Abstract

Soft Robots have been an increasingly studied topic due to their ability to deal with unknown situations, their inherent compliance which reduces computational load for control by allowing the robot to conform to complex scenarios without requiring precise movement or actuation when compared to rigid robots, as well as the ability to more safely interact with humans. As such a need to simulate soft robots has also developed. Furthermore, the ability to create robots with varying materials allows for designs with additional degrees of freedom as well as pre-programmed deformations. Soft robots can be thought as deforming through geometric constraints; from the shortening of a cable, or the increase in volume of a pneumatic system. A new framework has been developed to simulate multi-material soft robots using geometric modelling. This frame work provided a 45x increase in computational speed compared to commercial software such as Abaqus. In addition, it provides stable and accurate results past 30% strains which current state-of the art solver such as SOFA can not perform. To be able to take full advantage of the design freedom for soft robots, new manufacturing techniques need to be investigated. Conventional manufacturing techniques for elastomers struggle with complex geometry and multi-material fabrication. Additive manufacturing, in certain cases, has been able to address both those issues. While standard Fused Deposition Method and PolyJetting 3D printing techniques are capable of multi-material fabrication, both have inherent flaws that Digital Light Processing 3D printing can address. Therefore a novel multi-material solution was developed for the DLP process. This printer utilizes an active cleaning solution using a spray to reduce contamination and cleaning time. In addition, an automated storage and retrieval system is adapted to increase the efficiency and material capacity of the printer. When compared to the state of the art, a 3x speed increase is observed while having a build area that is 12 times larger, while also decreasing the cleaning time by 8x and decreasing contamination by 4x.