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).
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