Search Results (6)

Anguilliform locomotion, an efficient aquatic locomotion mode where the whole body is engaged in fluid–body interaction, contains sophisticated physics. We hypothesized that data-driven modeling techniques may extract models or patterns of the swimmers’ dynamics without implicitly measuring the hydrodynamic variables. This work proposes empirical kinematic control and data-driven modeling of a soft swimming robot. The robot comprises six serially connected segments that can individually bend with the segmental pneumatic artificial muscles. Kinematic equations and relations are proposed to measure the desired actuation to mimic anguilliform locomotion kinematics. The robot was tested experimentally and the position and velocities of spatially digitized points were collected using QualiSys^® Tracking Manager (QTM) 1.6.0.1. The collected data were analyzed offline, proposing a new complex variable delay-embedding dynamic mode decomposition (CDE DMD) algorithm that combines complex state filtering and time embedding to extract a linear approximate model. While the experimental results exhibited exotic curves in phase plane and time series, the analysis results showed that the proposed algorithm extracts linear and chaotic modes contributing to the data. It is concluded that the robot dynamics can be described by the linearized model interrupted by chaotic modes. The technique successfully extracts coherent modes from limited measurements and linearizes the system dynamics. Full article

Anguilliform swimming is one of the most complex locomotion modes, involving various interacting phenomena, necessitating multidisciplinary studies. Eel robots are designed to incorporate biological principles and achieve efficient locomotion by replicating natural anguilliform swimming. These robots are simpler to engineer and study compared to their natural counterparts. Nevertheless, characterizing the robot–environment interaction is complex, demanding computationally expensive fluid dynamics simulations. In this study, we employ machine learning strategies to investigate the temporal evolution of the system and discover a data-driven model. Three methods were studied, including dynamic mode decomposition (DMD), sparse system identification (SINDy using PySINDy package), and autoencoder neural network (AE NN), as a general function approximator. The models were simulated using MATLAB^® R2022 to obtain the prediction errors. The results show that the SINDy model presents less error within the regression range and performs better in extrapolation. Additionally, the SINDy model has a compact form and can explicitly formulate the coupling phenomena amongst the modes. Thus, instead of the standard DMD, we propose the SINDy-DMD approach to describe the anguilliform locomotion of the soft robot. The identified model was employed to recover the system state data matrix. It is concluded that the proposed model with quadratic terms provides a parsimonious representation of the system dynamics. Full article

Bio-inspired robots with elongated anatomy, like eels, are studied to discover anguilliform swimming principles and improve the robots’ locomotion accordingly. Soft continuum robots replicate animal–environment physics better than noncompliant, rigid, multi-body eel robots. In this study, a slender soft robot was designed and tested in an actual swimming experiment in a still-water tank. The robot employs soft pneumatic muscles laterally connected to a flexible backbone and activated with a rhythmic input. The position of seven markers mounted on the robot’s backbone was recorded using QualiSys^® Tracking Manager (QTM) 1.6.0.1. The system was modeled as a fully coupled fluid–solid interaction (FSI) system using COMSOL Multiphysics^® 6.1. Further data postprocessing and analysis were conducted, proposing a new mode decomposition algorithm using simulation data. Experiments show the success of swimming with a velocity of 28 mm/s and at a frequency of 0.9 Hz. The mode analysis allowed the modeling and explanation of the fluctuation. Results disclose the presence of traveling waves related to anguilliform waves obtained by the superposition of two main modes. The similarities of the results with natural anguilliform locomotion are discussed. It is concluded that soft robot undulation is ruled by dynamic modes induced by robot–environment interaction. Full article

Biological evidence demonstrates that fish can tune their body stiffness to improve thrust and efficiency during swimming locomotion. However, the stiffness-tuning strategies that maximize swimming speed or efficiency are still unclear. In the present study, a musculo-skeletal model of anguilliform fish is developed to study the properties of variable stiffness, in which the planar serial-parallel mechanism is used to model the body structure. The calcium ion model is adopted to simulate muscular activities and generate muscle force. Further, the relations among the forward speed, the swimming efficiency, and Young’s modulus of the fish body are investigated. The results show that for certain body stiffness, the swimming speed and efficiency are increased with the tail-beat frequency until reaching the maximum value and then decreased. The peak speed and efficiency are also increased with the amplitude of muscle actuation. Anguilliform fish tend to vary their body stiffness to improve the swimming speed and efficiency at a high tail-beat frequency or small amplitude of muscle actuation. Furthermore, the midline motions of anguilliform fish are analyzed by the complex orthogonal decomposition (COD) method, and the discussions of fish motions associated with the variable body stiffness and the tail-beat frequency are also presented. Overall, the optimal swimming performance of anguilliform fish benefits from the matching relationships among the muscle actuation, the body stiffness, and the tail-beat frequency. Full article

Fish propelled by body and/or caudal fin (BCF) locomotion can achieve high-efficiency and high-speed swimming performance, by changing their body motion to interact with external fluids. This flexural body motion can be prescribed through its curvature profile. This work indicates that when the fish swims with high efficiency, the curvature amplitude reaches a maximum at the caudal peduncle. In the case of high-speed swimming, the curvature amplitude shows three maxima on the entire body length. It is also demonstrated that, when the Reynolds number is in the range of 10⁴–10⁶, the swimming speed, stride length, and Cost of Transport (COT) are all positively correlated with the tail-beat frequency. A sensitivity analysis of curvature amplitude explains which locations change the most when the fish switches from the high-efficiency swimming mode to the high-speed swimming mode. The comparison among three kinds of BCF fish shows that the optimal swimming performance of thunniform fish is almost the same as that of carangiform fish, while it is better not to neglect the reaction force acting on an anguilliform fish. This study provides a reference for curvature control of bionic fish in a future time. Full article

Eel-like fish can exhibit efficient swimming with comparatively low metabolic cost by utilizing sub-ambient pressure areas in the trough of body waves to generate thrust, effectively pulling themselves through the surrounding water. While this is understood at the fish’s preferred swimming speed, little is known about the mechanism over a full range of natural swimming speeds. We compared the swimming kinematics, hydrodynamics, and metabolic activity of juvenile coral catfish (Plotosus lineatus) across relative swimming speeds spanning two orders of magnitude from 0.2 to 2.0 body lengths (BL) per second. We used experimentally derived velocity fields to compute pressure fields and components of thrust along the body. At low speeds, thrust was primarily generated through positive pressure pushing forces. In contrast, increasing swimming speeds caused a shift in the recruitment of push and pull propulsive forces whereby sub-ambient pressure gradients contributed up to 87% of the total thrust produced during one tail-beat cycle past 0.5 BL s⁻¹. This shift in thrust production corresponded to a sharp decline in the overall cost of transport and suggests that pull-dominated thrust in anguilliform swimmers is subject to a minimum threshold below which drag-based mechanisms are less effective. Full article