bulletphysics/bullet3

Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.

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Summary Information

Updated 5 minutes ago
Added to GitGenius on September 4th, 2026
Created on April 12th, 2011
Open Issues & Pull Requests: 424 (+0)
GitHub issues: Enabled
Number of forks: 3,093
Total Stargazers: 14,718 (+0)
Total Subscribers: 405 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 12.2 days
Mean response time: 116.8 days
90th percentile: 477.9 days
Tracked items: 60

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 4% of issues opened in the past year have been closed. Three people close 50% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 80
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 558 days
Stale 30+ days: 78
Stale 90+ days: 75

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Bullet Physics SDK is a physics simulation engine that provides real-time collision detection and multi-body dynamics for applications ranging from games and virtual reality to robotics and machine learning.

The engine solves the problem of simulating physical interactions between objects in real time. It handles rigid body dynamics, collision detection, and constraint solving through a C++ core library that can execute on either CPU or GPU. The tool supports optional GPU acceleration via OpenCL, allowing the entire collision detection and dynamics pipeline to run on graphics hardware for performance-critical applications.

Developers should choose this tool if they are building games, VR applications, robotics simulations, or reinforcement learning environments where accurate physics simulation is required. The project explicitly recommends PyBullet, its Python binding, for improved support in robotics, reinforcement learning, and VR use cases, making it accessible to researchers and practitioners who prefer Python. The C++ library itself targets developers comfortable with native code and requiring maximum performance or deep integration with existing systems. The engine runs on Windows, Linux, macOS, iOS, and Android, with optional OpenGL support for visualization in demos.

The project maintains an active development cycle with regular updates to both the core C++ library and PyBullet bindings. The issue tracker was closed to manage support volume, with community discussion directed to dedicated forums instead. Build infrastructure is mature, supporting multiple toolchains including CMake and Premake, with integration available through package managers like vcpkg. The codebase adheres to documented coding standards and contribution guidelines, and the permissive zlib license permits use in commercial and proprietary projects.