Bullet Real-Time Physics Simulation | Home of Bullet and PyBullet: physics simulation for games, vis

Time 2021-11-21 23:20:46

Web Name: Bullet Real-Time Physics Simulation | Home of Bullet and PyBullet: physics simulation for games, vis

WebSite: http://www.pybullet.org

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Bullet Real-Time Physics Simulation Search

Tiny differentiable simulator May 21, 2021 admin

We are developing a new differentiable simulator for robotics learning, called Tiny Differentiable Simulator, or TDS. The simulator allows for hybrid simulation with neural networks. It allows different automatic differentiation backends, for forward and reverse mode gradients. TDS can be trained using Deep Reinforcement Learning, or using Gradient based optimization (for example LFBGS). In addition, the simulator can be entirely run on CUDA for fast rollouts, in combination with Augmented Random Search. This allows for 1 million simulation steps per second.

TDS is used in a couple of research papers, such as the ICRA 2021 NeuralSim: Augmenting Differentiable Simulators with Neural Networks, by Eric Heiden, David Millard, Erwin Coumans, Yizhou Sheng and Gaurav S. Sukhatme.

You can checkout the source code here:
https://github.com/google-research/tiny-differentiable-simulator

PyBullet in a colab April 15, 2021 admin

You can directly try out PyBullet in your web browser, using Google Colab. !pip install pybullet takes about 15 seconds, since there is a precompiled Python wheel.

Here is an example training colab a PyBullet Gym environment using Stable Baselines PPO:

It is also possible to use hardware OpenGL3 rendering in a Colab, through EGL. Make sure to set the MESA environment variables. Here is an example colab.

PyBullet/Bullet Physics 3.05 September 24, 2020 admin

Tagged a github release of Bullet Physics and PyBullet, both version 3.05. The release was used for our motion imitation research, and also includes various improvements for the finite-element-method (FEM) deformable simulation, by Xuchen Han and Chuyuan Fu .

https://github.com/bulletphysics/bullet3/releases

See also the related repository with model-predictive-control (MPC) quadruped locomotion and the motion imitation research at https://github.com/google-research/motion_imitation

Assistive gym @ ICRA, 2020 June 3, 2020 admin

Assistive Gym leverages PyBullet for physical human-robot interaction and assistive robotics. Assistive Gym currently supports four collaborative robots and six physically assistive tasks.
It also supports learning-based control algorithms, and includes models of human motion, human preferences, robot base pose optimization, and realistic pose-dependent human joint limits

Paper Link: https://ras.papercept.net/proceedings/ICRA20/1572.pdf Zackory Erickson, Vamsee Gangaram, Ariel Kapusta, C. Karen Liu, and Charles C. Kemp, “Assistive Gym: A Physics Simulation Framework for Assistive Robotics”, IEEE International Conference on Robotics and Automation (ICRA), 2020.

Learning Agile Robotic Locomotion Skills by Imitating Animals April 3, 2020 admin

In “Learning Agile Robotic Locomotion Skills by Imitating Animals”, we present a framework that takes a reference motion clip recorded from an animal (a dog, in this case) and uses RL to train a control policy that enables a robot to imitate the motion in the real world. By providing the system with different reference motions, we are able to train a quadruped robot to perform a diverse set of agile behaviors, ranging from fast walking gaits to dynamic hops and turns. The policies are trained primarily in simulation, and then transferred to the real world using a latent space adaptation technique that can efficiently adapt a policy using only a few minutes of data from the real robot. All simulations are performed using PyBullet.

See also https://ai.googleblog.com/2020/04/exploring-nature-inspired-robot-agility.html and https://arxiv.org/abs/2004.00784

Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning March 17, 2020 admin

Robots can use meta-learning to quickly adapt from simulation to various real world conditions.

See paper at https://arxiv.org/abs/2003.01239

Lumote game using Bullet February 27, 2020 admin

Become the squishy glowing creature youve always wanted to be. Take control of the worlds inhabitants to solve puzzles. Overthrow the Mastermote! Check it out at https://store.steampowered.com/app/791240/Lumote

Alphabet Everyday Robot November 22, 2019 admin

Check out the Wired article about the Alphabet Everyday Robot.

PyBullet and Bullet Physics is used in the collaboration, as discussed in this Speeding up robot learning by 100x with simulation paper and described in those sim-to-real slides and the Challenges of Self-Supervision via Interaction in Robotics slides.

Facebook Habitat v0.1.3 adds Bullet Physics November 22, 2019 admin

Facebook AI Habitat is a new open source simulation platform created by Facebook AI that’s designed to train embodied agents (such as virtual robots) in photo-realistic 3D environments. The latest version adds Bullet Physics.

The github repo is here: https://github.com/facebookresearch/habitat-sim

Also check the online demo (no physics): https://aihabitat.org/demo

Robot Table Tennis research using PyBullet with Virtual Reality April 17, 2019 admin

This Robot Table Tennis project shows some very exciting research by Reza Mahjourian. It uses PyBullet and its Virtual Reality physics server support. Check out https://sites.google.com/corp/view/robottabletennis and his PhD thesis, Arxiv paper is  here: https://arxiv.org/abs/1811.12927

Hierarchical Policy Design for Sample-Efficient Learning of Robot Table Tennis Through Self-Play

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by wanglei at 09:02 2021-11-15 Home of Bullet and PyBullet: physics simulation for games, visual effects, robotics and reinforcement learning. Recent Posts Tiny differentiable simulator PyBullet in a colab PyBullet/Bullet Physics 3.05 Assistive gym @ ICRA, 2020 Learning Agile Robotic Locomotion Skills by Imitating Animals Selected Video

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