symmetric Flow Matching
    Niklas Funk, Julen Urain, Joao Carvalho, Vignesh Prasad, Georgia Chalvatzaki, and 1 more author
    arXiv, 2024
    PDF Website

2023

  1. mpd.png
    Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models
    João Carvalho, An T. Le, Mark Baierl, Dorothea Koert, and Jan Peters
    IROS, 2023
    PDF Website Code
  2. diminishing_returns.png
    Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning
    Daniel Palenicek, Michael Lutter, Joao Carvalho, and Jan Peters
    ICLR, 2023
    PDF

2022

  1. rrl_promp.png
    Adapting Object-Centric Probabilistic Movement Primitives with Residual Reinforcement Learning
    João Carvalho, Dorothea Koert, Marek Daniv, and Jan Peters
    Humanoids, 2022
    PDF
  2. conditioned_sbm_trajectory.png
    Conditioned Score-Based Models for Learning Collision-Free Trajectory Generation
    João Carvalho, Mark Baierl, Julen Urain, and Jan Peters
    NeurIPS Workshop SBM, 2022
    PDF
  3. nopg_mountain_car.png
    Batch Reinforcement Learning With a Nonparametric Off-Policy Policy Gradient
    Samuele Tosatto, João Carvalho, and Jan Peters
    IEEE TPAMI, 2022
    PDF Code

2021

  1. mvd-rl.png
    An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients
    João Carvalho, Davide Tateo, Fabio Muratore, and Jan Peters
    IJCNN, 2021
    PDF Code

2020

  1. nopg_lqr.png
    A Nonparametric Off-Policy Policy Gradient
    Samuele Tosatto, João Carvalho, Hany Abdulsamad, and Jan Peters
    AISTATS, 2020
    PDF Code