---
id: mink
version: "1.2.0"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# mink — Python inverse kinematics based on MuJoCo

License: permissive · Maintenance: active · Downloads: 337.9K/mo

## What it is and what it does

mink is a Python library for solving inverse kinematics (IK) problems on robot manipulators using the MuJoCo physics engine. It computes joint angles that move a robot's end-effector to a desired position and orientation while respecting joint limits, velocity bounds, and collision constraints. The library supports both single-arm and multi-arm systems, dexterous hands, humanoids, and legged robots, and can handle closed-chain kinematics through equality constraints.

The package depends on mujoco as its core physics backend, qpsolvers for quadratic programming, and typing_extensions for type hints. It provides a Lie group interface for rigid body transformations with native C optimization for performance-critical IK computations. Installation is straightforward across Linux, macOS, and Windows with pre-built wheels, though you will need a valid MuJoCo model and understanding of task specification to use it effectively.

Use it for:

- Real-time motion planning for robotic arms to reach target poses while avoiding obstacles.
- Humanoid robot control where multiple kinematic chains and balance constraints must be satisfied simultaneously.
- Dexterous manipulation tasks requiring hand and arm coordination with collision avoidance.
- Legged robot locomotion planning with closed-chain constraints from ground contact.
- Research prototyping of inverse kinematics algorithms on diverse robot morphologies.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

mink solves inverse kinematics problems for robot manipulators using MuJoCo, supporting task specification in configuration or operational space with collision avoidance and closed-chain constraints.

Yes, if you are working with MuJoCo-based robot simulation or control. mink is actively maintained, has no known vulnerabilities, uses a permissive license, and solves a well-defined problem (differential IK) with broad robot support. Install friction is moderate but manageable. Not suitable if you need IK for non-MuJoCo simulators or if your robot morphology is not covered by existing examples.

## Install

pip install mink
uv add mink
poetry add mink

## Installing mink

Before you install: Medium install friction due to compiled wheels across multiple platforms (cp310–cp312, macOS, Linux, Windows, musllinux). Active maintenance with recent release (55 days old) and 1493 repository stars suggest solid upkeep.

License in practice: Apache-2.0 is permissive; you may use, modify, and distribute mink freely in commercial and private projects, provided you retain license notices.

Quickstart:

pip install mink

import mink
# Requires MuJoCo model; see documentation for task setup
# solver = mink.IKSolver(...)

Requires MuJoCo physics engine and a valid robot model file; Python 3.10–3.13.

Verify before relying:

- Whether qpsolvers and typing_extensions are always required at runtime or only for specific features.
- Performance characteristics and scalability limits for real-time control loops.
- Compatibility with MuJoCo versions beyond what the fact sheet specifies.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: medium
- Maintenance: active
- Downloads: 337.9K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

inverse kinematics solver, robot arm IK, mujoco kinematics, differential inverse kinematics, robot motion planning, joint constraint optimization, collision-aware IK, robotics, kinematics, mujoco

[View on SkillFed](https://skillfed.io/packages/mink) · [View on PyPI](https://pypi.org/project/mink/)