libpinocchio
A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
Decision gist · record as of 2026-08-14
Yes, with conditions. libpinocchio is actively maintained, permissively licensed (BSD-3-Clause), and widely used in robotics research. Install if you need rigid body dynamics computation for robotics or physics simulation. Caveat: medium install friction from compiled dependencies; on non-Linux, use conda instead of pip. No known security vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.9.
- On non-Linux platforms, installation via conda is recommended; pip currently supports Linux only.
- Medium install friction due to compiled C++ dependencies (cmeel, cmeel-boost, cmeel-urdfdom, libcoal).
License · maintenance · safety
BSD-3-Clause (permissive) — BSD-3-Clause permissive license allows use in commercial and proprietary projects with minimal restrictions, requiring only license and copyright notice retention.
last release 2026-07-08 (37 days) · last repo commit 2026-07-08
0 known vulnerabilities (OSV.dev, 2026-08-14) · 589,544 downloads/mo, #5,860 on PyPI
Alternatives
Verify before relying
pip install libpinocchio
import libpinocchio
model = buildModelFromUrdf('robot.urdf')
data = model.createData()
forwardKinematics(model, data, q)- Whether the Python interface fully exposes all C++ algorithms mentioned in the description or if some features require direct C++ usage.
- Performance characteristics and scalability limits for systems with many degrees of freedom.
- Availability and maturity of automatic differentiation support via CppAD or CasADi integration.
- Exact API and usage patterns for the Python interface to libpinocchio.
What it is and what it does
libpinocchio is a Python-wrapped C++ library for computing rigid body dynamics efficiently. It implements state-of-the-art algorithms for forward and inverse kinematics, forward and inverse dynamics, centroidal dynamics, and their analytical derivatives. The library handles complex scenarios like closed-loop mechanisms and frictional contact problems, making it suitable for robot control, trajectory optimization, and physics-based simulation.
The package is built on Eigen for linear algebra and coal for collision detection. It supports multiple robot model formats (URDF, SDF, MJCF, SRDF) and can be used across robotics, biomechanics, computer graphics, and vision applications. Analytical derivatives enable gradient-based optimization and learning. The library is actively developed and powers several robotics frameworks.
Use it for
- Compute forward and inverse kinematics for robot manipulators to plan and execute motion.
- Solve trajectory optimization problems for robot control using analytical derivatives of dynamics.
- Simulate contact-rich manipulation tasks with frictional contact solvers.
- Perform system identification and parameter estimation using kinematic and dynamic regressors.
- Prototype robot learning algorithms in Python before deploying to production systems.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, with conditions.
libpinocchio is actively maintained, permissively licensed (BSD-3-Clause), and widely used in robotics research. Install if you need rigid body dynamics computation for robotics or physics simulation. Caveat: medium install friction from compiled dependencies; on non-Linux, use conda instead of pip. No known security vulnerabilities.
Install
libpinocchio on PyPI
Before you install
Medium install friction due to compiled C++ dependencies (cmeel, cmeel-boost, cmeel-urdfdom, libcoal). Pre-built wheels available for macOS (Intel and ARM) and Linux x86_64/aarch64. Actively maintained with recent releases.
Requires Python >=3.9. On non-Linux platforms, installation via conda is recommended; pip currently supports Linux only.
License in practice
BSD-3-Clause permissive license allows use in commercial and proprietary projects with minimal restrictions, requiring only license and copyright notice retention.
Quickstart
pip install libpinocchio
import libpinocchio
model = buildModelFromUrdf('robot.urdf')
data = model.createData()
forwardKinematics(model, data, q)Verify before relying
- Whether the Python interface fully exposes all C++ algorithms mentioned in the description or if some features require direct C++ usage.
- Performance characteristics and scalability limits for systems with many degrees of freedom.
- Availability and maturity of automatic differentiation support via CppAD or CasADi integration.
- Exact API and usage patterns for the Python interface to libpinocchio.
Package facts
| License | BSD-3-Clause permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 4 packagescmeelcmeel-boostcmeel-urdfdomlibcoal |
| Maintenance | Actively maintained 37 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 589,544 / month, #5,860 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: libpinocchio-4.1.0-0-py3-none-macosx_10_9_x86_64.whl; libpinocchio-4.1.0-0-py3-none-macosx_11_0_arm64.whl; libpinocchio-4.1.0-0-py3-none-manylinux_2_28_aarch64.whl; libpinocchio-4.1.0-0-py3-none-manylinux_2_28_x86_64.whl
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See also pin · pybullet · drake · dynamixel-sdk · pymunk · robot_descriptions · mplib · pin-pink · coal-library · toppra