SE3Kit: A Lightweight Python Library for Specialized Geometric Primitives in Robotics

2026-05-21

AI Summary

This work addresses the limitations of existing Python robotics libraries, which either impose heavy dependencies or lack mathematical rigor and specialized functionality for rigid-body transformations. To bridge this gap, we propose SE3Kit—a lightweight, pure-Python geometric computing library that relies solely on NumPy and implements efficient operations on SE(3) and SO(3) grounded strictly in Lie group theory. Designed without the overhead of deep learning frameworks or visualization tools, SE3Kit balances mathematical correctness with code simplicity, making it well-suited for embedded deployment, rapid prototyping, and educational use. The library effectively fills the void between general-purpose utilities and heavyweight robotics frameworks.

Abstract

The Python robotics ecosystem faces a challenge: while many libraries exist for rigid body transformations, few are both lightweight and mathematically strict. This paper introduces SE3Kit, a lightweight Python library efficient operations on the Special Euclidean Group SE(3) and the Special Orthogonal Group SO(3). Unlike established frameworks that require heavy dependencies (e.g., SpatialMath, PyPose) or general tools that lack robotics-specific features (e.g., SciPy), SE3Kit targets the gap between these extremes. It is designed for embedded deployment, rapid prototyping, and education while providing rigorous mathematical implementation. It provides a pure-Python, NumPy-only implementation of Lie Group operations, without the overhead of deep learning or other visualization software.

Problem

• SE(3)
• SO(3)
• lightweight library
• rigid body transformations
• robotics

Innovation

• SE3Kit
• SE(3)
• SO(3)
• Lie Group
• lightweight robotics library