Biomimetic Robotic Fish Research Articles

Numerical study of a self-propelled biomimetic robotic fish driven by pectoral fins in labriform mode

Numerical study of a self-propelled biomimetic robotic fish driven by pectoral fins in labriform mode

Hydrodynamic pressure sensing for a biomimetic robotic fish caudal fin integrated with a resistive pressure sensor

Micro-sensors, such as pressure and flow sensors, are usually adopted to attain actual fluid information around swimming biomimetic robotic fish for hydrodynamic analysis and control. However, most of the reported micro-sensors are mounted discretely on body surfaces of robotic fish and it is impossible to analyzed the hydrodynamics between the caudal fin and the fluid. In this work, a biomimetic caudal fin integrated with a resistive pressure sensor is designed and fabricated by laser machined conductive carbon fibre composites. To analyze the pressure exerted on the caudal fin during underwater oscillation, the pressure on the caudal fin is measured under different oscillating frequencies and angles. Then a model developed from Bernoulli equation indicates that the maximum pressure difference is linear to the quadratic power of the oscillating frequency and the maximum oscillating angle. The fluid disturbance generated by caudal fin oscillating increases with an increase of oscillating frequency, resulting in the decrease of the efficiency of converting the kinetic energy of the caudal fin oscillation into the pressure difference on both sides of the caudal fin. However, perhaps due to the longer stability time of the disturbed fluid, this conversion efficiency increases with the increase of the maximum oscillating angle. Additionally, the pressure variation of the caudal fin oscillating with continuous different oscillating angles is also demonstrated to be detected effectively. It is suggested that the caudal fin integrated with the pressure sensor could be used for sensing thein situflow field in real time and analyzing the hydrodynamics of biomimetic robotic fish.

Investigating the Influence of Counterflow Regions on the Hydrodynamic Performance of Biomimetic Robotic Fish.

Biomimetic robotic fish are a novel approach to studying quiet, highly agile, and efficient underwater propulsion systems, attracting significant interest from experts in robotics and engineering. These versatile robots showcase their ability to operate effectively in various water conditions. Nevertheless, the comprehension of the swimming mechanics and the evolution of the flow field of flexible robots in counterflow regions is still unknown. This paper presents a framework for the self-propulsion of robotic fish that imitates biological characteristics. The method utilizes computational fluid dynamics to analyze the hydrodynamic efficiency of the organisms at different frequencies of tail movement, under both still and opposing flow circumstances. Moreover, this study clarifies the mechanisms that explain how changes in the aquatic environment affect the speed and efficiency of propulsion. It also examines the most effective swimming tactics for places with counterflow. The results suggest that the propulsion effectiveness of robotic fish in counterflow locations does not consistently correspond to various tail-beat frequencies. By utilizing vorticity maps, a comparative analysis can identify situations when counterflow zones improve the efficiency of propulsion.

Autonomous Vision-Based Navigation and Stability Augmentation Control of a Biomimetic Robotic Hammerhead Shark

The application potential of robotic fish embedded with intelligent visual navigation algorithms in underwater autonomous operation is on full display recently. However, the existing visual navigation methods are limited by the underwater visual conditions and the motion characteristics of robotic fish. To this end, this paper proposes a novel autonomous navigation framework integrated with visual stabilization control. In practice, a stereo vision-based navigation network is proposed to generate the guidance law. On this basis, a biomimetic robotic hammerhead shark with a controllable cephalofoil is developed, and a nonlinear model predictive controller for cephalofoil stabilization relying on the dynamic model is elaborately designed. Extensive simulations and underwater experiments are conducted to validate the effectiveness and superiority of the proposed methods, which significantly enhance exploration efficiency and reduce image jitter by 26.02% compared to the traditional methods. The obtained results provide a new idea for underwater robots to autonomously explore the ocean. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is motivated by the problem of vision-based underwater autonomous navigation for a biomimetic robotic fish that possesses underwater visual stability and good maneuverability. The existing visual navigation networks usually generate unexpected navigation instructions when dealing with complex or ambiguous underwater scenes. Additionally, image jitter caused by the rhythmic motion of robotic fish can lead to navigation failure. This paper suggests an integrated navigation framework that includes a biomimetic platform design, a visual stabilization controller, and an intelligent underwater navigation network. Specifically, a novel sphyrnidae-inspired robotic shark is designed as a new platform with superior motion performance. To enhance underwater visual stability, a nonlinear model predictive control-based visual stabilization controller is proposed. Furthermore, a deep stereo attention navigation network based on a parallax attention mechanism is proposed to improve the generalization of vision-based autonomous navigation. A series of underwater search experiments on the robotic shark demonstrate the effectiveness and superiority of the proposed navigation framework. Hopefully, our proposed methods can provide valuable guidance and support for universal underwater robot navigation to accomplish practical marine tasks, such as underwater rescue, resource exploitation, biological observation, and so on.

Kinematic Modeling and Experimental Study of a Rope-Driven Bionic Fish.

This paper presents a biomimetic fish robot featuring a flexible spine driven by cables, which integrates the cable-driven mechanism with a flexible spine. The drive system separates the body and tail fin drives for control, offering enhanced flexibility and ease in achieving phase difference control between the body and tail fin movements compared to the conventional servo motor cascaded structure. A prototype of the biomimetic fish robot was developed, accompanied by the establishment of a kinematic model. Based on this model, a control method for the biomimetic fish is proposed. Additionally, we introduce the concept of prestress to establish a numerical model for the biomimetic fish. Using multi-physical field simulation software, we simulate the two-dimensional autonomous swimming process of the biomimetic fish under different flapping frequencies and solve for its swimming characteristics as well as hydrodynamic properties. Both the simulation and experimental results validate the accuracy of our kinematic model.

MEMS flexible conformal hydrophone based on heterogeneous integration technology

PurposeHuman-induced marine environmental noise, such as commercial shipping and seismic exploration, is concentrated in the low-frequency range. Meanwhile, low-frequency sound signals can achieve long-distance propagation in water. To meet the requirements of long-distance underwater detection and communication, this paper aims to propose an micro-electro-mechanical system (MEMS) flexible conformal hydrophone for low-frequency underwater acoustic signals. The substrate of the proposed hydrophone is polyimide, with silicon as the piezoresistive unit.Design/methodology/approachThis paper proposes a MEMS heterojunction integration process for preparing flexible conformal hydrophones. In addition, sensors prepared based on this process are non-contact flexible sensors that can detect weak signals or small deformations.FindingsThe experimental results indicate that making devices with this process cannot only achieve heterogeneous integration of silicon film, metal wire and polyimide, but also allow for customized positions of the silicon film as needed. The success rate of silicon film transfer printing is over 95%. When a stress of 1 Pa is applied on the x-axis or y-axis, the maximum stress on Si as a pie-zoresistive material is above, and the average stress on the Si film is around.Originality/valueThe flexible conformal vector hydrophone prepared by heterogeneous integration technology provides ideas for underwater acoustic communication and signal acquisition of biomimetic flexible robotic fish.

Numerical simulation of optimizing the swing curve of a 3DOF biomimetic pectoral fin in drag mode

In response to the optimization problem of the motion law of the pectoral fins of biomimetic robotic fish, this paper uses computational fluid dynamics (CFD) methods to achieve the CFD optimization of two types of rigid biomimetic pectoral fins with three degrees of freedom (DOF): elliptical and 8-shaped swing curves. By analyzing the hydrodynamic characteristic curve of the pectoral fins, pressure distribution upstream and downstream of the fin surface, velocity vector of the surrounding flow field during pectoral fin swing, and three-dimensional vortex structure, it is found that when the pectoral fins are pushed forward in an elliptical swing curve, the resistance peak value decreases after two optimizations. However, at the same time, a certain amount of thrust is lost. When the pectoral fin advances in an 8-shaped swinging curve, after two optimizations, the pectoral fins resistance decreases while maintaining an enormous thrust, comprehensively improving the propulsive effect of the pectoral fin on the robotic fish. By substituting the optimized 8-shaped pattern into the robotic fish model, it is found that the flapping angle of 35° has better drag reduction performance, and the average swimming speed of the robotic fish is the fastest at this angle.

Enhancing efficiency and propulsion in bio-mimetic robotic fish through end-to-end deep reinforcement learning

Aquatic organisms are known for their ability to generate efficient propulsion with low energy expenditure. While existing research has sought to leverage bio-inspired structures to reduce energy costs in underwater robotics, the crucial role of control policies in enhancing efficiency has often been overlooked. In this study, we optimize the motion of a bio-mimetic robotic fish using deep reinforcement learning (DRL) to maximize propulsion efficiency and minimize energy consumption. Our novel DRL approach incorporates extended pressure perception, a transformer model processing sequences of observations, and a policy transfer scheme. Notably, significantly improved training stability and speed within our approach allow for end-to-end training of the robotic fish. This enables agiler responses to hydrodynamic environments and possesses greater optimization potential compared to pre-defined motion pattern controls. Our experiments are conducted on a serially connected rigid robotic fish in a free stream with a Reynolds number of 6000 using computational fluid dynamics simulations. The DRL-trained policies yield impressive results, demonstrating both high efficiency and propulsion. The policies also showcase the agent's embodiment, skillfully utilizing its body structure and engaging with surrounding fluid dynamics, as revealed through flow analysis. This study provides valuable insights into the bio-mimetic underwater robots optimization through DRL training, capitalizing on their structural advantages, and ultimately contributing to more efficient underwater propulsion systems.

Propulsion curve analysis and optimisation of biomimetic pectoral fin with three degree of freedom based on multi-layer perception

This paper aims to improve the swimming efficiency of biomimetic robotic fish by optimising its propulsion curve with three degree of freedom (DOF), in which the key is to minimise the resistance during swing backstroke of the pectoral fin. For this purpose, a reference point on the pectoral fin is first selected, and then an 8-shaped propulsion curve is constructed to coordinate rowing and flapping motions. Meanwhile, a propulsion curve of feathering motion is also given correspondingly. On this basis, the overall curvature and curve offset are proposed as measurement parameters for the deformation of the propulsion curve and the proportion of abdominal/dorsal circles in the propulsion curve, respectively. As the motion law of feathering is given in a sinusoidal pattern, a data set of hydrodynamic parameters is obtained for pectoral fin propulsion under different motion parameter conditions by computational fluid dynamics(CFD) numerical simulation. Once again, a propulsion curve optimisation model is established based on multi-layer perception(MLP), which uses the hydrodynamic parameters data set as input. The results show that the resistance of swing backstroke reached the minimum when overall curvature is π/10 and curve offset is 0.4, which is enhanced by 30.13% and 33.33% at thrust and lift direction compared to the existing design, respectively. Furthermore, the flow field structure and hydrodynamic parameters around the robotic fish are calculated by CFD. The results show that two sets of vortex rings are generated around the fish body during a propulsion cycle. The vortex rings detached towards the lower and upper sides of the fish body such that the lift is minimal, the thrust direction is relatively stable, and the resistance is minimal during the swing backstroke. The experimental results indicate that it can raise propulsion efficiency during the pectoral fin propulsion process, verifying the effectiveness of this method.

Autonomous Recovery Control of Biomimetic Robotic Fish Based on Multi-Sensory System

Autonomous Recovery Control of Biomimetic Robotic Fish Based on Multi-Sensory System

Recent Advances in Design, Sensing, and Autonomy of Biomimetic Robotic Fish: A Review

Recent Advances in Design, Sensing, and Autonomy of Biomimetic Robotic Fish: A Review

Current Status and Technical Challenges in the Development of Biomimetic Robotic Fish-Type Submersible

With the continuous deepening of ocean exploration, submersibles have become essential tools that have garnered considerable attention in the academia. As of the 2020s, driven by advancements in materials and various disciplines, the development of submersibles has undergone important transformations compared to their initial state. In this paper, we provide a comprehensive review of the developments in submersible technology from a historical point of view. In particular, we emphasize the emergence of the robotic fish-type submersibles. This process is characterized by the fusion of biomimicry and advanced technologies, and represents the future direction of submersible developments. Thus, we also emphasize the key technological challenges that robotic fish-type submersibles should focus on. Finally, we outline a general procedure for developing biomimetic robotic fish-type submersibles by drawing insights from a recent 2,000-m biomimicry prototype study. We hope to pave a smoother path for the future advancement of submersibles.

Development of the bioinspired propulsion system for a robotic fish

Biomimetic robots aim to replicate the movement principles of living creatures, which have been continuously perfected by nature to ensure survival. Technically, survival comprises two factors: optimizing movement efficacy, such as speed, distance traveled, or acceleration, and minimizing energy consumption during movement. Researchers have made several attempts to develop a biomimetic fish robot [1–3]. Tunas are a group of fish with numerous evolutionary adaptations that make them exceptional swimmers, including tail shape, lateral peduncle keels, pectoral fin shape, and finlets. Thunniform locomotion is characterized by limited undulation, typically restricted to the rear one-third of the body, with maximal amplitude reached at the end of the tail peduncle. A bioinspired propulsion system was developed for a robotic fish model. It is based on the combination of an elastic cord with a tail fin that is firmly attached to the cord. Two symmetric movable thrusts that simulate muscle contractions connect the tail fin to a servomotor. The propulsion system provides oscillatory tail movement that can be controlled for amplitude and frequency. This movement translates to the movement of the robotic fish, which executes the thunniform principle of locomotion. The body and tail fin of the robotic fish were designed using a computational model that simulates a virtual body in water. Subsequently, we constructed a prototype of the robotic fish and tested it under experimental conditions. Experiments were conducted to investigate the relationship between the robot’s kinematics and the dynamic parameters of the propulsion system. The results showed that increasing the frequency of tail fin oscillations led to an increase in the robot’s speed. At fixed frequencies, there was an interval of energetically efficient travel speeds up to a threshold velocity. Movement at higher speeds was achievable; however, it was accompanied by greater power consumption. The conclusion aligns with the data from COT studies on living tunas, indicating qualitative agreement. However, the robot’s values were quantitatively higher. Our robotic fish reached a maximum speed of approximately 0.4 BL/s, exceeding speeds in other works where a simplified tail section was used (0.22 BL/s [4], 0.254 BL/s [5]). Our study demonstrated a correlation between the efficiency of robot swimming and amplitude, which was previously unexplored in addition to previous findings on the relationship between tail beat frequency and swimming speed, as well as the dependence of frequency and swimming speed. The results showed that increasing the oscillation amplitude of the propulsion system, at a fixed frequency, only led to a rise in swimming speed up to a certain threshold. However, further increases in amplitude resulted in minimal speed increases at higher energy costs. An evaluation of energy efficiency was conducted, assessing its dependence on dynamic parameters of tail oscillation. The results show that the transport cost rises as the tail amplitude rises beyond the threshold. Furthermore, it was found that for a fixed frequency, an interval of energetic preferred speeds up to a threshold exists. Although moving at a higher speed is possible, it consumes more power. In general, it is preferable to increase caudal fin oscillation frequency rather than amplitude to increase swimming speed. These findings are in qualitative accordance with the outcomes of the numerical simulation of thunniform swimming.

A Circular Formation Method for Biomimetic Robotic Fish Inspired by Fish Milling.

Circular motion phenomena, akin to fish milling, are prevalent within the animal kingdom. This paper delineates two fundamental mechanisms underlying such occurrences: forward following and circular topological communication. Leveraging these pivotal concepts, we present a multi-agent formation circular model based on a second-order integrator. This model engenders the attainment of homogeneous intelligence convergence along the circumferential trajectory. The convergence characteristics are intricately linked to the number of agents and the model parameters. Consequently, we propose positive and negative solutions for ascertaining the convergent circle property and model parameters. Furthermore, by integrating our proposed formation control methodology with a robotic fish dynamics model, we have successfully implemented simulations and experiments, demonstrating the circular formation of multiple biomimetic robotic fish. This study provides a mathematical explication for the circular motion observed in animal groups and introduces a novel approach to achieving circular formation in multiple robots inspired by biological phenomena.

A Novel Untethered Robotic Fish with an Actively Deformable Caudal Fin

Based on the observation that live fish caudal fins exhibit softness, flexibility, and active deformation, which are essential for generating thrust, stability, and maneuverability, herein, a comprehensive study on a novel type of bionic robotic fish with an actively deformable caudal fin is presented. The article first presents the design of the robot. Next, the quasisteady model theory is used to establish the hydrodynamic force for modeling the deformable caudal fin. Furthermore, three deformation modes are studied and compared: the conventional nondeformable mode, the sine‐based mode, and the instantaneous mode. Finally, a series of extensive experiments are conducted to evaluate various performance metrics of this innovative untethered biomimetic robotic fish, including thrust, swimming speed, yaw stability, turning radius, and turning rate. The results demonstrate that the introduction of active deformation of the caudal fin significantly enhances the swimming performance in the aforementioned indices when compared to the conventional nondeformable mode. Notably, the instantaneous mode exhibits best performance in terms of thrust, swimming speed, turning radius, and turning rate, while the sine‐based mode demonstrates the best yaw stability. Consequently, this research contributes to the advancement of robotic fish design and the development of underwater biomimetic robots.

Development of a Low-Cost Soft Robot Fish With Biomimetic Swimming Performance

Abstract This paper investigates the methodology and techniques for a soft biomimetic robot fish that has a straightforward design, relatively simple fabrication, and low cost. In addition to the investigations of fabrication techniques, we also explore the numerical analysis of the biological fish swimming performance, with its inspiration for robot fish design, which is less studied in the literature. In this research, therefore, various swimming locomotion patterns within the body and/or caudal fin family are analyzed for kinematics and hydrodynamics using analytical methods and computational fluid dynamics (CFD) to inspire the robot fish design for improved swimming performance. By straightforward design and fabrication, the swimming performance of the numerical robot fish is verified by means of simulation using 3D CFD, and the prototype performance is validated using in-water experimental tests. This study showcases a new easy-to-design and easy-to-fabricate robust biomimetic robot fish with comparable swimming performance, which has good potential for purposes like education, research, and entertainment.

Three-Dimensional Printed Biomimetic Robotic Fish for Dynamic Monitoring of Water Quality in Aquaculture.

The extensive water pollution caused by production activities is a key issue that needs to be addressed in the aquaculture industry. The dynamic monitoring of water quality is essential for understanding water quality and the growth of fish fry. Here, a low-cost, low-noise, real-time monitoring and automatic feedback biomimetic robotic fish was proposed for the dynamic monitoring of multiple water quality parameters in aquaculture. The biomimetic robotic fish achieved a faster swimming speed and more stable posture control at a swing angular velocity of 16 rad/s by using simulation analysis. A fast swimming speed (0.4 m/s) was achieved through the control of double-jointed pectoral and caudal fins, exhibiting various types of movements, such as straight swimming, obstacle avoidance, turning, diving, and surfacing. As a demonstration of application, bionic robotic fish were placed in a lake for on-site water sampling and parameter detection. The relative average deviations in water quality parameters, such as water temperature, acidity and alkalinity, and turbidity, were 1.25%, 0.07%, and 0.94%, respectively, meeting the accuracy requirements for water quality parameter detection. In the future, bionic robotic fish are beneficial for monitoring water quality, fish populations, and behaviors, improving the efficiency and productivity of aquaculture, and also providing interesting tools and technologies for science education and ocean exploration.

Research and Experiment on a Bionic Fish Based on High-Frequency Vibration Characteristics.

This paper takes the high-frequency vibration characteristics of a bionic robot fish as the research object. Through research on the vibration characteristics of a bionic fish, we quantified the role of voltage and beat frequency in high-speed and stable swimming. We proposed a new type of electromagnetic drive. The tail is made of 0° silica gel to simulate the elastic characteristics of fish muscles. We completed a series of experimental studies on the vibration characteristics of biomimetic robotic fish. Through the single-joint fishtail underwater experiment, the influence of vibration characteristics on parameters during swimming was discussed. In terms of control, the central mode generator control method (CPG) control model is adopted, and a replacement layer is designed in combination with particle swarm optimization (PSO). By changing the elastic modulus of the fishtail, the fishtail resonates with the vibrator, and the swimming efficiency of the bionic fish is improved. Finally, through the prototype experiment, it is found that the bionic robot fish can achieve high-speed swimming through high-frequency vibration.

LQR Control and Optimization for Trajectory Tracking of Biomimetic Robotic Fish Based on Unreal Engine.

A realistic and visible dynamic simulation platform can significantly facilitate research on underwater robots. This paper uses the Unreal Engine to generate a scene that resembles real ocean environments, before building a visual dynamic simulation platform in conjunction with the Air-Sim system. On this basis, the trajectory tracking of a biomimetic robotic fish is simulated and assessed. More specifically, we propose a particle swarm optimization algorithm-based control strategy to optimize the discrete linear quadratic regulator controller for the trajectory tracking problem, as well as tracking and controlling discrete trajectories with misaligned time series through introducing a dynamic time warping algorithm. Simulation analyses of the biomimetic robotic fish following a straight line, a circular curve without mutation, and a four-leaf clover curve with mutation are carried out. The obtained results verify the feasibility and effectiveness of the proposed control strategy.

Social competence improves the performance of biomimetic robots leading live fish

Collective motion is commonly modeled with static interaction rules between agents. Substantial empirical evidence indicates, however, that animals may adapt their interaction rules depending on a variety of factors and social contexts. Here, we hypothesized that leadership performance is linked to the leader’s responsiveness to the follower’s actions and we predicted that a leader is followed longer if it adapts to the follower’s avoidance movements. We tested this prediction with live guppies that interacted with a biomimetic robotic fish programmed to act as a ‘socially competent’ leader. Fish that were avoiding the robot were approached more carefully in future approaches. In two separate experiments we then asked how the leadership performance of the socially competent robot leader differed to that of a robot leader that either approached all fish in the same, non-responsive, way or one that did change its approach behavior randomly, irrespective of the fish’s actions. We found that (1) behavioral variability itself appears attractive and that socially competent robots are better leaders which (2) require fewer approach attempts to (3) elicit longer average following behavior than non-competent agents. This work provides evidence that social responsiveness to avoidance reactions plays a role in the social dynamics of guppies. We showcase how social responsiveness can be modeled and tested directly embedded in a living animal model using adaptive, interactive robots.