Design, Modeling, and Experiment of Underactuated Flexible Gliding Robotic Fish

In this article, we present the design of an innovative gliding robotic fish with an underactuated flexible tail. Inspired by underwater gliders, we combine the critical modules of a glider, such as the buoyancy regulation module (BRM) and attitude regulation module (ARM), with the main structure of an underactuated robotic fish to develop the gliding robotic fish, which is able to realize two kinds of motion modes, including swimming and gliding. First, an open and modular design method is applied throughout the design of the gliding robotic fish, meaning all nonwaterproof devices are installed in separate small sealed chambers. Then, the dynamic models for swimming motion in the horizontal plane and gliding motion in the vertical plane are established, and the hydrodynamic coefficients used in modeling are estimated by computational fluid dynamics (CFD) simulation. The 1R pseudorigid-body model (PRBM) is used to reflect the bending of the compliant tail during swimming, and the effects of changes in net buoyancy moment, center of gravity (CG) of BRM, and buoyancy moment of ARM are considered in the gliding dynamic model. To validate the performance of gliding robotic fish and the accuracy of the dynamic model, relevant experiments and simulations are conducted, and the differences between them are compared. The results indicate that the gliding robotic fish has promising swimming and gliding performance and reveal the effectiveness of the dynamic model. The research in this article provides inspiration for improving the value of bionic robotic fish in practical applications.

Automated summary

This article presents the design of an innovative gliding robotic fish with a flexible tail. By combining critical modules of a glider with the structure of an underactuated robotic fish, swimming and gliding modes are achieved. The article applies an open and modular design method, establishes dynamic models, and conducts experiments and simulations to validate the performance and accuracy of the model.