This article explores a set of locomotion optimization methods for a novel tendon-driven robotic fish. With the typical features of the dual tendon driving active tail and variable stiffness passive caudal fin, a fully functioning tendon-drive robotic fish is developed. Next, a practical dynamic model for the tendon-driven robotic fish is established with full consideration of variable stiffness passive caudal fin, and the model parameters are accurately identified via data-driven methods. More importantly, to improve the motion performances, an asymmetric central pattern generator is particularly proposed, and an adjustment rule of passive stiffness is explored to fit different motion states of the robotic fish. Finally, extensive simulations and aquatic experiments verify the feasibility of the proposed prototype and locomotion optimization methods. The obtained results show that the improvements of steering radius and forward swimming velocity are 36.3% and 29%, respectively. At present, our robotic fish can achieve maximum forward swimming as 1.04 BL/s (BL for the body length), maximum turning rate as 153.3 $^\circ$ /s, and the minimum turning radius reaches to 0.31 BL, providing a valuable reference for bioinspired research of aquatic mechanical design and locomotion control.

For bioinspired underwater robots, it is a great challenge to achieve both high swimming speed and steering maneuverability. To this end, this article presents an untethered high-performance robotic tuna through mechanism optimization and steering strategies design. First, combining the advantages of single-joint and multijoint robotic fish, a novel mechanism of redundant joints is designed to enrich the swimming patterns of the robotic tuna. Next, a three-dimensional dynamic model is established, and the model parameters are accurately identified by experimental data. With the aid of the model and experiments, the speed performance is optimized under the key parameters of tail fin, such as size and flexibility. Further, from the perspective of imitating tuna and the demand of actual operations, two steering strategies are proposed to improve the steering performance. Finally, extensive simulation and experiments verify the effectiveness of the proposed methods. The obtained results reveal that the untethered robotic tuna can achieve both high swimming speed with 2.26 m/s (equivalent to 3.13 body lengths per second) and outstanding steering maneuverability with 0.48 body lengths in turning radius, providing valuable insight into performing special missions in cluttered ocean environments.

This article proposes the mechanical design and dynamic model of an innovative manta-inspired robot system for both efficient fast swimming and high spatial maneuverability. Inspired by some biological studies, a pair of unique pectoral fins with six separate degrees of freedoms (DOFs) are developed. The novel design is characterized by an improved crank-rocker mechanism and a distinctive horizontal DOF. The former not only endows the robot with high swimming speed, but also guarantees efficient flapping patterns which are close to manta rays. The latter is employed to coordinate with the flapping movement, allowing remarkable pitch adjustment. Further, the basic motion strategy is presented by detailed analyses to the pectoral fins. Besides, based on the Morrison equation and infinitesimal method, a complete dynamic model for robotic manta with flexible pectoral fins is established, whose parameters are determined through experimental data. Moreover, the linear swimming and pitching experiments are conducted, demonstrating the prominent movement performance of the presented design and the effectiveness of the dynamic model. The obtained results shed light on updated design and control of next-generation agile underwater vehicles and robots capable of multimodal motions in dynamic and complex aquatic environments.

This article proposes a novel barrier-based adaptive line-of-sight (ALOS) three-dimensional (3-D) path-following system for an underactuated multijoint robotic fish. The framework of the developed path-following system is established based on a detailed dynamic model, including a barrier-based ALOS guidance strategy, three integrated inner-loop controllers, and a nonlinear disturbance observer (NDOB)-based sideslip angle compensation, which is employed to preserve a reliable tracking under a frequently varying sideslip angle of the robotic fish. First, a barrier-based convergence strategy is proposed to deal with probable along-track error disruption and suppress the error within a manageable range. Meanwhile, an improved adaptive guidance scheme is adopted with an appropriate look-ahead distance. Afterward, a novel NDOB-based sideslip angle compensation is put forward to identify the varying sideslip angle independent of speed estimation. Subsequently, inner-loop controllers are intended for regulation about the controlled references, including a super-twisting sliding-mode control (STSMC)-based speed controller, a global fast terminal sliding-mode control (GFTSMC)-based heading controller, and a GFTSMC-based depth controller. Finally, simulations and experiments with quantitative comparison in 3-D linear and helical path following are presented to verify the effectiveness and robustness of the proposed system. This path-following system provides a solid foundation for future marine autonomous cruising of the underwater multijoint robot.

This article proposes a model predictive control (MPC)-based depth control system for the gliding motion of a gliding robotic dolphin. An injector-based buoyancy-driven mechanism is employed to achieve more precise control of net buoyancy. In the system, a novel framework of depth control is proposed on the basis of a simplified model, including a depth controller with improved MPC, a heading controller with velocity-based proportional-integral-derivative, and a sliding mode observer. Extensive simulation and experimental results demonstrate the effectiveness of the proposed control methods. In particular, a variety of slider-based experiments are also conducted to explore the performance of a movable slider in the depth control so as to better govern the gliding angle. The results obtained reveal that it is feasible to realize regular gliding angles via regulating the slider, which offers promising prospects for bio-inspired gliding robots playing a key role in ocean exploration.