Fish-inspired segment models for undulatory steady swimming

Form and function of anguilliform swimming

Anguilliform swimmers are long and narrow animals that propel themselves by undulating their bodies. Observations in nature and recent investigations suggest that anguilliform swimming is highly efficient. However, understanding the underlying reasons for the efficiency of this type of locomotion requires interdisciplinary studies spanning from biology to hydrodynamics. Regrettably, these different fields are rarely discussed together, which hinders our ability to understand the repeated evolution of this swimming mode in vertebrates. This review compiles the current knowledge of the anatomical features that drive anguilliform swimming, compares the resulting kinematics across a wide range of anguilliform swimmers, and describes the resulting hydrodynamic interactions using data from both in vivo experiments and computational studies.

Bioinspiration and biomimetics in marine robotics: a review on current applications and future trends

Over the past few years, the research community has witnessed a burgeoning interest in biomimetics, particularly within the marine sector. The study of biomimicry as a revolutionary remedy for numerous commercial and research-based marine businesses has been spurred by the difficulties presented by the harsh maritime environment. Biomimetic marine robots are at the forefront of this innovation by imitating various structures and behaviors of marine life and utilizing the evolutionary advantages and adaptations these marine organisms have developed over millennia to thrive in harsh conditions. This thorough examination explores current developments and research efforts in biomimetic marine robots based on their propulsion mechanisms. By examining these biomimetic designs, the review aims to solve the mysteries buried in the natural world and provide vital information for marine improvements. In addition to illuminating the complexities of these bio-inspired mechanisms, the investigation helps to steer future research directions and possible obstacles, spurring additional advancements in the field of biomimetic marine robotics. Considering the revolutionary potential of using nature's inventiveness to navigate and thrive in one of the most challenging environments on Earth, the current review's conclusion urges a multidisciplinary approach by integrating robotics and biology. The field of biomimetic marine robotics not only represents a paradigm shift in our relationship with the oceans, but it also opens previously unimaginable possibilities for sustainable exploration and use of marine resources by understanding and imitating nature's solutions.

Review of Computational Fluid Dynamics Analysis in Biomimetic Applications for Underwater Vehicles

Biomimetics, which draws inspiration from nature, has emerged as a key approach in the development of underwater vehicles. The integration of this approach with computational fluid dynamics (CFD) has further propelled research in this field. CFD, as an effective tool for dynamic analysis, contributes significantly to understanding and resolving complex fluid dynamic problems in underwater vehicles. Biomimetics seeks to harness innovative inspiration from the biological world. Through the imitation of the structure, behavior, and functions of organisms, biomimetics enables the creation of efficient and unique designs. These designs are aimed at enhancing the speed, reliability, and maneuverability of underwater vehicles, as well as reducing drag and noise. CFD technology, which is capable of precisely predicting and simulating fluid flow behaviors, plays a crucial role in optimizing the structural design of underwater vehicles, thereby significantly enhancing their hydrodynamic and kinematic performances. Combining biomimetics and CFD technology introduces a novel approach to underwater vehicle design and unveils broad prospects for research in natural science and engineering applications. Consequently, this paper aims to review the application of CFD technology in the biomimicry of underwater vehicles, with a primary focus on biomimetic propulsion, biomimetic drag reduction, and biomimetic noise reduction. Additionally, it explores the challenges faced in this field and anticipates future advancements.

Robot Programming from Fish Demonstrations

Fish are capable of learning complex relations found in their surroundings, and harnessing their knowledge may help to improve the autonomy and adaptability of robots. Here, we propose a novel learning from demonstration framework to generate fish-inspired robot control programs with as little human intervention as possible. The framework consists of six core modules: (1) task demonstration, (2) fish tracking, (3) analysis of fish trajectories, (4) acquisition of robot training data, (5) generating a perception-action controller, and (6) performance evaluation. We first describe these modules and highlight the key challenges pertaining to each one. We then present an artificial neural network for automatic fish tracking. The network detected fish successfully in 85% of the frames, and in these frames, its average pose estimation error was less than 0.04 body lengths. We finally demonstrate how the framework works through a case study focusing on a cue-based navigation task. Two low-level perception-action controllers were generated through the framework. Their performance was measured using two-dimensional particle simulations and compared against two benchmark controllers, which were programmed manually by a researcher. The fish-inspired controllers had excellent performance when the robot was started from the initial conditions used in fish demonstrations (>96% success rate), outperforming the benchmark controllers by at least 3%. One of them also had an excellent generalisation performance when the robot was started from random initial conditions covering a wider range of starting positions and heading angles (>98% success rate), again outperforming the benchmark controllers by 12%. The positive results highlight the utility of the framework as a research tool to form biological hypotheses on how fish navigate in complex environments and design better robot controllers on the basis of biological findings.

Electronic thygmonasty model inMimosa pudicabiomimetic robot

Direct contact of random objects from the open environment to the panel surface of an electronic device may reduce the work efficiency and cause permanent damage. However, there is a possible way to solve this problem, notably by implementing an adaptive structure design inspired by plants. TheMimosa pudicaplant provides several interesting information on its adaptability. Various studies have been conducted on the electrical properties of its organs explaining the phytoactuator and phytosensor cells that function within it. We combined the use of sensors, actuators, and synthetic excitable tissue as the first robot model purposed to mimic the behavior of theM. pudicaplant. The Computer vision method was used to measure leaf angular movement and collected it as plant behavior data based on the mechanical stimulus experiment. The Robot structure has eight arms equipped with sensors, servo motors, and microcontrollers that are operated with two activation system models approach. The first model could imitate the stimulus process received by electronic circuits that generate action potential signals with a maximum voltage of 4.71-5.02 V and a minimum voltage of -5.33 to -3.45 V that propagated from node to node. The second model involves a trained artificial neural network model with a supervised learning pattern that provides 100% accuracy when choosing movement output based on the given combination. This robot imitates theM. pudica's intelligent sensing capabilities and its ability to change the structure shape based on the thygmonasty experiments data which could provide an overview of how plants process information and perform hazard avoidance actions efficiently. Future applications for the technology inspired by the plant's self-defense mechanisms are adaptive intelligent structures that can protect against harmful conditions, particle contamination, and adjusting panel structure to search for desired environmental parameters.

EcoPhysioMechanics: Integrating energetics and biomechanics to understand fish locomotion under climate change

Ecological physiologists and biomechanists have been broadly investigating swimming performance in a diversity of fishes, however the connection between form, function and energetics of locomotion has been rarely evaluated in the same system and under climate change scenarios. In this perspective I argue that working within the framework of 'EcoPhysioMechanics', i.e., integrating energetics and biomechanics tools, to measure locomotor performance and behavior under different abiotic factors, improves our understanding of the mechanisms, limits and costs of movement. To demonstrate how ecophysiomechanics can be applied to locomotor studies, I outline how linking biomechanics and physiology allows us to understand how fishes may modulate their movement to achieve high speeds or reduce the costs of locomotion. I also discuss how the framework is necessary to quantify swimming capacity under climate change scenarios. Finally, I discuss current dearth of integrative studies and gaps in empirical datasets that are necessary to understand fish swimming under changing environments.