  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.
