In this work, we show that sensors based on soft, intentionally-lossy optical waveguides are well-suited for soft robotic grasping applications in the deep-sea. Each finger of a soft robotic hand is outfitted with a 2×1 array of optical sensing elements to enable proprioception and contact force sensing. Curvature sensing elements are integrated directly into the structure of a finger, while contact force sensors are fabricated as standalone units and attached afterward. Along with considerations for interfacing with deep-sea remotely operated vehicles (ROVs), models for the effect of bending on light loss and the effect of normal force on strain were used to inform sensor design decisions. Our sensors show sensitivity to curvature over a range of diameters from 8 mm to 76 mm, and sub-Newton force sensitivity. Additionally, sensors were characterized in simulated deep-sea environments at temperatures from -10°C to 50°C and hydrostatic pressures up to 4000 psi. The sensitivity of our curvature sensors is invariant to the temperatures and pressure ranges tested, though contact force sensors decreased in sensitivity as temperatures decreased. Finally, we successfully demonstrate that sensors onboard soft finger actuators can provide informative state feedback during grasping operations in air and water.

Many areas of robotics, particularly locomotion and grasping, can benefit from the ability to modulate friction on surfaces that come into contact with objects in the environment. Previous research has tried to address the challenge of tunable friction; however, those efforts only provide modest gains or are difficult to integrate. We propose a tunable friction mechanism that relies on pneumatic actuation and is easily integrated into pre-existing soft actuators. We characterize the performance of our friction mechanism with quantitative force data for varying preload forces, substrate materials, and inflation pressures. Testing results show that our tunable friction mechanism achieves an order of magnitude differentiation in friction forces between high and low friction states. We demonstrate its potential application in a one degree-of-freedom soft crawler and a soft gripper with actuatable finger friction pads. The crawler successfully propelled itself forward by leveraging asymmetric strokes and the gripper achieved a factor of five differentiation of grip force between engaged and disengaged states of the friction tuning mechanism.