VoxelFuse

This project seeks to provide methods and set of tools for processing, modifying, and generating 3D models that use multiple materials and fabrication processes. Areas of research include planning of fabrication steps, automatic part modification, optimization of component properties, and generation of the files and fixtures needed to produce multi-material parts. Implementation of these algorithms is done in Python using a voxel-based model representation. This work will make multi-material fabrication more accessible for educational and research robotics.

The example model pictured shows a 3D printed robot joint with an embedded servo motor. To create this part, a simple model was first created that represented the desired shape and position of the robot body and motor. VoxelFuse was then used to process the input model to generate clearances around the motor and export the modified model for slicing. After slicing the model and generating printer g-code, VoxelFuse was used to determine the layer at which the print needed to be paused to insert the motor, and then to modify the g-code accordingly. While printing, two colors of plastic were used to illustrate where this insertion step occured.

More information and source code is available in the project's GitHub repository. For more information on the underlying framework and example applications, see the papers on my Google Scholar Profile.