Finite Rigid Elements Based Modelling of a Soft Bending Actuator Considering Hysteresis Effect

• Published in: Digest book (International Conference on Robotics and Mechatronics. Online) pp. 368 - 375
• Main Authors: Sharifian, Atena, Najafian, Sina, Soleimanzadeh, Mohammadali, Ghafarirad, Hamed
• Format: Conference Proceeding
• Language: English
• Published: IEEE 17.12.2024
• Subjects: Accuracy; Actuators; Bending; Computational modeling; dynamic modelling; Finite element analysis; Finite rigid element method; Hysteresis; Robots; Safety; Service robots; soft bending actuator; soft robot; Soft robotics
• ISSN: 2572-6889
• DOI: 10.1109/ICRoM64545.2024.10903632

Traditional robotic systems, characterized by rigid link structures, are inherently limited to a narrow range of applications due to their inflexibility and associated safety risks in human-robot interactions. In contrast, soft actuators offer a viable alternative, providing enhanced safety, flexibility, and adaptability. These actuators exhibit virtually unlimited degrees of freedom, enabling a broad spectrum of functionalities. The integration of soft actuators into various devices has seen significant advancements, particularly in the fields of rehabilitation, prosthetic limbs, robotic arms, and robotic gripper systems. This paper explores the development and application of soft actuators, emphasizing their transformative potential in both industrial and biomedical contexts. Soft actuators exhibit complex, nonlinear behaviors, including hysteresis, due to the intrinsic properties of their constituent materials, posing significant modeling challenges. Recent studies have focused extensively on modeling these actuators. This research investigates the static and dynamic modeling of a fabricated soft bending actuator, incorporating the hysteresis effect. The model is developed using the Finite Rigid Elements method and the conventional Denavit-Hartenberg approach. Advantages of the Finite Rigid Elements method include ease of implementation due to its logical and intuitive structure, high accuracy in modeling and analyzing system behaviors, and low computational cost, making it efficient. The results are then validated through experimental comparisons, highlighting the model's accuracy in representing the actuator's behavior.