Python library for robotic simulation using the MuJoCo engine:
OpenAI 2017.6:
open-sourcing a high-performance Python library
for robotic simulation using the MuJoCo engine,
developed over our past year of robotics research.
This library is one of our core tools for
deep learning robotics research,
which we’ve now released as a major version of mujoco-py,
our Python 3 bindings for MuJoCo.
. mujoco-py uses data parallelism through OpenMP
and direct-access memory management through
Cython [C translator] and NumPy [math pkg]
to make batched simulation more efficient.
Cython is an optimizing static compiler
for both the Python programming language
and the extended Cython programming language (based on Pyrex).
It makes writing C extensions for Python
as easy as Python itself.
MuJoCo (Multi-Joint dynamics with Contact):
. It is a physics engine aiming to facilitate
research and development in robotics,
biomechanics, graphics and animation,
and other areas where fast and accurate simulation is needed.
It offers a unique combination of speed, accuracy and modeling power,
yet it is not merely a better simulator.
Instead it is the first full-featured simulator
designed from the ground up for the purpose of
model-based optimization,
and in particular optimization through contacts.
MuJoCo makes it possible to scale up
computationally-intensive techniques
such optimal control, physically-consistent state estimation,
system identification and automated mechanism design,
and apply them to complex dynamical systems in contact-rich behaviors.
It also has more traditional applications
such as testing and validation of control schemes
before deployment on physical robots,
interactive scientific visualization,
virtual environments, animation and gaming.
No comments:
Post a Comment