Learning Soft Robot and Soft Actuator Dynamics using Deep Neural Network

Authors

  • Hari Prakash Thanabalan School of Engineering and Material Science, Queen Mary University of London

Abstract

Inspired by living organisms and being the forefront of robotics evolution, the research in soft robotics has been growing exponentially. Due to the flexibility of these robots that is made from soft materials such as silicone or even a fabric allows them to manoeuvre on secluded environments through crevice openings which bring many advantages comparing to the rigid-component robots which proves much more delicate interaction with humans and environments. In this paper, modelling of the soft robot using finite element modelling will be discussed in conjunction with deep neural network for the bending and control of the end effector.

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Published

2021-06-12

How to Cite

Thanabalan, H. P. (2021). Learning Soft Robot and Soft Actuator Dynamics using Deep Neural Network. International Journal of Electrical Engineering and Applied Sciences (IJEEAS), 4(1). Retrieved from https://ijeeas.utem.edu.my/ijeeas/article/view/6060

Issue

Section

Mechatronics and Intelligent Robotics