Mechatronic design and locomotion control of a robotic thunniform swimmer for fast cruising

Control of movement of underwater swimmers: Animals, simulated animates and swimming robots

The control of movement in living organisms represents a fundamental task that the brain has evolved to solve. One crucial aspect is how the nervous system organizes the transformation of sensory information into motor commands. These commands lead to muscle activation and subsequent animal movement, which can exhibit complex patterns. One example of such movement is locomotion, which involves the translation of the entire body through space. Central Pattern Generators (CPGs) are neuronal circuits that provide control signals for these movements. Compared to the intricate circuits found in the brain, CPGs can be simplified into networks of neurons that generate rhythmic activation, coordinating muscle movements. Since the 1990s, researchers have developed numerous models of locomotive circuits to simulate different types of animal movement, including walking, flying, and swimming. Initially, the primary goal of these studies was to construct biomimetic robots. However, it became apparent that simplified CPGs alone were not sufficient to replicate the diverse range of adaptive locomotive movements observed in living organisms. Factors such as sensory modulation, higher-level control, and cognitive components related to learning and memory needed to be considered. This necessitated the use of more complex, high-dimensional circuits, as well as novel materials and hardware, in both modeling and robotics. With advancements in high-power computing, artificial intelligence, big data processing, smart materials, and electronics, the possibility of designing a new generation of true bio-mimetic robots has emerged. These robots have the capability to imitate not only simple locomotion but also exhibit adaptive motor behavior and decision-making. This motivation serves as the foundation for the current review, which aims to analyze existing concepts and models of movement control systems. As an illustrative example, we focus on underwater movement and explore the fundamental biological concepts, as well as the mathematical and physical models that underlie locomotion and its various modulations.

A Comparative and Collaborative Study of the Hydrodynamics of Two Swimming Modes Applicable to Dolphins

This paper presents a hydrodynamics study that examines the comparison and collaboration of two swimming modes relevant to the universality of dolphins. This study utilizes a three-dimensional virtual swimmer model resembling a dolphin, which comprises a body and/or caudal fin (BCF) module, as well as a medium and/or paired fin (MPF) module, each equipped with predetermined kinematics. The manipulation of the dolphin to simulate various swimming modes is achieved through the application of overlapping grids in conjunction with the parallel hole cutting technique. The findings demonstrate that the swimming velocity and thrust attained through the single BCF mode consistently surpass those achieved through the single MPF mode and collaborative mode. Interestingly, the involvement of the MPF mode does not necessarily contribute to performance enhancement. Nevertheless, it is encouraging to note that adjusting the phase difference between the two modes can partially mitigate the limitations associated with the MPF mode. To further investigate the potential advantages of dual-mode collaboration, we conducted experiments by increasing the MPF frequency while keeping the BCF frequency constant, thus introducing the concept of frequency ratio (β). In comparison to the single BCF mode, the collaborative mode with a high β exhibits superior swimming velocity and thrust. Although its efficiency experiences a slight decrease, it tends to stabilize. The corresponding flow structure indirectly verifies the favorable impact of collaboration.

Multi-objective evolutionary design of central pattern generator network for biomimetic robotic fish

Fish-inspired motion is an important research area with many applications in real-world tasks such as underwater vehicles or robotic fish control design. Owing to robust, smooth, and coordinated oscillatory signals generated by Central Pattern Generators (CPGs) for locomotion control of robots with multiple degrees of freedom, CPGs are the most versatile solution for robotic control systems, especially in robotic fish. However, tuning central pattern generator parameters is difficult for complex mechanical system designs. Besides, most current CPG-based methods only consider one aspect (e.g., speed), which widens the gap between theory and practice in robotic fish design. Also, it may affect the practical applicability of the designed motion model to a certain extent. This paper addresses this problem by constructing a multi-objective evolutionary design of a central pattern generator network to control the proposed biomimetic robotic fish. A new CPG model is proposed to help biomimetic robotic fish swim efficiently. In addition, an efficient multi-objective evolutionary algorithm proposed in our previous work is also applied to assist the biomimetic robotic fish in obtaining faster-swimming speed, good stability of the head, and higher propulsive efficiency simultaneously. Considering that the result of multi-objective optimization is a set of non-dominated solutions rather than a solution, a screening method based on fuzzy theory is adopted to assist decision-makers in selecting the most appropriate solution. Based on this, the control model of biomimetic robotic fish is constructed. The proposed control model is simulated and compared with seven well-known algorithms and a series of robotic fish designs. After that, the proposed control model is validated with extensive experiments on the actual biomimetic robotic fish. Simulations and experiments demonstrate the proposed control model’s effectiveness and good performance, especially when the control model has been applied to the real biomimetic robotic fish.

Utilization of Function Generation Synthesis on Biomimetics: A Case Study on Moray Eel Double Jaw Design

Throughout history, humans have observed living or non-living things in nature and then imitated them in relation to these observations. This is due to the fact that the energy found in nature is generally consumed at an optimal level in order for it to endure. Biomimetic inspiration in many designs and applications is widely displayed, including within the field of engineering. In this paper, we were inspired by the double set of jaws found in the moray eel, which gives this fish a huge advantage while hunting, with a mobile pharyngeal jaw that works together with its oral jaw in order to overcome ineffective suction capabilities. A procedure that mimics the hunting motion of the moray eel was utilized by considering the overall movement as a single degree of freedom with multiple outputs on account of the repeating motion that is required during hunting. This procedure includes structural and dimensioning synthesis, wherein the latter was utilized with analytic kinematic synthesis for each linkage transfer. The flexibilities in parameters were taken into account with a novel multiple iterative kinematic synthesis algorithm that resulted in various mechanisms with the same purpose. Among the excessive number of resultant mechanisms, the optimization was carried out by considering the highest torque transmission ratio at critical timings that were specified as bio-constraints. In the end, the kinematic movement validation was utilized.

A comprehensive review on fish-inspired robots

Recently, the increasing interest in underwater exploration motivates the development of aquatic unmanned vehicles. To execute hazardous tasks in an unknown or even hostile environment, researchers have directed on developing biomimetic robots inspired by the extraordinary maneuverability, cruising speed, and propulsion efficiency of fish. Nevertheless, the performance of current prototypes still has gaps compared with that of real fishes. In this review, recent approaches in structure designs, actuators, and sensors are presented. In addition, the theoretical methods for modeling the robotic fishes are consolidated, and the control strategies are offered. Finally, the current challenges are summarized, and possible future directions are deeply discussed. It is expected that the emergence of new engineering and biological technologies will enhance the field of robotic fish for further advancement.

Design and development of autonomous robotic fish for object detection and tracking

In this article, an autonomous robotic fish is designed for underwater operations like object detection and tracking along with collision avoidance. The computer-aided design model for prototype robotic fish is designed using the Solid Works® software to export an stereolithography (STL) file to MakerBot, a 3D printer, to manufacture the parts of robotic fish using polylactic acid thermoplastic polymer. The precise maneuverability of the robotic fish is achieved by the propulsion of a caudal fin. The oscillation of the caudal fin is controlled by a servomotor. A combination of visual and ultrasonic sensors is used to track the position and distance of the desired object with respect to the fish and also to avoid the obstacles. The robotic fish has the ability to detect an object up to a distance of 90 cm at normal exposure conditions. A computational fluid dynamics analysis is conducted to analyze the fluid hydrodynamics (flow rate of water and pressure) around the hull of a robotic fish and the drag force acting on it. A series of experimental results have shown the effectiveness of the designed underwater robotic fish.

Mechatronic Design and Manufacturing of the Intelligent Robotic Fish for Bio-Inspired Swimming Modes

This paper presents mechatronic design and manufacturing of a biomimetic Carangiform-type autonomous robotic fish prototype (i-RoF) with two-link propulsive tail mechanism. For the design procedure, a multi-link biomimetic approach, which uses the physical characteristics of a real carp fish as its size and structure, is adapted. Appropriate body rate is determined according to swimming modes and tail oscillations of the carp. The prototype is composed of three main parts: an anterior rigid body, two-link propulsive tail mechanism, and flexible caudal fin. Prototype parts are produced with 3D-printing technology. In order to mimic fish-like robust swimming gaits, a biomimetic locomotion control structure based on Central Pattern Generator (CPG) is proposed. The designed unidirectional chained CPG network is inspired by the neural spinal cord of Lamprey, and it generates stable rhythmic oscillatory patterns. Also, a Center of Gravity (CoG) control mechanism is designed and located in the anterior rigid body to ensure three-dimensional swimming ability. With the help of this design, the characteristics of the robotic fish are performed with forward, turning, up-down and autonomous swimming motions in the experimental pool. Maximum forward speed of the robotic fish can reach 0.8516 BLs-1 and excellent three-dimensional swimming performance is obtained.