Swimming Robot Research Articles

LUO-V2 and MSPerception: A multi-fin co-drive robotic fish and its multi-sensor-based experimental system

Experimental systems for analyzing robotic fish swimming play a crucial role in optimizing robotic fish, which prompted us to design an experimental system that combines information from multiple sensors to address the shortcomings of current experimental systems with a single measurement. Furthermore, we are interested in a multi-fin co-drive robotic fish. This paper presents the design of a robotic fish, LUO-V2, and an experimental system, MSPerception. The LUO-V2 represents a novel solution for developing multi-fin co-drive robotic fish. It also provides a controller for LUO-V2, which can synchronously control the multi-fin of the robotic fish. Furthermore, the MSPerception system has been designed based on the fusion of multi-sensor information, which can sense the average thrust, swimming speed, and flow field, which provides an effective tool for studying robotic fish swimming. MSPerception was employed to investigate the factors influencing the swimming performance of LUO-V2 and to compare it with the flow field around the caudal fin of a real fish. The experimental results demonstrated that the multi-fin co-drive significantly enhanced the robotic fish’s performance. This research can provide a theorectical foundation for developing multi-fin co-drive robotic fish and experimental systems.

Self‐Propelled Morphing Matter for Small‐Scale Swimming Soft Robots

AbstractAquatic insects have developed versatile locomotion mechanisms that have served as a source of inspiration for decades in the development of small‐scale swimming robots. However, despite recent advances in the field, efficient, untethered, and integrated powering, actuation, and control of small‐scale robots remains a challenge due to the out‐of‐equilibrium and dissipative nature of the driving physical and chemical phenomena. Here, we have designed small‐scale, bioinspired aquatic locomotors with programmable deterministic trajectories that integrate self‐propelled chemical motors and photoresponsive shape‐morphing structures. A Marangoni motor system is developed integrating structural protein networks that self‐regulate the release of chemical fuel with photochemical liquid crystal network (LCN) actuators that change their shape and deform in and out of the surface of water. While the diffusion of fuel from the motor system regulates the propulsion, the dissipative photochemical deformation of LCNs provides locomotors with control over the directionality of motion at the air‐water interface. This approach gives access to five different but interchangeable modes of locomotion within a single swimming robot via morphing of the soft structure. The proposed design, which mimics the mechanisms of surface gliding and posture change of semiaquatic insects such as water treaders, offers solutions for autonomous swimming soft robots via untethered and orthogonal power and control.

Hopping potential wells and gait switching in a fish-like robot with a bistable tail

Fish outperform current underwater robots in speed, agility, and efficiency of locomotion, in part due to their flexible appendages that are capable of rich combinations of modes of motion. In fish-like robots, actuating many different modes of oscillation of tails or fins can become a challenge. This paper presents a highly underactuated (with a single actuator) fish-like robot with a bistable tail that features a double-well elastic potential. Oscillations of such a tail depend on the frequency and amplitude of excitation, and tuning the frequency-amplitude can produce controllable oscillations in different modes leading to different gaits of the robot. This robot design is inspired by recent work on underactuated flexible swimming robots driven by a single rotor. The oscillations of the rotor can propel and steer the robot, but saturation of the rotor makes performing long turns challenging. This paper demonstrates that by adding geometric bistability to the flexible tail, turns can be performed by controllably exciting single-well oscillations in the tail, while exciting double-well oscillations of the tail produces average straight-line motion. The findings of this paper go beyond the application to a narrow class of fish-like robots. More broadly we have demonstrated the use of periodic excitation to produce bistable response that generate different gaits including a steering gait. The mechanics demonstrated here show the feasibility of applications to other mobile soft robots.

Encoding spatiotemporal asymmetry in artificial cilia with a ctenophore-inspired soft-robotic platform

A remarkable variety of organisms use metachronal coordination (i.e., numerous neighboring appendages beating sequentially with a fixed phase lag) to swim or pump fluid. This coordination strategy is used by microorganisms to break symmetry at small scales where viscous effects dominate and flow is time-reversible. Some larger organisms use this swimming strategy at intermediate scales, where viscosity and inertia both play important roles. However, the role of individual propulsor kinematics-especially across hydrodynamic scales-is not well-understood, though the details of propulsor motion can be crucial for the efficient generation of flow. To investigate this behavior, we developed a new soft robotic platform using magnetoactive silicone elastomers to mimic the metachronally coordinated propulsors found in swimming organisms. Furthermore, we present a method to passively encode spatially asymmetric beating patterns in our artificial propulsors. We investigated the kinematics and hydrodynamics of three propulsor types, with varying degrees of asymmetry, using Particle Image Velocimetry and high-speed videography. We find that asymmetric beating patterns can move considerably more fluid relative to symmetric beating at the same frequency and phase lag, and that asymmetry can be passively encoded into propulsors via the interplay between elastic and magnetic torques. Our results demonstrate that nuanced differences in propulsor kinematics can substantially impact fluid pumping performance. Our soft robotic platform also provides an avenue to explore metachronal coordination at the meso-scale, which in turn can inform the design of future bioinspired pumping devices and swimming robots.

Enhanced buoyancy and propulsion in 3D printed swimming micro-robots based on a hydrophobic nano-fibrillated cellulose aerogel and porous lead-free piezoelectric ceramics

This paper provides the first demonstration of additively manufactured swimming micro-robots which combine a hydrophobic nanofibrillated cellulose aerogel, to provide long-term buoyancy, with a low acoustic impedance porous piezoelectric ceramic for improved propulsion. The hydrophobic nanocellulose aerogel is shown to exhibit a high and stable contact angle that was maintained for extended periods of time, which facilitates long-term and stable buoyancy of the micro-robot. To quantify the benefits of introducing porosity into the active piezoelectric element, a new analysis model was developed to inform material design and maximize the acoustic propulsion force. Detailed characterisation and modelling of the swimming robots demonstrated that a swimming robot based on a lead-free porous Ba0.85Ca0.15Zr0.1Ti0.9O3 (BCZT) ceramic exhibited a higher acoustic radiation propulsion force and a faster swimming speed compared to a robot fabricated using a dense ceramic element. These benefits were associated with the lower elastic modulus, density and acoustic impedance of the porous piezoelectric material. The lower dielectric constant, reduced device capacitance, and lower resonant frequency of the porous piezoelectric element also significantly reduced the driving current and power requirements of the robot. This work therefore provides new insights on the impact of hydrophobic and acoustically matched piezoelectric materials on the performance of swimming micro-robots, and successfully demonstrates the use of porosity to improve acoustic impedance matching of resonant piezoelectric devices, such as micro-robots and ultrasonic transducers.

Fish-inspired tracking of underwater turbulent plumes

Autonomous ocean-exploring vehicles have begun to take advantage of onboard sensor measurements of water properties such as salinity and temperature to locate oceanic features in real time. Such targeted sampling strategies enable more rapid study of ocean environments by actively steering towards areas of high scientific value. Inspired by the ability of aquatic animals to navigate via flow sensing, this work investigates hydrodynamic cues for accomplishing targeted sampling using a palm-sized robotic swimmer. As proof-of-concept analogy for tracking hydrothermal vent plumes in the ocean, the robot is tasked with locating the center of turbulent jet flows in a 13,000-liter water tank using data from onboard pressure sensors. To learn a navigation strategy, we first implemented RL on a simulated version of the robot navigating in proximity to turbulent jets. After training, the RL algorithm discovered an effective strategy for locating the jets by following transverse velocity gradients sensed by pressure sensors located on opposite sides of the robot. When implemented on the physical robot, this gradient following strategy enabled the robot to successfully locate the turbulent plumes at more than twice the rate of random searching. Additionally, we found that navigation performance improved as the distance between the pressure sensors increased, which can inform the design of distributed flow sensors in ocean robots. Our results demonstrate the effectiveness and limits of flow-based navigation for autonomously locating hydrodynamic features of interest.

Using Reinforcement Learning to Develop a Novel Gait for a Bio-Robotic California Sea Lion.

While researchers have made notable progress in bio-inspired swimming robot development, a persistent challenge lies in creating propulsive gaits tailored to these robotic systems. The California sea lion achieves its robust swimming abilities through a careful coordination of foreflippers and body segments. In this paper, reinforcement learning (RL) was used to develop a novel sea lion foreflipper gait for a bio-robotic swimmer using a numerically modelled computational representation of the robot. This model integration enabled reinforcement learning to develop desired swimming gaits in the challenging underwater domain. The novel RL gait outperformed the characteristic sea lion foreflipper gait in the simulated underwater domain. When applied to the real-world robot, the RL constructed novel gait performed as well as or better than the characteristic sea lion gait in many factors. This work shows the potential for using complimentary bio-robotic and numerical models with reinforcement learning to enable the development of effective gaits and maneuvers for underwater swimming vehicles.

Dynamics, stability and bifurcations of a planar three-link swimmer with passive visco-elastic joint using “ideal fluid” model

Articulated swimming robots have a promising potential for various marine applications. A common theoretical model assumes ideal fluid, where the viscosity is negligible and the swimmer–fluid interaction is induced by reactive forces originating from added mass effect. Some previous works used this model to study planar multi-link swimmers under kinematic input prescribing all joint angles. Inspired by biological swimmers in nature that utilize body flexibility, in this work we consider an underactuated three-link swimmer where one joint is periodically actuated while the other joint is passive and viscoelastic. Analysis of the swimmer’s nonlinear dynamics reveals that its motion depends significantly on the amplitude and frequency of the actuated joint angle. Optimal frequency is found where the swimmer’s net displacement per cycle is maximized, under symmetric periodic oscillations of the passive joint. In addition, upon crossing critical values of amplitude or frequency, the system undergoes a bifurcation where the symmetric periodic solution loses stability and asymmetric solutions evolve, for which the swimmer moves along an arc. We analyze these phenomena using numerical simulations and analytical methods of perturbation expansion, harmonic balance, Floquet theory, and Hill’s determinant. The results demonstrate the important role of parametric excitation in stability and bifurcations of motion for flexible underactuated locomotion.

RL-CWtrans Net: multimodal swimming coaching driven via robot vision.

In swimming, the posture and technique of athletes are crucial for improving performance. However, traditional swimming coaches often struggle to capture and analyze athletes' movements in real-time, which limits the effectiveness of coaching. Therefore, this paper proposes RL-CWtrans Net: a robot vision-driven multimodal swimming training system that provides precise and real-time guidance and feedback to swimmers. The system utilizes the Swin-Transformer as a computer vision model to effectively extract the motion and posture features of swimmers. Additionally, with the help of the CLIP model, the system can understand natural language instructions and descriptions related to swimming. By integrating visual and textual features, the system achieves a more comprehensive and accurate information representation. Finally, by employing reinforcement learning to train an intelligent agent, the system can provide personalized guidance and feedback based on multimodal inputs. Experimental results demonstrate significant advancements in accuracy and practicality for this multimodal robot swimming coaching system. The system is capable of capturing real-time movements and providing immediate feedback, thereby enhancing the effectiveness of swimming instruction. This technology holds promise.

Minimal actuation and control of a soft hydrogel swimmer from flutter instability

Micro-organisms propel themselves in viscous environments by the periodic, nonreciprocal beating of slender appendages known as flagella. Active materials have been widely exploited to mimic this form of locomotion. However, the realization of such coordinated beating in biomimetic flagella requires complex actuation modulated in space and time. We prove through experiments on polyelectrolyte hydrogel samples that directed undulatory locomotion of a soft robotic swimmer can be achieved by untethered actuation from a uniform and static electric field. A minimal mathematical model is sufficient to reproduce, and thus explain, the observed behavior. The periodic beating of the swimming hydrogel robot emerges from flutter instability thanks to the interplay between its active and passive reconfigurations in the viscous environment. Interestingly, the flutter-driven soft robot exhibits a form of electrotaxis whereby its swimming trajectory can be controlled by simply reorienting the electric field. Our findings trace the route for the embodiment of mechanical intelligence in soft robotic systems by the exploitation of flutter instability to achieve complex functional responses to simple stimuli. While the experimental study is conducted on millimeter-scale hydrogel swimmers, the design principle we introduce requires simple geometry and is hence amenable for miniaturization via micro-fabrication techniques. We believe it may also be transferred to a wider class of soft active materials.

Towards Fish Welfare in the Presence of Robots: Zebrafish Case

Zebrafish (Danio rerio) have emerged as a valuable animal model for neurobehavioral research, particularly in the study of anxiety-related states. This article explores the use of conceptual models to investigate stress, fear, and anxiety in zebrafish induced by bio-inspired mini-robotic fish with different components and designs. The objective is to optimize robotic biomimicry and its impact on fish welfare. Previous studies have focused on externally controlled fish models, whereas this study introduces prototypes of freely actuated swimming robots to examine interactions between a bio-inspired robot and individual zebrafish. By means of analysis of behavioral responses, certain robotic components have been identified as potential causes of anxiety in fish, which have provided insights that may be applicable to other species and future aquacultural robot designs.

Bridging nonlinear dynamics and physiology: Implications for CPGs and biomimetic robotics. Reply to comments on “Control of movement of underwater swimmers: Animals, simulated animates and swimming robots”

Bridging nonlinear dynamics and physiology: Implications for CPGs and biomimetic robotics. Reply to comments on “Control of movement of underwater swimmers: Animals, simulated animates and swimming robots”

Functional soft robotic composites based on organic photovoltaic and dielectric elastomer actuator.

Improving the energy efficiency of robots remains a crucial challenge in soft robotics, with energy harvesting emerging as a promising approach to address it. This study presents a functional soft robotic composite called OPV-DEA, which integrates flexible organic photovoltaic (OPV) and dielectric elastomer actuator (DEA). The composite can simultaneously generate electrostatic bending actuation and harvest energy from external lights. Owing to its simplicity and inherent flexibility, the OPV-DEA is poised to function as a fundamental building block for soft robots. This study aimed to validate this concept by initially establishing the fabrication process of OPV-DEA. Subsequently, experimental samples are fabricated and characterized. The results show that the samples exhibit a voltage-controllable bending actuation of up to 15.6° and harvested power output of 1.35 mW under an incident power irradiance of 11.7 mW/cm2. These performances remain consistent even after 1000 actuation cycles. Finally, to demonstrate the feasibility of soft robotic applications, an untethered swimming robot equipped with two OPV-DEAs is fabricated and tested. The robot demonstrates swimming at a speed of 21.7mm/s. The power consumption of the robot is dominated by a high-voltage DC-DC converter, with a value approximately 1.5 W. As a result, the on-board OPVs cannot supply the necessary energy during locomotion simultaneously. Instead, they contribute to the overall system by charging a battery used for the controller on board. Nevertheless, these findings suggest that the OPV-DEA could pave the way for the development of an unprecedented range of functional soft robots.

Nature-inspired miniaturized magnetic soft robotic swimmers

State-of-the-art biomedical applications such as targeted drug delivery and laparoscopic surgery are extremely challenging because of the small length scales, the requirements of wireless manipulation, operational accuracy, and precise localization. In this regard, miniaturized magnetic soft robotic swimmers (MSRS) are attractive candidates since they offer a contactless mode of operation for precise path maneuvering. Inspired by nature, researchers have designed these small-scale intelligent machines to demonstrate enhanced swimming performance through viscous fluidic media using different modes of propulsion. In this review paper, we identify and classify nature-inspired basic swimming modes that have been optimized over large evolutionary timescales. For example, ciliary swimmers like Paramecium and Coleps are covered with tiny hairlike filaments (cilia) that beat rhythmically using coordinated wave movements for propulsion and to gather food. Undulatory swimmers such as spermatozoa and midge larvae use traveling body waves to push the surrounding fluid for effective propulsion through highly viscous environments. Helical swimmers like bacteria rotate their slender whiskers (flagella) for locomotion through stagnant viscid fluids. Essentially, all the three modes of swimming employ nonreciprocal motion to achieve spatial asymmetry. We provide a mechanistic understanding of magnetic-field-induced spatiotemporal symmetry-breaking principles adopted by MSRS for the effective propulsion at such small length scales. Furthermore, theoretical and computational tools that can precisely predict the magnetically driven large deformation fluid–structure interaction of these MSRS are discussed. Here, we present a holistic descriptive review of the recent developments in these smart material systems covering the wide spectrum of their fabrication techniques, nature-inspired design, biomedical applications, swimming strategies, magnetic actuation, and modeling approaches. Finally, we present the future prospects of these promising material systems. Specifically, synchronous tracking and noninvasive imaging of these external agents during in vivo clinical applications still remains a daunting task. Furthermore, their experimental demonstrations have mostly been limited to in vitro and ex vivo phantom models where the dynamics of the testing conditions are quite different compared the in vivo conditions. Additionally, multi-shape morphing and multi-stimuli-responsive modalities of these active structures demand further advancements in 4D printing avenues. Their multi-state configuration as an active solid-fluid continuum would require the development of multi-scale models. Eventually, adding multiple levels of intelligence would enhance their adaptivity, functionalities, and reliability during critical biomedical applications.

Miniature soft robots modeled after microorganisms

Magnetic soft robotic swimmers are reliable and fully controllable, allowing them to have widespread biomedical and microfluidic applications

Learning control for body caudal undulation with soft sensory feedback

Soft bio-mimetic robotics is a growing field of research that seeks to close the gap with animal robustness and adaptability where conventional robots fall short. The embedding of sensors with the capability to discriminate between different body deformation modes is a key technological challenge in soft robotics to enhance robot control–a difficult task for this type of systems with high degrees of freedom. The recently conceived Linear Repetitive Learning Estimation Scheme (LRLES)–to be included in the traditional Proportional–integral–derivative (PID) control–is proposed here as a way to compensate for uncertain dynamics on a soft swimming robot, which is actuated with soft pneumatic actuators and equipped with soft sensors providing proprioceptive information pertaining to lateral body caudal bending akin to a goniometer. The proposed controller is derived in detail and experimentally validated, with the experiment consisting of tracking a desired trajectory for the bending angle envelope while continuously oscillating with a constant frequency. The results are compared vis a vis those achieved with the traditional PID controller, finding that the PID endowed with the LRLES outperforms the PID controller (though the latter has been separately tuned) and experimentally validating the novel controller’s effectiveness, accuracy, and matching speed.

Electricity-Driven Strategies for Bioinspired Multifunctional Swimming Marangoni Robots Based on Super-Aligned Carbon Nanotube Composites.

Marangoni actuators that are propelled by surface tension gradients hold significant potential in small-scale swimming robots. Nevertheless, the release of "fuel" for conventional chemical Marangoni actuators is not easily controllable, and the single swimming function also limits application areas. Constructing controllable Marangoni robots with multifunctions is still a huge challenge. Herein, inspired by water striders, electricity-driven strategies are proposed for a multifunctional swimming Marangoni robot (MSMR), which is fabricated by super-aligned carbon nanotube (SACNT) and polyimide (PI) composite. The MSMR consists of a Marangoni actuator and air-ambient actuators. Owing to the temperature gradient generated by the electrical stimulation on the water surface, the Marangoni actuators can swim controllably with linear, turning, and rotary motions, mimicking the walking motion of water striders. In addition, the Marangoni actuators can also be driven by light. Importantly, the air-ambient actuators fabricated by SACNT/PI bilayer structures demonstrate the function of grasping objects on the water surface when electrically Joule-heated, mimicking the predation behavior of water striders. With the synergistic effect of the Marangoni actuator and air-ambient actuators, the MSMR can navigate mazes with tunnels and grasp objects. This research will provide a new inspiration for smart actuators and swimming robots.

Delayed feedback control of synchronization patterns: Comment on “Control of movement of underwater swimmers: Animals, simulated animates and swimming robots” by S.Yu. Gordleeva et al.

Delayed feedback control of synchronization patterns: Comment on “Control of movement of underwater swimmers: Animals, simulated animates and swimming robots” by S.Yu. Gordleeva et al.

Movement control mechanism of underwater swimmers via resonance entrainment of central pattern generators Comment on “Control of movement of underwater swimmers: Animals, simulated animates and swimming robots” by Gordleeva et al.

Movement control mechanism of underwater swimmers via resonance entrainment of central pattern generators Comment on “Control of movement of underwater swimmers: Animals, simulated animates and swimming robots” by Gordleeva et al.

Effects of caudal fin stiffness on optimized forward swimming and turning maneuver in a robotic swimmer

In animal and robot swimmers of body and caudal fin (BCF) form, hydrodynamic thrust is mainly produced by their caudal fins, the stiffness of which has profound effects on both thrust and efficiency of swimming. Caudal fin stiffness also affects the motor control and resulting swimming gaits that correspond to optimal swimming performance; however, their relationship remains scarcely explored. Here using magnetic, modular, undulatory robots (μBots), we tested the effects of caudal fin stiffness on both forward swimming and turning maneuver. We developed six caudal fins with stiffness of more than three orders of difference. For a μBot equipped with each caudal fin (and μBot absent of caudal fin), we applied reinforcement learning in experiments to optimize the motor control for maximizing forward swimming speed or final heading change. The motor control of μBot was generated by a central pattern generator for forward swimming or by a series of parameterized square waves for turning maneuver. In forward swimming, the variations in caudal fin stiffness gave rise to three modes of optimized motor frequencies and swimming gaits including no caudal fin (4.6 Hz), stiffness <10−4 Pa m4 (∼10.6 Hz) and stiffness >10−4 Pa m4 (∼8.4 Hz). Swimming speed, however, varied independently with the modes of swimming gaits, and reached maximal at stiffness of 0.23 × 10−4 Pa m4, with the μBot without caudal fin achieving the lowest speed. In turning maneuver, caudal fin stiffness had considerable effects on the amplitudes of both initial head steering and subsequent recoil, as well as the final heading change. It had relatively minor effect on the turning motor program except for the μBots without caudal fin. Optimized forward swimming and turning maneuver shared an identical caudal fin stiffness and similar patterns of peduncle and caudal fin motion, suggesting simplicity in the form and function relationship in μBot swimming.