Dynamic Mechanical Metamaterials for Underactuated Soft Robotics

Abstract

Soft robots promise rich behaviors with minimal hardware by embedding part of the control in the body. We pursue this idea using flexible mechanical metamaterials as a soft embodiment and focus on the design and validation of a dynamic metamaterial platform for underactuated motion generation. We adopt a dynamic model with ligament-level viscous damping, identify its parameters from quasi-static tests, and validate it quantitatively against dynamic experiments. We compare three fabrication routes for the compliant ligaments. We then adopt an inverse-design framework that tunes the geometry so that a single sinusoidal base input produces closed-loop motion at a user-selected target region. Using a hybrid global–local optimization strategy (CMA-ES + MMA) with an angular momentum objective, the framework automatically discovers non-trivial geometries that generate clockwise or counter-clockwise limit cycles from the same reciprocal input. We further demonstrate frequency-based multifunctionality in simulation: a single architecture switches between opposing closed-loop behaviors (CW vs. CCW) when driven at distinct frequencies. Overall, the results position dynamic metamaterials as a viable soft embodiment that shifts complexity from electronics to morphology, a step toward single-actuator, multigait soft robotic matter.