The restoration of coral reef population in coastal regions is currently a growing concern. Many attempts have been made to apply new approaches to limit the deterioration of coral reefs, and to accelerate the growth of new reefs to protect coastal areas and ecosystems using available renewable energy sources. This paper highlights the new approaches and their various advantages and limitations in tidal and wave energy. The paper also suggests improvements to some of those systems using the recent developments in soft robotics, especially the use of biomimetic fish as a feasible support platform for the monitoring and maintenance of the power generation and potential restoration systems. © 2023 IEEE.
A Unified FPGA Realization for Fractional-Order Integrator and Differentiator
This paper proposes a generic FPGA realization of an IP core for fractional-order integration and differentiation based on the Grünwald–Letnikov approximation. All fractional-order dependent terms are approximated to simpler relations using curve fitting to enable an efficient hardware realization. Compared to previous works, the proposed design introduces enhancements in the fractional-order range covering both integration and differentiation. An error analysis between software and hardware results is presented for sine, triangle and sawtooth signals. The proposed generic design is realized on XC7A100T FPGA achieving frequency of 9.328 MHz and validated experimentally for a sine input signal on the oscilloscope. The proposed unified generic design is suitable for biomedical signal processing applications. In addition, it can be employed as a laboratory tool for fractional calculus education. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Plant stem tissue modeling and parameter identification using metaheuristic optimization algorithms
Bio-impedance non-invasive measurement techniques usage is rapidly increasing in the agriculture industry. These measured impedance variations reflect tacit biochemical and biophysical changes of living and non-living tissues. Bio-impedance circuit modeling is an effective solution used in biology and medicine to fit the measured impedance. This paper proposes two new fractional-order bio-impedance plant stem models. These new models are compared with three commonly used bio-impedance fractional-order circuit models in plant modeling (Cole, Double Cole, and Fractional-order Double-shell). The two proposed models represent the characterization of the biological cellular morphology of the plant stem. Experiments are conducted on two samples of three different medical plant species from the family Lamiaceae, and each sample is measured at two inter-electrode spacing distances. Bio-impedance measurements are done using an electrochemical station (SP150) in the range of 100 Hz to 100 kHz. All employed models are compared by fitting the measured data to verify the efficiency of the proposed models in modeling the plant stem tissue. The proposed models give the best results in all inter-electrode spacing distances. Four different metaheuristic optimization algorithms are used in the fitting process to extract all models parameter and find the best optimization algorithm in the bio-impedance problems. © 2022, The Author(s).
Design and control of soft biomimetic pangasius fish robot using fin ray effect and reinforcement learning
Soft robots provide a pathway to accurately mimic biological creatures and be integrated into their environment with minimal invasion or disruption to their ecosystem. These robots made from soft deforming materials possess structural properties and behaviors similar to the bodies and organs of living creatures. However, they are difficult to develop in terms of integrated actuation and sensing, accurate modeling, and precise control. This article presents a soft-rigid hybrid robotic fish inspired by the Pangasius fish. The robot employs a flexible fin ray tail structure driven by a servo motor, to act as the soft body of the robot and provide the undulatory motion to the caudal fin of the fish. To address the modeling and control challenges, reinforcement learning (RL) is proposed as a model-free control strategy for the robot fish to swim and reach a specified target goal. By training and investigating the RL through experiments on real hardware, we illustrate the capability of the fish to learn and achieve the required task. © 2022, The Author(s).
Underwater Soft Robotics: A Review of Bioinspiration in Design, Actuation, Modeling, and Control
Nature and biological creatures are some of the main sources of inspiration for humans. Engineers have aspired to emulate these natural systems. As rigid systems become increasingly limited in their capabilities to perform complex tasks and adapt to their environment like living creatures, the need for soft systems has become more prominent due to the similar complex, compliant, and flexible characteristics they share with intelligent natural systems. This review provides an overview of the recent developments in the soft robotics field, with a focus on the underwater application frontier. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Modeling of Soft Pneumatic Actuators with Different Orientation Angles Using Echo State Networks for Irregular Time Series Data
Modeling of soft robotics systems proves to be an extremely difficult task, due to the large deformation of the soft materials used to make such robots. Reliable and accurate models are necessary for the control task of these soft robots. In this paper, a data-driven approach using machine learning is presented to model the kinematics of Soft Pneumatic Actuators (SPAs). An Echo State Network (ESN) architecture is used to predict the SPA’s tip position in 3 axes. Initially, data from actual 3D printed SPAs is obtained to build a training dataset for the network. Irregularintervals pressure inputs are used to drive the SPA in different actuation sequences. The network is then iteratively trained and optimized. The demonstrated method is shown to successfully model the complex non-linear behavior of the SPA, using only the control input without any feedback sensory data as additional input to the network. In addition, the ability of the network to estimate the kinematics of SPAs with different orientation angles ? is achieved. The ESN is compared to a Long Short-Term Memory (LSTM) network that is trained on the interpolated experimental data. Both networks are then tested on Finite Element Analysis (FEA) data for other ? angle SPAs not included in the training data. This methodology could offer a general approach to modeling SPAs with varying design parameters. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Soft robotic grippers: A review on technologies, materials, and applications
The growing need for manipulators capable of handling delicate objects with care and coexisting safely with humans has brought soft robots to the forefront as a practical and cost-effective solution. In this context, this paper aims to explore soft grippers, a unique and versatile subset of soft robots. It provides an overview of various soft grasping techniques and materials, highlighting their respective advantages and limitations, along with showcasing several designed and tested models. As medicine and agriculture are acknowledged as pivotal domains required for basic human survival, this paper explores the potential applications of soft robotic grippers in these respective fields. Additionally, it further investigates how soft grippers can contribute to reducing cost and enhancing production efficiency while addressing practical relevant solutions. Considering the escalating environmental threats, particularly in oceans and coral reefs, the paper examines the potential of soft grasping underwater to mitigate these challenges, considered as crucial for conserving the fisheries industry and pertinent economic fields. Lastly, it outlines the current challenges and future prospects of soft grippers, emphasizing the importance of overcoming obstacles through finding solutions such as using bioinspiration to create effective technical solutions and highlighting the importance of commercialization. © 2024 Elsevier B.V.