From Problem to Solution: Bio-inspired 3D Printing for Bonding Soft and Rigid Materials via Underextrusions
<|reference_start|>From Problem to Solution: Bio-inspired 3D Printing for Bonding Soft and Rigid Materials via Underextrusions: Vertebrate animals benefit from a combination of rigidity for structural support and softness for adaptation. Similarly, integrating rigidity and softness can enhance the versatility of soft robotics. However, the challenges associated with creating durable bonding interfaces between soft and rigid materials have limited the development of hybrid robots. Existing solutions require specialized machinery, such as polyjet 3D printers, which are not commonly available. In response to these challenges, we have developed a 3D printing technique that can be used with almost all commercially available FDM printers. This technique leverages the common issue of underextrusion to create a strong bond between soft and rigid materials. Underextrusion generates a porous structure, similar to fibrous connective tissues, that provides a robust interface with the rigid part through layer fusion, while the porosity enables interlocking with the soft material. Our experiments demonstrated that this method outperforms conventional adhesives commonly used in soft robotics, achieving nearly 200\% of the bonding strength in both lap shear and peeling tests. Additionally, we investigated how different porosity levels affect bonding strength. We tested the technique under pressure scenarios critical to soft and hybrid robots and achieved three times more pressure than the current adhesion solution. Finally, we fabricated various hybrid robots using this technique to demonstrate the wide range of capabilities this approach and hybridity can bring to soft robotics. has context menu<|reference_end|>
@article{goshtasbi2024from,
    title={From Problem to Solution: Bio-inspired 3D Printing for Bonding Soft and
  Rigid Materials via Underextrusions},
    author={Arman Goshtasbi, Luca Grignaffini, Ali Sadeghi},
    journal={arXiv preprint arXiv:2408.01210},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.01210},
    primaryClass={cs.RO}
}