publications

Please visit Google Scholar for a complete list.

2026

  1. Do My Samples Help? Compute Budget Allocation for Real-World Sampling-Based MPC in Contact-Rich Manipulation

    Magnus Dierking , João Carvalho , Vince Kurtz , Jan Peters , Nils Dengler

    arXiv, 2026

    PDF Website Code

  2. Residual Compliant Policy: Learning Compliant Policies from Few Demonstrations

    Chunyu Jiang , Yichen Cai , Shuai Li , Wenbin Sun , João Carvalho

    arXiv, 2026

    PDF Website

  3. Diminishing Return of Value Expansion Methods

    Daniel Palenicek , Michael Lutter , João Carvalho , Daniel Dennert , Faran Ahmad

    IEEE TPAMI, 2026

    PDF

  4. Geometry-Aware Probabilistic Shared Autonomy with Riemannian Motion Policies

    Kay Pompetzki , Cristiana Farias , João Carvalho , Georgia Chalvatzaki , and Jan Peters

    ICRA Workshop on Geometry in the Age of Data-Driven Robotics, 2026

    PDF

  5. Real-World Deployment of Massively Parallel Sampling-Based MPC for Contact-Rich Manipulation

    Magnus Dierking , João Carvalho , An Thai Le , Georgia Chalvatzaki , and Jan Peters

    ICRA Workshop on Frontiers of Optimization for Robotics, 2nd Edition, 2026

    PDF

  6. The Blind Skateboarder: Unlocking Dexterous Robotic Skateboarding via Interactive Perception

    Aditya Bhatt , Ansh Prakash , João Carvalho , Puze Liu , and Jan Peters

    IROS Workshop on Perception and Decision Making for Athletic Humanoid Robotics, 2026

    Best Poster Award

    PDF

  7. Blind Whole-Body Haptic Dexterity Without Tactile Sensors

    Aditya Bhatt , Ansh Prakash , Oleg Kaidanov , João Carvalho , Puze Liu

    IROS Workshop on Enhancing Dexterous Manipulation Through Haptic Feedback, 2026

    PDF

  8. Learning Paths, Following Safely: Flow Matching Meets Predictive Control

    P. Holzmann , M. Pfefferkorn , J. Carvalho , A. Younes , A. Le

    In preparation, 2026

  9. Robot Path Planning via Flow Matching with Safety and Adaptivity through Predictive Control

    Philipp Holzmann , Maik Pfefferkorn , João Carvalho , Ali Younes , An T. Le

    GRC, 2026

2025

  1. 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; PP-RAI, 2026; AAAI, 2026

    PDF Website Code

  2. Enhancing Robot Manipulation Skills through Learning

    João Carvalho

    PhD Thesis, 2025

    PDF Website

  3. Model Tensor Planning

    An Thai Le , Khai Nguyen , Minh Nhat Vu , João Carvalho , and Jan Peters

    TMLR, 2025; ICLR, 2026; R:SS Workshop Motion Planning and Control via Parallelization, 2025; ICRA Workshop RoboARCH: Robotics Acceleration with Computing Hardware and Systems, 2025

    PDF Website Code

  4. Global Tensor Motion Planning

    An T. Le , Kay Pompetzki , João Carvalho , Joe Watson , Julen Urain

    IEEE RA-L, 2025; ICRA, 2026; GRC, 2025; CoRL Workshop on Differentiable Optimization Everywhere, 2024

    PDF Website Code

  5. Diffusion Meets Control: Constrained Motion Planning with Predictive Safety Guarantees

    P. Holzmann , J. Carvalho , A. Younes , A. Le , M. Pfefferkorn

    GRC, 2025

  6. Learning

    Joe Watson , Julen Urain , João Carvalho , Niklas Funk , and Jan Peters

    Robotics Goes MOOC: Knowledge, 2025

2024

  1. 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

    arXiv, 2024; GRC, 2025

    PDF Website

  2. ActionFlow: Equivariant, Accurate, and Efficient Policies with Spatially Symmetric Flow Matching

    Niklas Funk , Julen Urain , Joao Carvalho , Vignesh Prasad , Georgia Chalvatzaki

    arXiv, 2024; GRC, 2025; CoRL Workshop on Mastering Robot Manipulation in a World of Abundant Data, 2024; R:SS Workshop Priors4Robots, 2024

    Best Paper Award — R:SS Workshop Priors4Robots, 2024

    PDF Website

2023

  1. 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 Return of Value Expansion Methods in Model-Based Reinforcement Learning

    Daniel Palenicek , Michael Lutter , Joao Carvalho , and Jan Peters

    ICLR, 2023

    PDF

2022

  1. Adapting Object-Centric Probabilistic Movement Primitives with Residual Reinforcement Learning

    João Carvalho , Dorothea Koert , Marek Daniv , and Jan Peters

    Humanoids, 2022

    PDF

  2. Conditioned Score-Based Models for Learning Collision-Free Trajectory Generation

    João Carvalho , Mark Baierl , Julen Urain , and Jan Peters

    NeurIPS Workshop on Score-Based Methods, 2022

    PDF

  3. Batch Reinforcement Learning With a Nonparametric Off-Policy Policy Gradient

    Samuele Tosatto , João Carvalho , and Jan Peters

    IEEE TPAMI, 2022

    PDF Code

  4. Integrated Bi-Manual Motion Generation and Control shaped for Probabilistic Movement Primitives

    Jonathan Vorndamme , João Carvalho , Riddhiman Laha , Dorothea Koert , Luis F. C. Figueredo

    Humanoids, 2022

    Best Interactive Paper Award Finalist

  5. An Analysis of Measure-Valued Derivatives for Policy Gradients

    João Carvalho , and Jan Peters

    RLDM, 2022

2021

  1. 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. A Nonparametric Off-Policy Policy Gradient

    Samuele Tosatto , João Carvalho , Hany Abdulsamad , and Jan Peters

    AISTATS, 2020

    PDF Code

2019

  1. Nonparametric Off-Policy Policy Gradient

    João Carvalho

    2019

2012

  1. Electric Distribution Network Loss Computation and Minimization

    J. Carvalho

    2012