L Downs, A Francis, N Koenig, B Kinman… - … on Robotics and …, 2022 - ieeexplore.ieee.org
Interactive 3D simulations have enabled break-throughs in robotics and computer vision, but simulating the broad diversity of environments needed for deep learning requires large …
A Szot, A Clegg, E Undersander… - Advances in neural …, 2021 - proceedings.neurips.cc
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 …
The rapid rise in popularity of Large Language Models (LLMs) with emerging capabilities has spurred public curiosity to evaluate and compare different LLMs, leading many …
Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and training …
We present BEHAVIOR-1K, a comprehensive simulation benchmark for human-centered robotics. BEHAVIOR-1K includes two components, guided and motivated by the results of an …
robosuite is a simulation framework for robot learning powered by the MuJoCo physics engine. It offers a modular design for creating robotic tasks as well as a suite of benchmark …
Building home assistant robots has long been a goal for vision and robotics researchers. To achieve this task, a simulated environment with physically realistic simulation, sufficient …
C Gan, J Schwartz, S Alter, D Mrowca… - arxiv preprint arxiv …, 2020 - arxiv.org
We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation. TDW enables simulation of high-fidelity sensory data and physical interactions between …