Habitat 2.0: Training home assistants to rearrange their habitat
Abstract We introduce Habitat 2.0 (H2. 0), a simulation platform for training virtual robots in
interactive 3D environments and complex physics-enabled scenarios. We make …
interactive 3D environments and complex physics-enabled scenarios. We make …
Theseus: A library for differentiable nonlinear optimization
We present Theseus, an efficient application-agnostic open source library for differentiable
nonlinear least squares (DNLS) optimization built on PyTorch, providing a common …
nonlinear least squares (DNLS) optimization built on PyTorch, providing a common …
Expressive body capture: 3d hands, face, and body from a single image
To facilitate the analysis of human actions, interactions and emotions, we compute a 3D
model of human body pose, hand pose, and facial expression from a single monocular …
model of human body pose, hand pose, and facial expression from a single monocular …
Closing the sim-to-real loop: Adapting simulation randomization with real world experience
We consider the problem of transferring policies to the real world by training on a distribution
of simulated scenarios. Rather than manually tuning the randomization of simulations, we …
of simulated scenarios. Rather than manually tuning the randomization of simulations, we …
Variable compliance control for robotic peg-in-hole assembly: A deep-reinforcement-learning approach
CC Beltran-Hernandez, D Petit, IG Ramirez-Alpizar… - Applied Sciences, 2020 - mdpi.com
Featured Application Assembly tasks with industrial robot manipulators. Abstract Industrial
robot manipulators are playing a significant role in modern manufacturing industries …
robot manipulators are playing a significant role in modern manufacturing industries …
Dynamicfusion: Reconstruction and tracking of non-rigid scenes in real-time
We present the first dense SLAM system capable of reconstructing non-rigidly deforming
scenes in real-time, by fusing together RGBD scans captured from commodity sensors. Our …
scenes in real-time, by fusing together RGBD scans captured from commodity sensors. Our …
Dexterous imitation made easy: A learning-based framework for efficient dexterous manipulation
SP Arunachalam, S Silwal, B Evans… - 2023 ieee international …, 2023 - ieeexplore.ieee.org
Optimizing behaviors for dexterous manipulation has been a longstanding challenge in
robotics, with a variety of methods from model-based control to model-free reinforcement …
robotics, with a variety of methods from model-based control to model-free reinforcement …
Embodied hands: Modeling and capturing hands and bodies together
Humans move their hands and bodies together to communicate and solve tasks. Capturing
and replicating such coordinated activity is critical for virtual characters that behave …
and replicating such coordinated activity is critical for virtual characters that behave …
Self-supervised 6d object pose estimation for robot manipulation
To teach robots skills, it is crucial to obtain data with supervision. Since annotating real world
data is time-consuming and expensive, enabling robots to learn in a self-supervised way is …
data is time-consuming and expensive, enabling robots to learn in a self-supervised way is …
PoseRBPF: A Rao–Blackwellized particle filter for 6-D object pose tracking
Tracking 6-D poses of objects from videos provides rich information to a robot in performing
different tasks such as manipulation and navigation. In this article, we formulate the 6-D …
different tasks such as manipulation and navigation. In this article, we formulate the 6-D …