# Timor Python: A Toolbox for Industrial Modular Robotics

arXiv: https://arxiv.org/abs/2209.06758 · HTML: https://mlsanity.com/paper/2209.06758/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Sep 2022.

## Built on by (most cited first, 2 of 2)

- [Optimizing Modular Robot Composition: A Lexicographic Genetic Algorithm Approach](https://mlsanity.com/paper/2309.08399/) (2023)
- [Holistic Construction Automation with Modular Robots: From High-Level Task Specification to Execution](https://mlsanity.com/paper/2412.20867/) (2024)

## Abstract (arXiv)

Modular Reconfigurable Robots (MRRs) represent an exciting path forward for industrial robotics, opening up new possibilities for robot design. Compared to monolithic manipulators, they promise greater flexibility, improved maintainability, and cost-efficiency. However, there is no tool or standardized way to model and simulate assemblies of modules in the same way it has been done for robotic manipulators for decades. We introduce the Toolbox for Industrial Modular Robotics (Timor), a Python toolbox to bridge this gap and integrate modular robotics into existing simulation and optimization pipelines. Our open-source library offers model generation and task-based configuration optimization for MRRs. It can easily be integrated with existing simulation tools - not least by offering URDF export of arbitrary modular robot assemblies. Moreover, our experimental study demonstrates the effectiveness of Timor as a tool for designing modular robots optimized for specific use cases.