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.
翻译:软水下游泳器的计算设计具有挑战性,因为软体体型模型的自由度较高。 在本文中,我们展示了一条不同的管道,用于共同设计软游泳器的几何测量和控制器。 我们的管道打开了基于梯度的算法,用于发现新游泳器的设计,比传统的无梯度解决方案效率更高。 我们建议瓦瑟斯坦温温温岩中心作为软水下游泳器的几何设计的基础,因为它是不同的,并且可以自然地通过最佳运输在生物启发基形之间进行干涉。 通过将这一设计空间与不同的模拟和控制结合起来,我们可以有效地优化软水下游泳器的性能,而模拟方法比基线方法要少。 我们展示了我们方法在快速、稳定和节能游泳等各种设计问题上的功效,并展示了多目标设计的适用性。