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).

Mar 14, 2025 · Show what you made with Bullet Physics SDK: Games, Demos, Integrations with a graphics engine, modeler or any other application

Mar 17, 2025 · The Bullet user manual and related documentation are in the docs folder of the Physics SDK: There is also online API documentation. You can re-generate the API documentation by running Doxygen in the root of Bullet. The PyBullet Quickstart Guide shows how to use PyBullet, which is useful for Robotics, Virtual Reality and Reinforcement Learning ...

Apr 15, 2021 · Home of Bullet and PyBullet: physics simulation for games, visual effects, robotics and reinforcement learning.

Sep 16, 2018 · Create rigid simulations with constraints to build complex mechanical interactions. Paint softbody constraint weights to animate. Add jiggle and bounce to any prop or character. Use the Live Simulation mode to preview dynamics in realtime, or calculate simulations to include in rendered animations. See for more information on Bullet and Poser ...

For efficient and more flexible data collection, we train in simulation and transfer the policies to a real robot. We show that using curriculum learning, policies learned with a sparse reward formulation can be trained at similar rates as with a shaped reward.

Oct 17, 2017 · To make our physics simulation easier to use, especially for roboticist and machine learning experts, we created Python bindings, see examples/pybullet. In addition, we added Virtual Reality support for HTC Vive and Oculus Rift using the openvr sdk.

Jan 8, 2011 · Bullet can be used in several ways, as Full Rigid Body simulation, as Collision Detector Library or Low Level / Snippets like the GJK Closest Point calculation. The Dependencies can be seen in this documentation under Directories

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).

Mar 4, 2014 · RESEARCH AND DEVELOPMENT IN COLLISION DETECTION & PHYSICS. Don't post Bullet support questions here!