DiffAqua: A Differentiable Computational Design Pipeline for Soft Underwater Swimmers with Shape Interpolation
1MIT CSAIL 2ETH Zürich
[Overview]
The overview of our differentiable pipeline for both forward and backward propagation.
Abstract
The computational design of soft underwater swimmers is challenging because of the high degrees of freedom in soft-body modeling. In this paper, we present a differentiable pipeline for co-designing a soft swimmer's geometry and controller. Our pipeline unlocks gradient-based algorithms for discovering novel swimmer designs more efficiently than traditional gradient-free solutions. We propose Wasserstein barycenters as a basis for the geometric design of soft underwater swimmers since it is differentiable and can naturally interpolate between bio-inspired base shapes via optimal transport. By combining this design space with differentiable simulation and control, we can efficiently optimize a soft underwater swimmer's performance with fewer simulations than baseline methods. We demonstrate the efficacy of our method on various design problems such as fast, stable, and energy-efficient swimming and demonstrate applicability to multi-objective design.
Paper
DiffAqua: A Differentiable Computational Design Pipeline for Soft Underwater Swimmers with Shape Interpolation
ACM Transactions on Graphics, Proceedings of ACM SIGGRAPH, 2021
[Paper] [Video] [Code] [Slides]
Citation
@article{ma2021diffaqua,
  title={DiffAqua: A Differentiable Computational Design Pipeline for Soft Underwater Swimmers with Shape Interpolation},
  author={Ma, Pingchuan and Du, Tao and Zhang, John Z and Wu, Kui and Spielberg, Andrew and Katzschmann, Robert K and Matusik, Wojciech},
  journal={ACM Transactions on Graphics (TOG)},
  volume={40},
  number={4},
  pages={132},
  year={2021},
  publisher={ACM New York, NY, USA}
}
Video
Results
[Shape Exploration]
The illustration of the Wasserstein barycentric interpolation on the shape and the actuators .
[Co-Optimization]
Co-optimization (bottom) outperforms control-only optimization (top 3) when designing the fastest swimmer.
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