Topology-Optimized, Dual-Phase Gripper With Force Estimation for Underwater Operation

Abstract

Addressing the critical trade-off between compliance and grasping force in underwater manipulation, this letter presents a novel topology optimization framework to automate the design of soft, variable-stiffness fingers from a single material. By employing multiple load cases within the optimization objective, our framework automatically synthesizes a finger structure that preserves the adaptive Fin Ray effect while exhibiting programmed, multi-stage stiffness. We utilize this method to realize a dual-phase finger, characterized by low initial stiffness for compliant contact with a compliant object and high subsequent stiffness for secure grasping. Quantitative comparisons validate this achievement with the optimized design yielding a grasping force 3.6 times higher than that of a Fin Ray finger with comparable softness, while simultaneously achieving an adaptation 2.8 times higher than that of a high-force Fin Ray variant. To enable damage-aware teleoperation, a flex sensor is embedded within the finger structure. We establish a mapping to grasping force via a piecewise-regressed model, whose structure directly reflects the finger's dual-phase mechanical behavior. The gripper is validated through a series of underwater experiments ranging from controlled laboratory tests to a nearshore field trial. This work establishes a new pathway for designing automated, single-material soft grippers with direct applications in complex underwater environments.