Modeling Locomotion of a Hydrogel Crawler

Soft smart materials used as actuators play an increasingly important role in the development of soft, biologically compatible locomotion systems. However, their compliant nature and distributed surface interactions make the systems highly complex. While soft body locomotion has been demonstrated at a variety of length scales, the modeling of such systems remains highly specific and ad-hoc. Data-driven geometric mechanics provides a practical framework for characterizing system dynamics for dissipative and underactuated systems. Here, we present a new application of data-driven modeling on a soft crawler made of thermo-responsive hydrogels, materials that swell and shrink as a function of temperature. Forward locomotion requires symmetry breaking, and most prior hydrogel crawlers rely on surface features to break symmetry; the design presented here uses the morphologically tuned, spatially asymmetric hydrogel swelling dynamics to induce locomotion, eliminating the need for specialized surface structures. For this specific system, we show that despite the complexity introduced by the soft body, its body shape can be characterized using a low dimensional shape subspace via straightforward dimensionality reduction (PCA). Based on finite element simulation data, we built and tested a data-driven model for the hydrogel locomotion behavior around its typical temperature cycles. The next step will be to test our locomotion modeling and gait design approach using physical hydrogel robots.