Abstract
Underwater soft robots are challenging to model and control because of their high degrees of freedom and their intricate coupling with water. In this letter, we present a method that leverages the recent development in differentiable simulation coupled with a differentiable, analytical hydrodynamic model to assist with the modeling and control of an underwater soft robot. We apply this method to Starfish, a customized soft robot design that is easy to fabricate and intuitive to manipulate. Our method starts with data obtained from the real robot and alternates between simulation and experiments. Specifically, the simulation step uses gradients from a differentiable simulator to run system identification and trajectory optimization, and the experiment step executes the optimized trajectory on the robot to collect new data to be fed into simulation. Our demonstration on Starfish shows that proper usage of gradients from a differentiable simulator not only narrows down its simulation-to-reality gap but also improves the performance of an open-loop controller in real experiments.
Highlights
D EVELOPMENTS in marine robotics provide many advantages for tasks such as underwater exploration, sample collection, and observation of marine wildlife [1]
Aquatic animals demonstrate the advantages of having a soft-body structure for swimming and navigating aquatic environments, highlighting how compliance and flexibility is a key component for efficient underwater locomotion [2] and motivating the design of soft robotic swimmers
We demonstrate the efficacy of our pipeline on Starfish, a customized underwater soft robot design made of silicone foam and actuated with four tendons
Summary
D EVELOPMENTS in marine robotics provide many advantages for tasks such as underwater exploration, sample collection, and observation of marine wildlife [1]. Aquatic animals demonstrate the advantages of having a soft-body structure for swimming and navigating aquatic environments, highlighting how compliance and flexibility is a key component for efficient underwater locomotion [2] and motivating the design of soft robotic swimmers. Date of publication March 31, 2021; date of current version April 20, 2021. This letter was recommended for publication by Associate Editor F. (Tao Du and Josie Hughes contributed to this work.) (Corresponding author: Tao Du.)
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