Robotic Fish Research Articles

Backstepping control of gliding robotic fish for pitch and 3D trajectory tracking

Underwater gliders are known for their energy-efficiency and long-duration operations, with demonstrated applications in ocean exploration, fish tracking, and environmental sampling. Many applications such as exploring a large area of underwater ruins would benefit from accurate trajectory tracking. Trajectory tracking is particularly challenging for underwater gliders due to their under-actuated, highly nonlinear dynamics. Taking gliding robotic fish as an example, a backstepping-based controller is proposed to track the desired pitch angle and reference position in the 3D space. In particular, under-actuation is addressed by exploiting the coupled dynamics and introducing a modified error term that combines pitch and horizontal position tracking errors. Two-time-scale analysis of singularly perturbed systems is used to establish the convergence of all tracking errors to a neighborhood around zero. The effectiveness of the proposed control scheme is demonstrated via simulation and experimental results, and its advantages are shown via comparison with a PID controller and a baseline backstepping controller that does not use the modified error. This paper is accompanied by a video available at: https://youtu.be/D8Vej3weeGc.

NA-CPG: A robust and stable rhythm generator for robot motion control

Central pattern generators (CPGs) have been widely applied in robot motion control for the spontaneous output of coherent periodic rhythms. However, the underlying CPG network exhibits good convergence performance only within a certain range of parameter spaces, and the coupling of oscillators affects the network output accuracy in complex topological relationships. Moreover, CPGs may diverge when parameters change drastically, and the divergence is irreversible, which is catastrophic for the control of robot motion. Therefore, normalized asymmetric CPGs (NA-CPGs) that normalize the amplitude parameters of Hopf-based CPGs and add a constraint function and a frequency regulation mechanism are proposed. NA-CPGs can realize parameter decoupling, precise amplitude output, and stable and rapid convergence, as well as asymmetric output waveforms. Thus, it can effectively cope with large parameter changes to avoid network oscillations and divergence. To optimize the parameters of the NA-CPG model, a reinforcement-learning-based online optimization method is further proposed. Meanwhile, a biomimetic robotic fish is illustrated to realize the whole optimization process. Simulations demonstrated that the designed NA-CPGs exhibit stable, secure, and accurate network outputs, and the proposed optimization method effectively improves the swimming speed and reduces the lateral swing of the multijoint robotic fish by 6.7% and 41.7%, respectively. The proposed approach provides a significant improvement in CPG research and can be widely employed in the field of robot motion control.

Dynamic Modeling and Performance Analysis for a Wire-Driven Elastic Robotic Fish

The complex and continuous undulation of fishtail facilitates extraordinary underwater motion performance for natural fish. For the widely used Multi-Joint robotic fish, a lot of joints are used to simulate continuum fishtail, resulting in some challenges, e.g., the mechanism complexity, friction losses of adjacent joints, load disequilibrium and unsmooth servomotor output power. To overcome these intractable hurdles, motivated by natural fish, this letter proposes a wire-driven elastic robotic fish, which simulates fish muscle through multi-wire drive and adopts a fishlike spine design based on elastic component. Compared with the existing wire-driven robotic fish with discrete multiple-joints-spine and single-wire drive, our robotic fish not only has continuum fishtail, but also can swing with C-Shape and S-Shape owing to multi-wire coupling drive, and simulate the energy storage behavior of fish by elastic component. Further, a Lagrangian dynamic model that models a robotic fish with continuum fishtail and passive flexible joint is developed to explore the propulsive performance and validated by extensive experiments and simulations, and our robotic fish reaches the maximum swimming speed of 0.58 m/s, i.e., 1.04 BL/s. Finally, the superiority of the proposed drive mechanism in disposing of load disequilibrium and smoothing output power of servomotor, is analyzed and validated by the comparisons between a Multi-Joint robotic fish and our robotic fish.

Development of a High-Speed Swimming Robot With the Capability of Fish-Like Leaping

Achieving fast and agile swimming still remains extremely challenging for a self-propelled robotic fish due to the constraint of actuator’s propulsion capability. In this article, we report an untethered bioinspired robotic fish, which combines a high-frequency oscillation and a compliant passive mechanism to realize fast swimming, high pitch maneuvers, and even the leaping motion. For pursuing the explosive propulsion of the robotic fish, we propose an actuation system with a powerful output and a compact structure. A dynamic model is established and indicates that the compliant joint is able to modulate the power transmitted to a caudal fin to affect its velocity in the return stroke for generating more peak thrust. The design is validated with extensive experimental results. Namely, the robotic fish can surprisingly reach up to a speed of 3.8 body lengths per second (BL/s). Compared to the case with a rigid joint, dramatic improvements, involving a speed of 1.2 BL/s and a swimming distance of 141.2 m (70.6%), have been obtained, which reveal that besides the high-frequency oscillation, the compliant passive mechanism is also of great significance to perform high-speed swimming. Additionally, the robotic fish demonstrates its high pitch maneuvers by performing an agile front flip motion with a radius of 0.4 BL and an average angular velocity of 439 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> /s. Most importantly, with a simple control strategy, our robotic fish can remarkably leap out of water completely. Results from this study provide significant insights into the innovative designs of next-generation robotic fishes, which require high speed and maneuverability.

Event-Triggered Control of Robotic Fish With Reduced Communication Rate

Underwater robots often need to communicate with external localization sensors. The low bandwidth in such communications is one of the bottlenecks in achieving accurate tracking control. Toward this end, we adopt a novel periodic event-triggered control (PETC) which allows a robotic fish to reduce its communication load in tracking a desired heading angle with position feedback from an external sensor. To design the PETC, a linear state-space model is derived from a nonlinear dynamic model of the robotic fish with a small perturbation assumption. The PETC consists of an observer, state-feedback controller, integrator, event-trigger rule, and predictor. The observer and state-feedback controller are designed to drive the tracking error to zero. The integrator reduces the steady-state error. The event-trigger rule determines when communication is needed while ensuring the efficacy of the state-feedback controller, and the predictor predicts the state vector for the state-feedback controller when communication is not available. For comparison, an observer-based state feedback control (OSFC) and a proportional-integral-derivative (PID) control are implemented in real-time experiments. Simulations and experimental results show that the PETC can dramatically reduce the number of communication instances without significantly degrading tracking performance, thereby saving communication energy and reducing the need for high bandwidth underwater communication.

Separate Control Strategy for a Biomimetic Gliding Robotic Fish

In this article, we present a novel separate strategy to control the pitch attitude and the gliding direction for a biomimetic gliding robotic fish by the coordination of the external and internal control surfaces. First, we derive the gliding dynamics and hydrodynamics within the framework of the extended angle of attack (AOA), based on which the gliding model is decomposed into pitch and velocity terms. Next, the backstepping and model predictive controllers are designed to regulate pitch angle using a movable mass and an AOA using pectoral fins based on their control features, respectively. Further, extensive simulations encompassing separate control and path following with desired pitch attitude are conducted to verify the feasibility and superiority of the proposed control strategy. More importantly, to capture the real-time gliding states in practical environment, we develop a gliding measurement and control system. Through the system, the aquatic experiments are carried out to further verify the effectiveness of the proposed separate control strategy. The obtained results offer valuable insight into the development of complex motion control of the gliding robots, laying a solid foundation for diversified underwater missions besides visual perception and autonomous docking.

Development and Control of a Bioinspired Robotic Remora for Hitchhiking

Remora, a bony fish, is well known for the remarkable hitchhiking behavior, by which it can transport itself over large distances without too much effort. In this article, a novel robotic remora with a stable adhesion system and its motion control methods are proposed for transferring the hitchhiking behavior to the engineered system. In terms of the mechatronic design, a robotic prototype with the uncoupled planar and vertical motion mechanisms is created to realize the precise and agile movement. Furthermore, a reliable adhesion system possessing low preload demand, considerable adhesive force ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim \text{250}\text{ N}$</tex-math></inline-formula> ), and reversible adhesion ability is developed, and then, the design principle of the adhesive disc is investigated. In the aspect of motion control, a mode-switch-based planar pose (position and orientation) control method and an antidisturbance depth control method are designed. The combination of these two controllers endows the robotic remora with the ability to precisely arrive at any position in a 3-D space, which paves the way for the hitchhiking task. Extensive experimental results are presented to support the performance benefits of the proposed robotic remora and control methods. Finally, the hitchhiking behavior is implemented successfully by robotic remora. To the best of our knowledge, this is the first engineered implementation of hitchhiking for a fin-actuated underwater robot. The results obtained will promote the design and control of the future underwater adhesion robot and offer valuable insights into the long-endurance robotic fish and mother–son multirobot system.

Design and Optimization of an Untethered High-Performance Robotic Tuna

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.

Dynamic modeling of a fish tail actuated by IPMC actuator based on the absolute nodal coordinate formulation

Ionic polymer metal composite (IPMC) is a smart material with low driving voltage, high energy conversion, light weight and simple structure. It is suitable for driving the tail fin of small bionic fish. Actuators made of this material are quite flexible, and they are laborious to accurately describe the complex deformation of structures. Absolute nodal coordinate formulation (ANCF) has great merits in describing large deformation and large displacement problems. In this paper, the feasibility of ANCF in dynamic modeling of a fish tail actuated by IPMC actuator will be explored for the first time. The tail fin is simplified into two forms: a pure flexible IPMC beam and a hybrid beam that consists of an IPMC beam and a fixed rigid beam. The ANCF one-dimensional two-node beam element is adopted. Considering the influence of deformation curvature, the exact expression of generalized elastic force is obtained. The proposed dynamic model can describe the large deformation problem of the flexible beam. The dynamic responses of the pure IPMC beam tail fin and the hybrid tail fin driven by square wave voltage are calculated. The displacement changes of end nodes are compared, and the swing law under different driving voltage amplitude, frequency, and fluid resistance is analyzed. It is found that the driving efficiency of IPMC can be improved by increasing the driving voltage amplitude, reducing the voltage frequency, and reducing the fluid resistance in a certain range. This research would be beneficial to the study of the large swing motion mechanism of bionic robotic fish.

A Review of Locomotion, Control, and Implementation of Robot Fish

A Review of Locomotion, Control, and Implementation of Robot Fish

Analysis of Heading Stability due to Interactions between Pectoral and Caudal Fins in Robotic Boxfish Locomotion

Investigating the interaction between fins can guide the design and enhance the performance of robotic fish. In this paper, we take boxfish as the bionic object and discuss the effect of coupling motion gaits among the two primary propulsors, pectoral and caudal fins, on the heading stability of the body. First, we propose the structure and control system of the bionic boxfish prototype. Second, using a one/two-way fluid–structure interaction numerical method, we analyse the key parameters of the prototype and discuss the influence of pectoral and caudal motion gaits on the hydrodynamic performance. Finally, effect of the pectoral and caudal interactions on heading stability of the prototype is systematically analyzed and verified in experiments. Results show that the course-deviating degree, oscillation amplitudes of yawing, rolling, and pitching exhibited by the prototype are smaller than that caused by single propulsor when the motion gaits of both pectoral and caudal fins are coordinated in a specific range. This paper reveals for the first time the effect of interactions between pectoral and caudal fins, on the stability of body's course by means of Computational Fluid Dynamics and prototype experiments, which provides an essential guidance for the design of robotic fish propelled by multi-fins.

Tail-stiffness optimization for a flexible robotic fish

Undulation regulation in a robotic fish propelled by a passive flexible tail is more similar to that of a natural fish than with a rigid tail, owing to the smooth curvature of the flexible tail. Moreover, it has been observed that fish change the stiffness of their bodies to adapt to various swimming states. Inspired by this, a stiffness optimization scheme is explored for a novel elastic tail, which can improve the performance of the robotic fish. Spring steels are used as passive flexible joints of the fishtail; these can be easily expanded into multi-joint structures and the joint stiffness can be altered by changing the joint size. In this study, the Lagrangian dynamic method is employed to establish a dynamic model of the robotic fish in which passive flexible joints are simplified by a pseudo-rigid-body model. In addition, the hydrodynamics of the head and tail are analyzed using the simplified Morison equation and quasi-steady wing theory, respectively. Furthermore, to determine unknown hydrodynamic parameters in the dynamic model, a parameter identification method is applied. The results show that the identified simulation speeds fit the experimental speeds well within a wide range of stiffness values. Finally, to improve performance, the influence of joint stiffness and frequency on swimming speed is investigated based on the identified dynamic model. At each frequency, the optimal joint stiffness distribution is one that reduces the stiffness from the front to the rear. At the maximum driving frequency of 2.5 Hz, the optimal swimming speed is 0.3 body lengths per second, higher than that when rigid joints are used.

Underwater gas leak detection using an autonomous underwater vehicle (robotic fish)

Gas leaks from subsea oil and gas facilities could cause significant ocean environment damage. Such leaks can cause fire and explosion, for example, a fire on the ocean surface west of Mexico's Yucatan peninsula. Detecting a gas leak is critical in managing fire and explosion risks. This study proposes using autonomous underwater vehicles -robotic fish- for gas leak plume detection. The robotic fish is equipped with advance two well-known deep learning models, Faster RCNN and YOLOV4. A physical experiment system of various sizes of underwater gas leaks is used to generate the benchmark dataset. The results demonstrated the YOLOV4 model has a stronger online real-time capability. It is 43 times faster than the Faster RCNN model with the same level of accuracy. This study verifies the feasibility of integrating deep learning models with the mobile vehicle for real-time autonomous gas leak detection. This contribution will enable the development of a safe and reliable digital twin of subsea emergency management.

Learn to swim: Online motion control of an underactuated robotic eel based on deep reinforcement learning

As a typical underwater robot, the robotic fish has been a hot topic of research in terms of the swimming control method and the reduction of energy consumption. Body flexibility and passive designs have been proven to be effective approaches for improving the swimming performance of robotic fishes. However, the addition of passive structures or motions of these approaches makes it more difficult to control the movement of robotic fish. In this paper, we proposed a deep reinforcement learning-based method for online learning control of a robotic eel with multiple passive structures. First, we designed a robotic eel with two wire-driven segments and two complaint bodies made of elastic material. Second, a simulation model of the robotic eel was built and the validity of the model was tested. Following that, the neural network was trained in simulation and deployed directly on the robotic eel, which was controlled without an underlying control model or strategy and directly online by the neural network. Finally, extensive experiments verified the effectiveness of our control method, which offers a valuable and potential solution for robots difficult to model and control.

Development of a Novel Underactuated Robotic Fish with Magnetic Transmission System

In this study, a robotic fish inspired to carangiform swimmers has been developed. The artifact presents a new transmission system that employs the magnetic field interaction of permanent magnets to ensure waterproofness and prevention from any overload for the structure and the actuating motor. This mechanism converts the rotary motion of the motor into oscillatory motion. Such an oscillating system, along with the wire-driven mechanism of the tail, generates the required traveling wave in the robotic fish. The complete free swimming robotic fish, measuring 179 mm in length with a mass of only 77 g, was able to maintain correct posture and neutral buoyancy in water. Multiple experiments were conducted to test the robotic fish performance. It could swim with a maximal speed of 0.73 body lengths per second (0.13 m/s) at a tail beat frequency of 3.25 Hz and an electric power consumption of 0.67 W. Furthermore, the robotic fish touched the upper bound of the efficient swimming range, expressed by the dimensionless Strouhal number: 0.43 at 1.75 Hz tail beat frequency. The lowest energy to travel 1 meter was 4.73 Joules for the final prototype. Future works will focus on endowing the robot with energy and navigation autonomy, and on testing its potential for real-world applications such as environmental monitoring and animal–robot interaction.

Thrust Improvement of a Biomimetic Robotic Fish by Using a Deformable Caudal Fin.

In nature, live fish has various deformable fins which are capable to promote the swimming speed, efficiency, stability, and thrust generation. However, this feature is rarely possessed by current man-made biomimetic robotic fishes. In this paper, a novel deformable caudal fin platform is proposed to improve thrust generation of biomimetic robotic fish. First, the design of the deformable caudal fin is given, which includes a servo motor, a gear-based transmission mechanism, fin bones, and silica membrane. Second, an improved Central Pattern Generator (CPG) model was developed to coordinately control the flapping of the tail and the deformation of the caudal fin. More specifically, three deformation patterns, i.e., conventional nondeformable mode, sinusoidal-based mode, instant mode, of the caudal fin are investigated. Third, extensive experiments are conducted to explore the effects of deformation of the caudal fin on the thrust generation of the biomimetic robotic fish. It was found that the instant mode of the caudal fin has the largest thrust, which sees a 27.5% improvement compared to the conventional nondeformable mode, followed by the sinusoidal-based mode, which also sees an 18.2% improvement. This work provides a novel way to design and control the deformation of the caudal fin, which sheds light on the development of high-performance biomimetic robotic fish.

Robust Optimization Design for Path Planning of Bionic Robotic Fish in the Presence of Ocean Currents

The bionic robotic fish is one of the special autonomous underwater vehicles (AUV), whose path planning is crucial for many applications including underwater environment detection, archaeology, pipeline leak detection, and so on. However, the uncertain ocean currents increase the difficulty of path planning for bionic robotic fish in practice. In this paper, the path energy consumption is selected as the objective function for path planning, path safety factor, and smoothness are considered as the constraint conditions. The kinematic model is established for bionic robotic fish and, considering the uncertainty of ocean currents, a “min-max” robust optimization problem is proposed in the light of the normal optimization model of path planning for bionic robotic fish. The co-evolutionary genetic algorithm is presented to solve the robust optimization problem with two populations; one population represents the solutions and the other represents the uncertain ocean currents. The objective of the proposed algorithm is to find a robust solution that has the best worst-case performance over a set of possible ocean currents. Multiple experiments indicate that the proposed algorithm is very effective for path planning for bionic robotic fish with ocean currents.

Using inverse learning for controlling bionic robotic fish with SMA actuators

Using inverse learning for controlling bionic robotic fish with SMA actuators

Designing a Multi-Parameter Method to Assess the Adaptation Period of Crucian Carp under Stress Conditions of the Bionic Robot Fish

Changes in the physiological and behavioral states of fish are affected by foreign substances. Therefore, fish need a certain adaptation period to eliminate the stress response. Herein, in order to determine the adaptation period, the bionic robot fish was used to obtain behavioral information about crucian carp, which was tested at five time points (1st, 7th, 14th, 21st and 28th day) within 28 days. First, the fear response and exploratory behavior of crucian carp affected by three-color bionic robot fish were explored. Then, according to the measurement results of the behavior, morphology, and feeding, and the physiological and biochemical properties of the crucian carp, a multi-parameter evaluation method was proposed to determine the adaptation period of the crucian carp under this monitoring mode. The results showed that more than 4 areas were occupied by crucian carp from the 21st day. From the 16th day, the number of crucian carp swimming with clear outlines gradually increased. The number of abnormal swimming occurrences decreased on day 13. More than 80% of the crucian carp body color returned to dark on the 23rd day. The crucian carp did not respond to food until day 19, when most of the crucian carp began to scramble for food. Food consumption reached more than two thirds on day 22. In addition, glucose and total protein leveled off after day 21, when mean hemoglobin levels were highest. Triglycerides showed a trend of first decreasing and then increasing. The pigmented area of the skin section gradually decreases and eventually stabilizes. In summary, it takes at least 23 days for the crucian carp to adapt to the influence of the bionic robot fish.

Trajectory Tracking Control of Rowing Pectoral Fin-Actuated Robotic Fish

Robotic fish has received increasing attention in the last few decades, as they hold strong promise in a myriad of applications. Efficient and precise control of these robots, particularly accurate trajectory control, has become essential in many of these applications. This article proposes a dual-loop backstepping-based trajectory tracking control approach for a robotic fish actuated by rowing pectoral fins. While rowing pectoral fin-based locomotion is important for maneuvering, the range constraints of fin movement pose significant challenges in the control of robotic fish, including potentially preventing the robot from generating the thrust needed to maneuver in a desired direction. To overcome these challenges, we propose a dual-loop controller, designed based on an averaged dynamic model of the robot. In particular, an outer-loop backstepping-based controller finds the needed force and moment inputs for the robot to track the desired trajectory, while the inner loop determines the optimal fin-beat parameters such that the resulting fin-generated forces and moment are close to their desired values. Experimental results are presented to show the efficacy of the proposed control scheme, where the robot is commanded to track a trajectory with variable linear and angular velocities. Comparing to a well-tuned proportional–integral–derivative controller, the proposed control scheme shows a distinct advantage in tracking desired orientations in addition to tracking desired positions.