Modular Reconfigurable Robots (MRRs) are an exciting innovation in industrial robotics. They promise greater flexibility, improved maintainability, and cost-efficiency compared to monolithic manipulators. 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 in 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.
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Modular Reconfigurable Robots (MRRs) are an exciting innovation in industrial robotics. They promise greater flexibility, improved maintainability, and cost-efficiency compared to monolithic manipulators. 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 i...
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