Fish-like aquatic propulsion studied using a pneumatically-actuated soft-robotic model

Fish locomotion is characterized by waves of muscle electrical activity that proceed from head to tail, and result in an undulatory pattern of body bending that generates thrust during locomotion. Isolating the effects of parameters like body stiffness, co-activation between the right and left sides of the body, and frequency on thrust generation has proven to be difficult in live fishes. We use a pneumatically-actuated fish-like model to investigate how these parameters affect locomotor force generation. We measure thrust as well as side forces and torques generated during propulsion. Using a statistical linear model we examine the effects of input parameter combinations on thrust generation. We show that both stiffness and frequency substantially affect swimming kinematics, and that there are complex interactive effects of these two parameters on thrust. The stiffer the backbone the more impact that increasing frequency has on thrust production. For stiffer models, increasing frequency resulted in higher values for both thrust and lateral forces. Large side forces reduce swimming efficiency but this effect could be mitigated by decreasing undulatory wavelength and allowing appropriate phasing of left and right body movements to reduce amplitudes of side force.

Tunas as a high-performance fish platform for inspiring the next generation of autonomous underwater vehicles

Tunas of the genus Thunnus are a group of high-performance pelagic fishes with many locomotor traits that are convergently shared with other high-performance fish groups. Because of their swimming abilities, tunas continue to be an inspiration for both comparative biomechanics and the design of biomimetic autonomous underwater vehicles (AUVs). Despite the strong history of studies in tuna physiology and current interest in tuna biomechanics and bio-inspired design, we lack quantitative data on the function of many features of tunas. Here we present data on the morphology, behavior, and function of tunas, focusing especially on experimentally examining the function of tuna lateral keels, finlets, and pectoral fins by using simple physical models. We find that both triangular lateral keels and flexible finlets decrease power requirements during swimming, likely by reducing lateral forces and yaw torques (compared to models either without keels or with rectangular keels, and models with stiff finlets or strip fins of equal area, respectively). However, both triangular keels and flexible finlets generate less thrust than other models either without these features or with modified keels or finlets, leading to a tradeoff between power consumption and thrust. In addition, we use micro computed tomography (µCT) to show that the flexible lateral keels possess a lateral line canal, suggesting these keels have a sensory function. The curved and fully-attached base of tuna pectoral fins provides high lift-to-drag ratio at low angles of attack, and generates the highest torques across speeds and angles of attack. Therefore, curved, fully-attached pectoral fins grant both better gliding and maneuvering performance compared to flat or curved, partially-attached designs. We provide both 3D models of tuna morphology derived from µCT scans and conclusions about the performance effects of tuna-like features as a resource for future biological and engineering work for next-generation tuna-inspired AUV designs.

Avoidance of non-localizable obstacles in echolocating bats: A robotic model

Most objects and vegetation making up the habitats of echolocating bats return a multitude of overlapping echoes. Recent evidence suggests that the limited temporal and spatial resolution of bio-sonar prevents bats from separately perceiving the objects giving rise to these overlapping echoes. Therefore, bats often operate under conditions where their ability to localize obstacles is severely limited. Nevertheless, bats excel at avoiding complex obstacles. In this paper, we present a robotic model of bat obstacle avoidance using interaural level differences and distance to the nearest obstacle as the minimal set of cues. In contrast to previous robotic models of bats, the current robot does not attempt to localize obstacles. We evaluate two obstacle avoidance strategies. First, the Fixed Head Strategy keeps the acoustic gaze direction aligned with the direction of flight. Second, the Delayed Linear Adaptive Law (DLAL) Strategy uses acoustic gaze scanning, as observed in hunting bats. Acoustic gaze scanning has been suggested to aid the bat in hunting for prey. Here, we evaluate its adaptive value for obstacle avoidance when obstacles can not be localized. The robot's obstacle avoidance performance is assessed in two environments mimicking (highly cluttered) experimental setups commonly used in behavioral experiments: a rectangular arena containing multiple complex cylindrical reflecting surfaces and a corridor lined with complex reflecting surfaces. The results indicate that distance to the nearest object and interaural level differences allows steering the robot clear of obstacles in environments that return non-localizable echoes. Furthermore, we found that using acoustic gaze scanning reduced performance, suggesting that gaze scanning might not be beneficial under conditions where the animal has limited access to angular information, which is in line with behavioral evidence.

Hybrid Inspired Research on the Flying-Jumping Locomotion of Locusts Using Robot Counterpart

Locusts are a kind of agile insects that can move and maneuver so efficiently in the unstructured terrain and complex environment. This marvel survivability of locusts benefits from their flying-jumping multi-modal locomotion. But until recently, the main influences of the locomotion performance are still a controversial and unknown issue. In this paper, the idea of hybrid inspired method that combines biologically inspired robot with robot inspired biology was proposed to explore the principle of flying-jumping locomotion of locusts. Firstly, we analyzed the influence of leg burrs and flapping wings on the jumping performance by the biological experiments. Nevertheless, individual heterogeneity and uncontrollability of locusts result in the unconvincing results of biological experiments. Therefore, according to the thought of robotics-inspired biology, we proposed and built a locust-inspired robot with flying-jumping locomotion via the principle of metamorphic mechanism based on the biological-inspired robot. Lastly, the preliminary robotic experiments were carried out to validate our thought that the flapping wings and leg burrs of locust have a great influence on the jumping performance. This robotics-inspired biology method remedied the shortcomings of biological experiments through the consistency and controllability of the robot experiments. Meanwhile, through the hybrid inspired research, the results show both the leg burrs and flapping wings can help the locust jump longer and improve the stability by adjusting the landing attitude to some extent, while the biological experiments dedicate that the locust with leg burrs and wings have the self-stability ability.

Tuna robotics: A high-frequency experimental platform exploring the performance space of swimming fishes

Tuna and related scombrid fishes are high-performance swimmers that often operate at high frequencies, especially during behaviors such as escaping from predators or catching prey. This contrasts with most fish-like robotic systems that typically operate at low frequencies (< 2 hertz). To explore the high-frequency fish swimming performance space, we designed and tested a new platform based on yellowfin tuna (Thunnus albacares) and Atlantic mackerel (Scomber scombrus). Body kinematics, speed, and power were measured at increasing tail beat frequencies to quantify swimming performance and to study flow fields generated by the tail. Experimental analyses of freely swimming tuna and mackerel allow comparison with the tuna-like robotic system. The Tunabot (255 millimeters long) can achieve a maximum tail beat frequency of 15 hertz, which corresponds to a swimming speed of 4.0 body lengths per second. Comparison of midline kinematics between scombrid fish and the Tunabot shows good agreement over a wide range of frequencies, with the biggest discrepancy occurring at the caudal fin, primarily due to the rigid propulsor used in the robotic model. As frequency increases, cost of transport (COT) follows a fish-like U-shaped response with a minimum at ~1.6 body lengths per second. The Tunabot has a range of ~9.1 kilometers if it swims at 0.4 meter per second or ~4.2 kilometers at 1.0 meter per second, assuming a 10-watt-hour battery pack. These results highlight the capabilities of high-frequency biological swimming and lay the foundation to explore a fish-like performance space for bio-inspired underwater vehicles.

Multi-functional soft-bodied jellyfish-like swimming

The functionalities of the untethered miniature swimming robots significantly decrease as the robot size becomes smaller, due to limitations of feasible miniaturized on-board components. Here we propose an untethered jellyfish-inspired soft millirobot that could realize multiple functionalities in moderate Reynolds number by producing diverse controlled fluidic flows around its body using its magnetic composite elastomer lappets, which are actuated by an external oscillating magnetic field. We particularly investigate the interaction between the robot's soft body and incurred fluidic flows due to the robot's body motion, and utilize such physical interaction to achieve different predation-inspired object manipulation tasks. The proposed lappet kinematics can inspire other existing jellyfish-like robots to achieve similar functionalities at the same length and time scale. Moreover, the robotic platform could be used to study the impacts of the morphology and kinematics changing in ephyra jellyfish.

Exploring Behaviors of Caterpillar-Like Soft Robots with a Central Pattern Generator-Based Controller and Reinforcement Learning

Due to their flexibility, soft-bodied robots can potentially achieve rich and various behaviors within a single body. However, to date, no methodology has effectively harnessed these robots to achieve such diverse desired functionalities. Controllers that accomplish only a limited range of behaviors in such robots have been handcrafted. Moreover, the behaviors of these robots should be determined through body–environment interactions because an appropriate behavior may not always be manifested even if the body dynamics are given. Therefore, we have proposed SenseCPG-PGPE, a method for automatically designing behaviors for caterpillar-like soft-bodied robots. This method optimizes mechanosensory feedback to a central pattern generator (CPG)-based controller, which controls actuators in a robot, using policy gradients with parameter-based exploration (PGPE). In this article, we deeply investigated this method. We found that PGPE can optimize a CPG-based controller for soft-bodied robots that exhibit viscoelasticity and large deformation, whereas other popular policy gradient methods, such as trust region policy optimization and proximal policy optimization, cannot. Scalability of the method was confirmed using simulation as well. Although SenseCPG-PGPE uses a CPG-based controller, it can achieve nonsteady motion such as climbing a step in a simulated robot. The approach also resulted in distinctive behaviors depending on different body–environment conditions. These results demonstrate that the proposed method enables soft robots to explore a variety of behaviors automatically.

Body-limb coordination mechanism underlying speed-dependent gait transitions in sea roaches

The sea roach is an isopod with 14 legs; owing to its many degrees of freedom and coordination thereof, it can walk rapidly on rough terrain. Although there likely exists a remarkable decentralized control mechanism that facilitates fast and adaptive locomotion of sea roaches, it still remains elusive. To address this issue, we performed behavioural experiments and revealed that sea roaches often change their gait patterns depending on the locomotion speed. We suggest that the bending of the body trunk in the pitch direction is essential for the gait transitions, and we propose a decentralized control mechanism for body-limb coordination. We demonstrate this with a sea-roach-like robot whose gait transition is achieved by the proposed mechanism. This mechanism has some points in common with control mechanisms proposed for other legged animals. Thus, our findings will help unveil the common principle of legged locomotion and aid the design of multi-legged robots that move like animals.