Abstract
Multistable structures are characterized by the existence of more than one statically stable state, which can provide a reference point for open-loop control schemes leveraging these systems' intrinsic mechanics. Multistable soft robots can thus take advantage of both the adaptability of soft robotics and the mechanical response of multistable elements for the potential simplification of robotic control and predictability. We present an energy-based analytical model for a class of soft multistable grippers enabling the design and prediction of their stable states abstracted as programmed operational points. The analytical model based on lumped parameter springs allows us to predict the system's final state upon actuation with reduced computational time compared to Finite Element (FE) simulations. The obtained computational efficiency enables us to search the configuration space in a tractable fashion, thereby facilitating the rational design of our grippers' set points. We validate our model against FE simulations and experimental tests. The model captures the fundamental mechanics of the introduced soft gripper topology, laying the foundation for efficient design optimization and simplified control of soft robots.
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