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.
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).
Theoretical and experimental investigation study of data driven work envelope modelling for 3D printed soft pneumatic actuators
In the last decade, soft robotics is considered one of the most widely researched fields in robotics, as it has many advantages and more versatile use than rigid robotics
Design and implementation of variable inclined air pillow soft pneumatic actuator suitable for bioimpedance applications
The technological revolution has caused the modernization of human–machine relationship changing our approach in problem solving our society issues and deviated the science of robotic all together
Tactile sensing biohybrid soft E-skin based on bioimpedance using aloe vera pulp tissues
Soft and flexible E-skin advances are a subset of soft robotics field where the soft morphology of human skin is mimicked
Modelling and implementation of soft bio-mimetic turtle using echo state network and soft pneumatic actuators
Advances of soft robotics enabled better mimicking of biological creatures and closer realization of animalsÂ’ motion in the robotics field
Biohybrid soft robots, E-skin, and bioimpedance potential to build up their applications: A review
Soft Robotics is a new approach towards better human-robot interaction and biomimicry in the robotics field