https://github.com/stack-of-tasks/tsid

Efficient Task Space Inverse Dynamics (TSID) based on Pinocchio
https://github.com/stack-of-tasks/tsid

control humanoids optimization pinocchio robotics task-space-inverse-dynamics

Last synced: 3 days ago
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Efficient Task Space Inverse Dynamics (TSID) based on Pinocchio

• Host: GitHub
• URL: https://github.com/stack-of-tasks/tsid
• Owner: stack-of-tasks
• License: bsd-2-clause
• Created: 2017-02-16T14:12:38.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2025-05-12T18:49:01.000Z (6 days ago)
• Last Synced: 2025-05-12T19:53:15.222Z (6 days ago)
• Topics: control, humanoids, optimization, pinocchio, robotics, task-space-inverse-dynamics
• Language: C++
• Homepage:
• Size: 6.34 MB
• Stars: 233
• Watchers: 16
• Forks: 83
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

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README

        
# TSID - Task Space Inverse Dynamics

[![Pipeline status](https://gitlab.laas.fr/stack-of-tasks/tsid/badges/master/pipeline.svg)](https://gitlab.laas.fr/stack-of-tasks/tsid/commits/master)

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[![PyPI version](https://badge.fury.io/py/tsid.svg)](https://badge.fury.io/py/tsid)

[![License](https://img.shields.io/badge/License-BSD%202--Clause-green.svg)](https://opensource.org/licenses/BSD-2-Clause)

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)

TSID is a C++ library for optimization-based inverse-dynamics control based on the rigid multi-body dynamics library [Pinocchio](https://github.com/stack-of-tasks/pinocchio).

## Documentation

* Take a look at the project [wiki](https://github.com/stack-of-tasks/tsid/wiki) for an overview of the design of the library.

* In the exercises folder you can find several examples of how to use TSID in Python with robot manipulators, humanoids, or quadrupeds.

* On the [website of Andrea Del Prete](https://andreadelprete.github.io/#teaching) you can find slides and video lessons on TSID.

* [Memmo 2020 summer school](https://memory-of-motion.github.io/summer-school/)

## Installation with Conda

If you want to directly dive into TSID in Python, only one single line is sufficient (assuming you have Conda installed):



conda install tsid -c conda-forge



## Installation from Debian/Ubuntu packages, with robotpkg

If you have never added robotpkg's software repository you can do it with the following commands:

```

sudo tee /etc/apt/sources.list.d/robotpkg.list <