# stack-of-tasks/pinocchio

A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives

Repository: https://github.com/stack-of-tasks/pinocchio
Canonical: https://ross.abutalabs.com/products/pinocchio
Homepage: http://stack-of-tasks.github.io/pinocchio/
Language: C++
License: BSD-2-Clause
License Family: permissive
Topics: robotics, dynamics, analytical-derivatives, kinematics, c-plus-plus, rigid-body-dynamics, code-generation, python, fcl, motion-planning, automatic-differentiation, urdf, ros, casadi, cppad, conda, pinocchio
Last push: 2026-08-26T01:28:50+00:00

## Health v2 (maintenance only)
Score: 93/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 80, longevity 100
- inputs: {"age_days": 4348, "days_push": 8, "days_rel": 57, "gap_med": 61, "n_releases_24m": 10}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3682, forks 570 (observed 2026-08-28T04:08:13.778746+00:00)

## What it is
Pinocchio is a fast C++ library (with Python bindings) implementing state-of-the-art rigid body dynamics algorithms for poly-articulated systems, including inverse/forward dynamics, Jacobians, and contact resolution. It provides analytical derivatives of core algorithms, enabling gradient-based optimization, control, and learning in robotics, simulation, and biomechanics.

## Use cases
- compute inverse and forward dynamics of a robot model
- calculate analytical derivatives of rigid body dynamics for gradient-based control
- parse URDF robot models and compute kinematics and Jacobians
- simulate articulated mechanisms with frictional contacts
- build model predictive control or reinforcement learning pipelines for legged robots
- compute center of mass and momentum dynamics for biomechanics analysis

## When to choose
- you need fast, efficient rigid body dynamics computations in C++ or Python
- you require analytical derivatives of dynamics algorithms for optimization or learning
- you are working on robot control, motion planning, or physics-based simulation
- you need closed-loop kinematic mechanisms and contact modeling support

## When to avoid
- you need a full physics engine with out-of-the-box rendering and game features
- you only need simple 2D physics simulation without articulated models
- you want a high-level robotics framework with built-in perception and planning stacks

## Facets
- artifact type: library
- maturity: active
- function: simulation, math, parser
- domain: robotics, simulation, computer-vision, graphics
- platform: cpp, python, windows, cross-platform
- tags: rigid-body-dynamics, kinematics, inverse-dynamics, forward-dynamics, analytical-derivatives, urdf, automatic-differentiation, motion-planning, robot-control, featherstone-algorithms, collision-detection, biomechanics, physics, code-generation, linux, macos

## Member repositories
- stack-of-tasks/pinocchio (main) score 93

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:13.778746+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:31:13.434563+00:00, confidence not recorded.
  - readme: https://github.com/stack-of-tasks/pinocchio (fetched 2026-08-28T04:08:13.778746+00:00, sha e0cd804a56a4)
  - homepage: http://stack-of-tasks.github.io/pinocchio/ (fetched 2026-08-29T09:25:04.354622+00:00, sha a05ba1ca06c4)
- Data as of 2026-08-30T08:39:29.467469+00:00.