Automated design of soft-rigid hybrid robots for dynamic locomotion

Rigid-bodied robots often lack compliance needed to adapt to unstructured environments, while fully soft robots, though highly adaptable, struggle with scalability and load capacity. In nature, musculoskeletal systems balance strength and flexibility by integrating hard and soft tissues. Inspired by this principle, we present an automated design method for soft-rigid hybrids that optimizes a freeform soft-body shape, a stiff truss layout, and multi-channel actuation. Our differentiable simulator couples the material point method (MPM) for deformable bodies with extended position-based dynamics (XPBD) for truss elements, enabling gradient-based search. The optimization generates truss skeletons that transmit actuation forces to the soft body. We fabricate the optimized design and evaluate it on a walking task. Experiments reproduce the walking mode predicted by the optimization, which does not emerge without the skeleton. Modal analysis further suggests that the skeleton enables deformation modes near the actuation frequency that promote effective stride generation.