Programmable Multistable Soft Grippers

Abstract

Soft robots have attracted significant interest due to their capability to interact, adapt and reconfigure in response to external stimuli. Due to their low modulus constitutive materials, intrinsic safety is embedded in softrobots, allowing them to perform tasks that are nearly impossible with rigid counterparts. Nevertheless, the resulting highly nonlinear response of such materials renders the kinematical prediction and control of soft robots challenging, ofter requiring sophisticated sensing and processing state processing algorithms. Leveraging multistability offers exciting opportunities to encode several stable states of soft robots, ultimately simplifying the actuation and control problems. We present a pneumatically actuated soft gripper with encoded multiple stable states that provide a route to shape reconfiguration without closed-loop control. Informed by the mechanics of hierarchically multistable metastructures, we design coexisting states resembling different actuation modes in soft manipulators, including grasping and twisting. This is achieved by leveraging distinct path-dependent inversion sequences to access desired coexisting states on-demand. Our strategy offers a new route for controlling soft multistable robots exploiting their strong nonlinear mechanics to the designer's advantage.