Search Results for author: Rika Antonova

Found 11 papers, 4 papers with code

DiffCloud: Real-to-Sim from Point Clouds with Differentiable Simulation and Rendering of Deformable Objects

no code implementations7 Apr 2022 Priya Sundaresan, Rika Antonova, Jeannette Bohg

However, for highly deformable objects it is challenging to align the output of a simulator with the behavior of real objects.

BayesSimIG: Scalable Parameter Inference for Adaptive Domain Randomization with IsaacGym

1 code implementation9 Jul 2021 Rika Antonova, Fabio Ramos, Rafael Possas, Dieter Fox

This paper outlines BayesSimIG: a library that provides an implementation of BayesSim integrated with the recently released NVIDIA IsaacGym.

reinforcement-learning

Sequential Topological Representations for Predictive Models of Deformable Objects

no code implementations23 Nov 2020 Rika Antonova, Anastasiia Varava, Peiyang Shi, J. Frederico Carvalho, Danica Kragic

Deformable objects present a formidable challenge for robotic manipulation due to the lack of canonical low-dimensional representations and the difficulty of capturing, predicting, and controlling such objects.

Bayesian Optimization in Variational Latent Spaces with Dynamic Compression

1 code implementation10 Jul 2019 Rika Antonova, Akshara Rai, Tianyu Li, Danica Kragic

We propose a model and architecture for a sequential variational autoencoder that embeds the space of simulated trajectories into a lower-dimensional space of latent paths in an unsupervised way.

Global Search with Bernoulli Alternation Kernel for Task-oriented Grasping Informed by Simulation

no code implementations10 Oct 2018 Rika Antonova, Mia Kokic, Johannes A. Stork, Danica Kragic

Our further contribution is a neural network architecture and training pipeline that use experience from grasping objects in simulation to learn grasp stability scores.

Deep Kernels for Optimizing Locomotion Controllers

no code implementations27 Jul 2017 Rika Antonova, Akshara Rai, Christopher G. Atkeson

First, we demonstrate improvement in sample efficiency when optimizing a 5-dimensional controller on the ATRIAS robot hardware.

Unlocking the Potential of Simulators: Design with RL in Mind

no code implementations8 Jun 2017 Rika Antonova, Silvia Cruciani

We design a simulator for solving a pivoting task (of interest in Robotics) and demonstrate that even a simple simulator designed with RL in mind outperforms high-fidelity simulators when it comes to learning a policy that is to be deployed on a real robotic system.

Decision Making

Reinforcement Learning for Pivoting Task

1 code implementation1 Mar 2017 Rika Antonova, Silvia Cruciani, Christian Smith, Danica Kragic

In this work we propose an approach to learn a robust policy for solving the pivoting task.

Continuous Control reinforcement-learning

Sample Efficient Optimization for Learning Controllers for Bipedal Locomotion

no code implementations15 Oct 2016 Rika Antonova, Akshara Rai, Christopher G. Atkeson

We develop a distance metric for bipedal locomotion that enhances the sample-efficiency of Bayesian Optimization and use it to train a 16 dimensional neuromuscular model for planar walking.

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