b'Diego Romeres'

research

∙ 07/11/2023

Forward Dynamics Estimation from Data-Driven Inverse Dynamics Learning

In this paper, we propose to estimate the forward dynamics equations of ...

0 Alberto Dalla Libera, et al. ∙

research

∙ 06/27/2023

Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos

To realize human-robot collaboration, robots need to execute actions for...

0 Chiori Hori, et al. ∙

research

∙ 05/04/2023

Learning Generalizable Pivoting Skills

The skill of pivoting an object with a robotic system is challenging for...

0 Xiang Zhang, et al. ∙

research

∙ 03/06/2023

Simultaneous Tactile Estimation and Control of Extrinsic Contact

We propose a method that simultaneously estimates and controls extrinsic...

0 Sangwoon Kim, et al. ∙

research

∙ 01/30/2023

Learning Control from Raw Position Measurements

We propose a Model-Based Reinforcement Learning (MBRL) algorithm named V...

0 Fabio Amadio, et al. ∙

research

∙ 12/02/2022

Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control

Robots have been steadily increasing their presence in our daily lives, ...

0 Devesh K Jha, et al. ∙

research

∙ 10/23/2022

Active Exploration for Robotic Manipulation

Robotic manipulation stands as a largely unsolved problem despite signif...

0 Tim Schneider, et al. ∙

research

∙ 09/28/2022

Constrained Dynamic Movement Primitives for Safe Learning of Motor Skills

Dynamic movement primitives are widely used for learning skills which ca...

0 Seiji Shaw, et al. ∙

research

∙ 04/22/2022

Design of Adaptive Compliance Controllers for Safe Robotic Assembly

Insertion operations are a critical element of most robotic assembly ope...

0 Devesh K Jha, et al. ∙

research

∙ 03/22/2022

Robust Pivoting: Exploiting Frictional Stability Using Bilevel Optimization

Generalizable manipulation requires that robots be able to interact with...

0 Yuki Shirai, et al. ∙

research

∙ 03/18/2022

PYROBOCOP: Python-based Robotic Control Optimization Package for Manipulation

PYROBOCOP is a Python-based package for control, optimization and estima...

0 Arvind Raghunathan, et al. ∙

research

∙ 03/05/2022

Chance-Constrained Optimization in Contact-Rich Systems for Robust Manipulation

This paper presents a chance-constrained formulation for robust trajecto...

0 Yuki Shirai, et al. ∙

research

∙ 11/20/2021

Imitation and Supervised Learning of Compliance for Robotic Assembly

We present the design of a learning-based compliance controller for asse...

0 Devesh K Jha, et al. ∙

research

∙ 06/06/2021

PYROBOCOP : Python-based Robotic Control Optimization Package for Manipulation and Collision Avoidance

PYROBOCOP is a lightweight Python-based package for control and optimiza...

212 Arvind U. Raghunathan, et al. ∙

research

∙ 06/02/2021

Trajectory Optimization for Manipulation of Deformable Objects: Assembly of Belt Drive Units

This paper presents a novel trajectory optimization formulation to solve...

0 Shiyu Jin, et al. ∙

research

∙ 04/26/2021

Control of Mechanical Systems via Feedback Linearization Based on Black-Box Gaussian Process Models

In this paper, we consider the use of black-box Gaussian process (GP) mo...

0 Alberto Dalla Libera, et al. ∙

research

∙ 04/02/2021

Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry

Object insertion is a classic contact-rich manipulation task. The task r...

0 Siyuan Dong, et al. ∙

research

∙ 01/28/2021

Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application

In this paper, we present a Model-Based Reinforcement Learning algorithm...

13 Fabio Amadio, et al. ∙

research

∙ 01/21/2021

Model-based Policy Search for Partially Measurable Systems

In this paper, we propose a Model-Based Reinforcement Learning (MBRL) al...

0 Fabio Amadio, et al. ∙

research

∙ 11/14/2020

Towards Human-Level Learning of Complex Physical Puzzles

Humans quickly solve tasks in novel systems with complex dynamics, witho...

13 Kei Ota, et al. ∙

research

∙ 07/22/2020

Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks

One of the main challenges in peg-in-a-hole (PiH) insertion tasks is in ...

0 Yifang Liu, et al. ∙

research

∙ 02/25/2020

Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements

In this paper, we propose a derivative-free model learning framework for...

0 Alberto Dalla Libera, et al. ∙

research

∙ 01/22/2020

Local Policy Optimization for Trajectory-Centric Reinforcement Learning

The goal of this paper is to present a method for simultaneous trajector...

14 Patrik Kolaric, et al. ∙

research

∙ 12/26/2019

Quasi-Newton Trust Region Policy Optimization

We propose a trust region method for policy optimization that employs Qu...

0 Devesh Jha, et al. ∙

research

∙ 10/23/2019

Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control

Robots need to learn skills that can not only generalize across similar ...

0 Jonathan Chang, et al. ∙

research

∙ 09/13/2018

Derivative-free online learning of inverse dynamics models

This paper discusses online algorithms for inverse dynamics modelling in...

0 Diego Romeres, et al. ∙

research

∙ 09/13/2018

Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze

This paper presents a problem of model learning for the purpose of learn...

0 Diego Romeres, et al. ∙

research

∙ 09/13/2018

Learning Hybrid Models to Control a Ball in a Circular Maze

This paper presents a problem of model learning to navigate a ball to a ...

0 Diego Romeres, et al. ∙

research

∙ 09/13/2018

Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics

Learning robot tasks or controllers using deep reinforcement learning ha...

0 Jeroen van Baar, et al. ∙

research

∙ 03/17/2016

Online semi-parametric learning for inverse dynamics modeling

This paper presents a semi-parametric algorithm for online learning of a...

0 Diego Romeres, et al. ∙

research

∙ 01/17/2016

On-line Bayesian System Identification

We consider an on-line system identification setting, in which new data ...

0 Diego Romeres, et al. ∙

research

∙ 07/02/2015

Identification of stable models via nonparametric prediction error methods

A new Bayesian approach to linear system identification has been propose...

0 Diego Romeres, et al. ∙

Diego Romeres

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