Collaborative Research: Elements: Discrete Simulation of Flexible Structures and Soft Robots

Sponsor: National Science Foundation (NSF)

Award Number: 2209783

PI: Andrew P. Sabelhaus


From carbon nanotubes to human-size soft robots, flexible and deformable structures are present throughout the next generation of promising engineering disciplines. However, simulation of these mechanical systems is often slow, and simulation software is challenging to use. In addition, there is little support for simulating flexible structures in common robotics research and education software, limiting the use of intelligent soft robots to experts only. On the other hand, the computer graphics community has developed advanced software for simulating flexible structures like hair and fur. Recent research has shown these computer graphics approaches can accurately simulate soft robots and flexible structures faster than real-time. This project develops an easy-to-use open-source software platform for these fast physics-based simulations of flexible structures, and incorporates the software into the national cyberinfrastructure ecosystem. This software, DiSMech, can be used by researchers of all ages to investigate the mechanics of slender structures, autonomy for soft robots, and breakthrough designs for deformable machines.

The objective of this work is to develop a discrete differential geometry (DDG) simulation environment into a widely-available software package capable of modeling soft and flexible structures. The DDG approach enables low-dimensional modeling of slender rods and flexible shells combined into arbitrary shapes, establishing a practical but still physically accurate contrast to computationally expensive finite element analysis (FEA) techniques. This work first develops a core software package for DiSMech that adapts prior work to meet the standard for national cyberinfrastructure: maintainable, extensible, and with a robust user interface. Next, a virtual testbed for a wide class of soft and flexible robots is built by incorporating DiSMech into an existing robotics software suite. The project team will use the combined software framework with a machine learning approach to develop a locomotion strategy for example soft robots. Finally, add-ons to DiSMech will incorporate machine learning alongside the DDG-based physics models for even faster simulations, demonstrating the research potential for this software in uncovering underlying physical phenomena. By advancing DDG-based physics simulations to capture a wide range of soft and flexible structures, with a computational speed sufficient for learned robot control, all in an easy-to-use interface, DiSMech addresses an important gap in the national cyberinfrastructure.

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