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Joao Moura

6 accepted papers

2025

Fast Flow-based Visuomotor Policies via Conditional Optimal Transport Couplings

Andreas Sochopoulos, Nikolay Malkin, Nikolaos Tsagkas, Joao Moura, Michael Gienger, Sethu Vijayakumar
CoRL 2025poster

Diffusion and flow matching policies have recently demonstrated remarkable performance in robotic applications by accurately capturing multimodal robot trajectory distributions. However, their computationally expensive inference, due to the numerical integration of an ODE or SDE, limits their applic…

Cited by 0Source ↗Scholar ↗
2025

Poke and Strike: Learning Task-Informed Exploration Policies

Marina Y. Aoyama, Joao Moura, Juan Del Aguila Ferrandis, Sethu Vijayakumar
CoRL 2025poster

In many dynamic robotic tasks, such as striking pucks into a goal outside the reachable workspace, the robot must first identify the relevant physical properties of the object for successful task execution, as it is unable to recover from failure or retry without human intervention. To address this…

Cited by 0Source ↗Scholar ↗
2024

Learning Visuotactile Estimation and Control for Non-prehensile Manipulation under Occlusions

Juan Del Aguila Ferrandis, Joao Moura, Sethu Vijayakumar
CoRL 2024poster

Manipulation without grasping, known as non-prehensile manipulation, is essential for dexterous robots in contact-rich environments, but presents many challenges relating with underactuation, hybrid-dynamics, and frictional uncertainty. Additionally, object occlusions in a scenario of contact uncert…

Cited by 4Source ↗Scholar ↗
2019

Equivalence of the Projected Forward Dynamics and the Dynamically Consistent Inverse Solution

Joao Moura, Vladimir Ivan, Mustafa Suphi Erden, Sethu Vijayakumar
RSS 2019poster

The analysis, design, and motion planning of robotic systems, often relies on its forward and inverse dynamic models. When executing a task involving interaction with the environment, both the task and the environment impose constraints on the robot’s motion. For modeling such systems, we need to in…

Cited by 8Source ↗PDF ↗Scholar ↗
2017

Learning Constrained Generalizable Policies by Demonstration

Leopoldo Armesto, Vladimir Ivan, Joao Moura, Antonio Sala, Sethu Vijayakumar
RSS 2017poster

Many practical tasks in robotic systems, such as cleaning windows, writing or grasping, are inherently constrained. Learning policies subject to constraints is a challenging problem. We propose a \emph{locally weighted constrained projection learning} method (LWCPL) that first estimates the constra…

Cited by 14Source ↗PDF ↗Scholar ↗