skip to main content

Title: A Fish-Like Soft-Robotic Model Generates a Diversity of Swimming Patterns

Fish display a versatile array of swimming patterns, and frequently demonstrate the ability to switch between these patterns altering kinematics as necessary. Many hard and soft robotic systems have sought to understand a variety of aspects pertaining to undulatory swimming, but most have been built to focus solely on a subset of those swimming patterns. We have expanded upon a previous soft robotic model, the pneufish, so that it can now simulate a variety of swimming patterns, much like a real fish. We explore the performance space available for this longer soft robotic model, which we call the quad-pneufish, with particular attention to the effects on lateral forces and z-torques produced during locomotion. We show that the quad-pneufish is capable of achieving a variety of midline patterns—including more realistic, fish-like patterns—and introducing a slight amount of co-activation between the left and right sides maintains forward thrust while decreasing lateral forces, indicating an increase in swimming efficiency. Robotic systems that are capable of producing an array of swimming movement patterns hold promise as experimental platforms for studying the diversity of fish locomotor patterns.

Publication Date:
Journal Name:
Integrative and Comparative Biology
Page Range or eLocation-ID:
p. 735-748
Oxford University Press
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Many aquatic animals swim by undulatory body movements and understanding the diversity of these movements could unlock the potential for designing better underwater robots. Here, we analyzed the steady swimming kinematics of a diverse group of fish species to investigate whether their undulatory movements can be represented using a series of interconnected multi-segment models, and if so, to identify the key factors driving the segment configuration of the models. Our results show that the steady swimming kinematics of fishes can be described successfully using parsimonious models, 83% of which had fewer than five segments. In these models, the anterior segments were significantly longer than the posterior segments, and there was a direct link between segment configuration and swimming kinematics, body shape, and Reynolds number. The models representing eel-like fishes with elongated bodies and fishes swimming at high Reynolds numbers had more segments and less segment length variability along the body than the models representing other fishes. These fishes recruited their anterior bodies to a greater extent, initiating the undulatory wave more anteriorly. Two shape parameters, related to axial and overall body thickness, predicted segment configuration with moderate to high success rate. We found that head morphology was a goodmore »predictor of its segment length. While there was a large variation in head segments, the length of tail segments was similar across all models. Given that fishes exhibited variable caudal fin shapes, the consistency of tail segments could be a result of an evolutionary constraint tuned for high propulsive efficiency. The bio-inspired multi-segment models presented in this study highlight the key bending points along the body and can be used to decide on the placement of actuators in fish-inspired robots, to model hydrodynamic forces in theoretical and computational studies, or for predicting muscle activation patterns during swimming.

    « less
  2. Abstract

    Fishes generate force to swim by activating muscles on either side of their flexible bodies. To accelerate, they must produce higher muscle forces, which leads to higher reaction forces back on their bodies from the environment. If their bodies are too flexible, the forces during acceleration could not be transmitted effectively to the environment, but fish can potentially use their muscles to increase the effective stiffness of their body. Here, we quantified red muscle activity during acceleration and steady swimming, looking for patterns that would be consistent with the hypothesis of body stiffening. We used high-speed video, electromyographic recordings, and a new digital inertial measurement unit to quantify body kinematics, red muscle activity, and 3D orientation and centre of mass acceleration during forward accelerations and steady swimming over several speeds. During acceleration, fish co-activated anterior muscle on the left and right side, and activated all muscle sooner and kept it active for a larger fraction of the tail beat cycle. These activity patterns are both known to increase effective stiffness for muscle tissuein vitro, which is consistent with our hypothesis that fish use their red muscle to stiffen their bodies during acceleration. We suggest that during impulsive movements, flexiblemore »organisms like fishes can use their muscles not only to generate propulsive power but to tune the effective mechanical properties of their bodies, increasing performance during rapid movements and maintaining flexibility for slow, steady movements.

    « less
  3. Fish maintain high swimming efficiencies over a wide range of speeds. A key to this achievement is their flexibility, yet even flexible robotic fish trail real fish in terms of performance. Here, we explore how fish leverage tunable flexibility by using their muscles to modulate the stiffness of their tails to achieve efficient swimming. We derived a model that explains how and why tuning stiffness affects performance. We show that to maximize efficiency, muscle tension should scale with swimming speed squared, offering a simple tuning strategy for fish-like robots. Tuning stiffness can double swimming efficiency at tuna-like frequencies and speeds (0 to 6 hertz; 0 to 2 body lengths per second). Energy savings increase with frequency, suggesting that high-frequency fish-like robots have the most to gain from tuning stiffness.

  4. The anterior body of many fishes is shaped like an airfoil turned on its side. With an oscillating angle to the swimming direction, such an airfoil experiences negative pressure due to both its shape and pitching movements. This negative pressure acts as thrust forces on the anterior body. Here, we apply a high-resolution, pressure-based approach to describe how two fishes, bluegill sunfish (Lepomis macrochirusRafinesque) and brook trout (Salvelinus fontinalisMitchill), swimming in the carangiform mode, the most common fish swimming mode, generate thrust on their anterior bodies using leading-edge suction mechanics, much like an airfoil. These mechanics contrast with those previously reported in lampreys—anguilliform swimmers—which produce thrust with negative pressure but do so through undulatory mechanics. The thrust produced on the anterior bodies of these carangiform swimmers through negative pressure comprises 28% of the total thrust produced over the body and caudal fin, substantially decreasing the net drag on the anterior body. On the posterior region, subtle differences in body shape and kinematics allow trout to produce more thrust than bluegill, suggesting that they may swim more effectively. Despite the large phylogenetic distance between these species, and differences near the tail, the pressure profiles around the anterior body are similar. Wemore »suggest that such airfoil-like mechanics are highly efficient, because they require very little movement and therefore relatively little active muscular energy, and may be used by a wide range of fishes since many species have appropriately shaped bodies.

    « less
  5. Cervical disc implants are conventional surgical treatments for patients with degenerative disc disease, such as cervical myelopathy and radiculopathy. However, the surgeon still must determine the candidacy of cervical disc implants mainly from the findings of diagnostic imaging studies, which can sometimes lead to complications and implant failure. To help address these problems, a new approach was developed to enable surgeons to preview the post-operative effects of an artificial disc implant in a patient-specific fashion prior to surgery. To that end, a robotic replica of a person’s spine was 3D printed, modified to include an artificial disc implant, and outfitted with a soft magnetic sensor array. The aims of this study are threefold: first, to evaluate the potential of a soft magnetic sensor array to detect the location and amplitude of applied loads; second, to use the soft magnetic sensor array in a 3D printed human spine replica to distinguish between five different robotically actuated postures; and third, to compare the efficacy of four different machine learning algorithms to classify the loads, amplitudes, and postures obtained from the first and second aims. Benchtop experiments showed that the soft magnetic sensor array was capable of precisely detecting the location and amplitudemore »of forces, which were successfully classified by four different machine learning algorithms that were compared for their capabilities: Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest (RF), and Artificial Neural Network (ANN). In particular, the RF and ANN algorithms were able to classify locations of loads applied 3.25 mm apart with 98.39% ± 1.50% and 98.05% ± 1.56% accuracies, respectively. Furthermore, the ANN had an accuracy of 94.46% ± 2.84% to classify the location that a 10 g load was applied. The artificial disc-implanted spine replica was subjected to flexion and extension by a robotic arm. Five different postures of the spine were successfully classified with 100% ± 0.0% accuracy with the ANN using the soft magnetic sensor array. All results indicated that the magnetic sensor array has promising potential to generate data prior to invasive surgeries that could be utilized to preoperatively assess the suitability of a particular intervention for specific patients and to potentially assist the postoperative care of people with cervical disc implants.« less