Robotic Fish Research Articles

Numerical and Experimental Study on Caudal Fin Oscillation Mode in Hemispherical Space

Abstract Attaining multidimensional movements, such as cruising, diving, and turning, is a crucial challenge in the development of bionic robotic fish. When only focusing on caudal fin movements, the caudal fin of a tuna generates significant lateral and propulsive forces and weak lift, while in contrast, the caudal fin of a dolphin generates significant lift and propulsive forces and weak lateral forces. The paper introduces a novel caudal fin oscillation mode for the hemispherical space, which extends the caudal fin oscillation features observed in tuna and dolphin to a broader range of organisms. First, we presented the concept of hemispherical space caudal fin oscillation mode, and demonstrated the principle of lift distribution through theoretical calculations. Moreover, we detailed the force distribution obtained by the robotic fish under different caudal fin oscillation modes through numerical simulations. Finally, we experimentally validated the feasibility of the hemispherical space caudal fin oscillation mode. The results indicate that by modifying the oscillation mode of the caudal fin in bionic robotic fish, it is possible to distribute the lift generated by the fin movement to various forces that aid in achieving multidimensional movement, including propulsive, lateral, and lift forces.

Design, simulation, and experimental investigation on a novel robot fish driven by piezoelectric bimorphs

The efficient swimming performance of fish is a miracle of nature, and the bionic robot fish powered by smart materials can replicate the movement pattern of fish to a greater extent. To achieve a simple, flexible, and controllable underwater robot, a novel robot fish driven by piezoelectric bimorphs is proposed in this study, which has similar swimming patterns to the body and/or caudal fin propulsion swimming mode and can achieve straight travel and steering underwater. The validity and feasibility of the principles were verified by wet mode simulation. A prototype is manufactured and tested for underwater vibration characteristics to confirm the motion pattern of the caudal fin of the robot fish. It weighs 13.3 g, a length of 150 mm. The maximum uniform speed of the robot fish prototype is 53 mm s−1, the thrust is 2.213 mN, and its maximum efficiency is 0.864%.

Implementation of Autonomous Docking and Charging for a Supporting Robotic Fish

Underwater energy supplements for autonomous underwater vehicles (AUVs) are significant for ocean exploitation owing to energy storage and data communication limitations. Aiming at the energy supplement for bionic robotic fish, an autonomous recharging-oriented docking approach is proposed in this paper. First, an omnidirectional docking system containing a supporting robotic fish capable of visual recognition and wireless charging and a docking platform is presented. Next, five locomotive modes are designed and analyzed based on the hybrid swimming and gliding patterns for the robot fish. Utilizing the five modes, a docking procedure is planned, and an onboard-visual-based autonomous docking control strategy is presented. Aquatic experiments, including docking with the platform and refloating a small robot, are performed to verify the effectiveness of the proposed approach. The obtained results offer valuable insights into the development of autonomous docking of bionic robots, laying a solid foundation for the permanent operation of various underwater devices and robots.

Barrier-Based Adaptive Line-of-Sight 3-D Path-Following System for a Multijoint Robotic Fish With Sideslip Compensation.

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.

Kinematic and hydrodynamic modeling of a wire-driven robotic fishtail: An experimental study

Robotic fish have been extensively developed for scientific research and engineering applications, with the robotic fishtail serving as a crucial component. Due to the complex deformation mechanism and hydrodynamic interaction, it remains a significant challenge to establish a real-time precise kinematic and hydrodynamic model for flapping robotic fishtails. This paper presents a kinematic and hydrodynamic model for a wire-driven robotic fishtail, incorporating experimental investigation. The wire-driven mechanism featuring a continuously compliant backbone and position-variable vertebrae is developed, enabling more flexible fishtail flapping and adjustable fish morphology. The kinematic and hydrodynamic models are established through the quasi-static method with proposed corrections accounting for flapping velocity and nonlinear backbone deformation during a flapping stroke, precisely assessing real-time hydrodynamic responses. The proposed models have been validated through physical tests in an open-water environment, and exhibit superior response predictive ability compared to traditional methods. A significant force peak is observed at the beginning of a flapping stroke, while small amount of reversed thrust occurs at its end. In a high-frequency flapping motion, the soft caudal fin generates greater thrust than a hard fin. Comprehensively, this study presents a systematic research methodology for modeling and experimental investigation of novel robotic fishtails and biomimetic propellers.

Multi-Joint Bionic Mechanism Based on Non-Circular Gear Drive.

Aiming at the nonlinear expansion/contraction drive problem between different cables in multi-joint cable drive mechanisms, a mechanical drive method based on a non-circular gear drive was proposed, which could replace the servo-sensing control system and minimize the system's complexity and cost. A multi-joint single-degree-of-freedom (DOF) bending mechanism was constructed with several T-shaped components and cross-shaped components. The principle of the multi-joint mechanism driven by non-circular gears was clarified. The corresponding relationships between the joint bending angle, cables' extension/retraction amount and non-circular gear transmission ratio were established. Using the Bowden cable driving, a multi-DOF bending mechanism decoupling scheme was proposed. Considering the adverse effect of non-circular gear hysteresis on the motion of multi-joint mechanisms, a non-circular gear backlash elimination method was proposed. The expression of the backlash of the non-circular gear with respect to the axial movement amount was deduced, which could enable the precise control of the backlash. A two-DOF multi-joint bionic mechanism driven by the non-circular gear was developed. The experimental results show that the mechanism can achieve coordinated bending motion by precisely controlling the line extension/contraction through non-circular gears. This multi-joint bionic mechanism driven by non-circular gears has the characteristics of reliable structure and simple control, and it is expected to be applied to bionic fish and bionic quadruped robots in the future.

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.

Autonomous Skill Learning of Water Polo Ball Heading for a Robotic Fish: Curriculum and Verification

This paper concerns the autonomous skill learning of water polo ball heading for a robotic fish in highly dynamic aquatic environments via Multi-stage Serial-Parallel Curriculum Learning (MSPCL). First, a radio-controlled robotic fish with hybrid fin propulsion is presented. Moreover, the water polo ball heading task is decomposed into two sequential subtasks: preparation and shooting. In order to cope with the multi-stage complex tasks, based on the easy-to-hard curriculum learning strategy, a novel MSPCL framework is proposed for the robotic fish to learn complex skills, which mainly includes curriculum scheduler, difficulty criterion, serial-parallel curriculum generation and performance measure modules. Furthermore, under the MSPCL framework, Soft Actor-Critic (SAC) algorithm is utilized for training the policy network. Therefore, the robotic fish can learn how to head the water polo ball via the proposed MSPCL method. Comparative simulations are carried out to verify the effectiveness of the MSPCL framework. Finally, the proposed MSPCL method is applied to a physical robotic fish named RoboDact. Swimming pool experiments of water polo ball heading of the RoboDact are conducted to demonstrate the validity and robustness of the proposed method.

Distributed Adaptive Formation Reconfiguration Control for Multiple AUVs Based on Affine Transformation in Three-Dimensional Ocean Environments

This article addresses the distributed formation reconfiguration control problem for a fleet of nonlinear multiple autonomous underwater vehicles (AUVs) in three-dimensional (3-D) ocean environments. A novel solution to the nonplanar multi-AUV formation reconfiguration control issue is presented by using the graph rigidity and affine transformation (GR-AT) method. Firstly, all AUVs cooperatively achieve a predefined initial cube formation by using the strategy of regulating the inter-AUV distances in a rigid graph. Then the proposed GR-AT method is used to reconstruct the formation shape in multi-obstacle underwater environments. A rigorous Lyapunov stability analysis shows that these distances converge to desired values. The efficiency of the formation reconfiguration control algorithm is confirmed by a series of simulation results. Finally, the corresponding 3-D realistic experiment based on bionic robot fish is carried out to validate the feasibility of the proposed formation control.

A Review of Robotic Fish Based on Smart Materials.

The present study focuses on summarizing the recent advancements in the field of fish swimming mode research and bionic robotic fish prototypes based on smart materials. It has been widely acknowledged that fish exhibit exceptional swimming efficiency and manoeuvrability compared to conventional underwater vehicles. In the pursuit of developing autonomous underwater vehicles (AUVs), conventional experimental methods often prove to be complex and expensive. Hence, the utilization of computer simulations for hydrodynamic modelling provides a cost-effective and efficient approach for analysing the swimming behaviour of bionic robotic fish. Additionally, computer simulations can provide data that are difficult to obtain through experimental methods. Smart materials, which integrate perception, drive, and control functions, are increasingly being applied to bionic robotic fish research. However, the utilization of smart materials in this field is still an area of ongoing research and several challenges remain unresolved. This study provides an overview of the current state of research on fish swimming modes and the development of hydrodynamic modelling. The application of four distinct types of smart materials in bionic robotic fish is then reviewed, with a focus on analysing the advantages and disadvantages of each material in driving swimming behaviour. In conclusion, the paper highlights the key technical challenges that must be addressed for the practical implementation of bionic robotic fish and provides insights into the potential future directions of this field.

Design and Fabrication of Bio-Inspired Robotic Systems for Developed Mobility and Functionality in Unstructured Environments

In turn, bio-inspired robotic systems have significantly contributed to the development of well-abled robots capable of moving and manipulating with ease in unknown environments. Imitating biological creatures in their mechanisms of adaptation and effectiveness of design gives these robots enhanced qualities of mobility, functionality, and resilience. In fact, major advances build on flexible joints, controlled underactuation, adaptive control, and sensory arrays of high quality, enabling these robots to traverse rough environments and perform high-precision operations inside the human body. For instance, snake-like robots should be able to move through narrow gaps and debris in some kind of search and rescue task much like a real snake, robotic fish can move effectively across underwater environments while monitoring water quality and marine life. These advancements in technology have broadened the sphere of application and effectiveness of robot applications, proving to be valuable tools in many areas, including disaster response, environmental monitoring, and space exploration. In this regard, one also realizes their significance due to the context of bio-inspired robots regarding the capability of data collection and analyses. The usual methods of data collection are generally limited in reach, recurrence, and resolution. Bio-inspired robots compensate for these inadequacies by continuously gathering various real-time data from environments not easily reachable for humans. More precise and detailed analysis of data resolution collected through these robots supports advanced techniques such as AI and machine learning. This is a very crucial capacity that is central to applications such as following wildlife, assessing the impacts of climate change, and monitoring pollution levels. The capacity of these robots to provide timely and accurate data ensures efforts in environmental management and conservation. The importance of bioinspired robotics, therefore, comes in the solutions associated with unstructured environments. Through the gains of nature, which have been exploited by evolution, these robots present new solutions that overcome the inability of classical robotic systems. The persistence in the performance and development of this field of science will provide ever-greater achievements, with very probably a very important role in the exploration, understanding, and interaction with the natural world played by bioinspired robotics.

Real-time implementation of deep reinforcement learning controller for speed tracking of robotic fish through data-assisted modeling

This article proposes real-time speed tracking of two-link surface swimming robotic fish using a deep reinforcement learning (DRL) controller. Hydrodynamic modelling of robotic fish is done by virtue of Newtonian dynamics and Lighthill’s kinematic model. However, this includes external unsteady reactive forces that cannot be modeled accurately due to the distributed nature of hydrodynamic behavior. Therefore, a novel data-assisted dynamic model and control method is proposed for the speed tracking of robotic fish. Initially, the cruise speed motion data are collected through experiments. The water-resistance coefficient is estimated using the least mean square fit, which is then adopted in the model. Subsequently, a closed-loop discrete-time DRL controller trained through a soft actor-critic (SAC) agent is implemented through simulations. SAC overcomes the brittleness problem encountered by other policy gradient approaches by encouraging the policy network for maximum exploration and not assigning a higher probability to any single part of actions. Due to this robustness in the policy learning, the convergence error becomes low in RL-SAC than RL-DDPG controller. The simulation results verify that the DRL-SAC control with data-assisted modelling substantially improves the speed tracking performance. Further, this controller is validated in real-time, and it is observed that the SAC-trained controller tracks the desired speed more accurately than the DDPG controller.

Modeling of soft fluidic actuators using fluid–structure interaction simulations with underwater applications

Soft robots have been developed for a variety of applications including gripping, locomotion, wearables and medical devices. For the majority of soft robots, actuation is performed using pneumatics or hydraulics. Many previous works have addressed the modeling of these fluid-driven soft robots using static finite element simulations where the pressure inside the actuator is assumed to be constant and uniform. The assumption of constant internal pressure is a useful simplification but introduces significant errors during events such as pressurization, depressurization, and transient loads from a liquid environment. Applications that use soft actuators for locomotion or propulsion operate using a sequence of transient events, so accurate simulation of these events is critical to optimizing performance. To improve the simulation of soft fluidic actuators and enable the modeling of both internal and external fluid flow in underwater applications, this work describes a fully-coupled, three-dimensional fluid–structure interaction simulation approach, where the pressure and flow dynamics are explicitly solved. This approach provides a realistic simulation of soft actuators in fluid environments, and permits the optimization of transient responses, which may be due to a combination of environmental fluid loads and non-uniform pressurization. The proposed methods are demonstrated in a number of case studies and experiments for a range of actuation and both internal and external inlet flow configurations, including bending actuators, a soft robotic fish fin for propulsion, and experimental results of a bending actuator in a high-speed fluid, which correlate closely with simulations. The proposed approach is expected to assist in the design, modeling, and optimization of bioinspired soft robots in underwater applications.

A distributed control method for flexible robotic fish based on PDE

AbstractAt present, research on flexible robotic fish has become a hot topic. Here, a novel dynamic model of flexible robotic fish is established, and a new control method for flexible robotic fish is proposed. Based on the Hamilton principle, the dynamic model of the flexible robotic fish is established by a partial differential equation, which obtains the relationship between the motion law and the force of the flexible robotic fish. The proposed control method produces the practical motion of flexible robotic fish along with any reference motion of flexible robotic fish, and it is proven that the attitude error is stable in a certain range by using the Lyapunov direct method and simulation. Control parameters are explored to reflect the influence on the control effect. For robotic fish, simulation results indicate that the proposed method can generate more than 10% greater propulsive force than some kinds of traditional control methods and improve the forward propelling efficiency of robotic fish.

Design, fabrication, and realisation of a robotic fish actuated by dielectric elastomer with a passive fin

AbstractRobotic fish actuated by smart materials has attracted extensive attention and has been widely used in many applications. In this study, a robotic fish actuated by dielectric elastomer (DE) films is proposed. The tensile behaviours of DE film VHB4905 are studied, and the Ogden constitutive equation is employed to describe the stress‐strain behaviour of the DE film. The fabrication processes of the robotic fish, including pre‐stretching treatment of the DE films, electrode coating with carbon paste, and waterproof treatment, are illustrated in detail. The dynamic response of the fabricated DE actuators under different excitation voltages is tested based on the experimental setup. Experimental results show that the first‐order natural frequencies of the obtained DE actuator in air is 4.05 Hz. Finally, the swimming performances of the proposed robotic fish at different driving levels are demonstrated, and it achieves an average swimming speed of 20.38 mm/s, with a driving voltage of 5kV at 0.8 Hz.

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.

Locomotion Optimization of a Tendon-Driven Robotic Fish With Variable Passive Tail Fin

This paper 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 (CPG) 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&#x0025; and 29&#x0025;, 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<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula>/s, and the minimum turning radius reaches to 0.31 BL, providing a valuable reference for bio-inspired research of aquatic mechanical design and locomotion control.

Backstepping-Based Tracking Control of Underactuated Aquatic Robots

Increased interest in the use of autonomous aquatic robots in a variety of applications has led to the need for efficient and precise control of these robots. In particular, accurate trajectory control has become of importance in many of these applications. However, the highly nonlinear and underactuated dynamics of many aquatic robots present significant challenges in control. In this work, we propose a trajectory-tracking control approach for a general class of underactuated aquatic robotic systems undergoing planar motion. We demonstrate how a backstepping-based control scheme can be synthesized to ultimately bound three tracking errors (2-D position and orientation), despite the underactuated nature of the system. Via multi-time-scale analysis of singularly perturbed systems, we prove how the control scheme achieves boundedness and convergence of the tracking errors to a neighborhood of the origin. Finally, we implement the proposed scheme on a robotic fish and demonstrate its efficacy via experimental results. This article is complemented with a video: https://youtu.be/7007tUQd3KI.

Proactivity of fish and leadership of self-propelled robotic fish during interaction

Fish interacting with biomimetic robotic fish is beneficial for animal behavior research, particularly in the study of collective behavior. Compared with passive-dragging robotic fish, self-propelled robotic fish floats in water, and its movement matches the flow field formed by the caudal fin oscillation, leading to more realistic interaction with animals. In this paper, we propose a self-propelled koi-mimicking robotic fish entity, develop a system for robotic fish and koi fish interaction, and conduct extensive experiments on quantity variation and parameter variation. The results showed that fish exhibited significantly lower proactivity when alone, and the most proactive case is one robotic fish interacting with two real fish. The experiments on parameter variation indicated that fish may respond more proactivity to robotic fish that swim with high frequency and low amplitude, but may also move together with high-frequency and high-amplitude swimming robotic fish. These findings could provide insights into fish collective behavior, guide the design of further fish-robot interaction experiments, and suggest directions for future improvements in goal-oriented robotic fish platforms.