Novel design and position control strategy of a soft robot arm

Al-Ibadi, A; Nefti-Meziani, S; Davis, ST; Theodoridis, T

Abstract

This article presents a novel design of a continuum arm, which has the ability to extend and bend efficiently. Numerous designs and experiments have been done to different dimensions on both types of McKibben pneumatic muscle actuators (PMA) in order to study their performances. The contraction and extension behaviour have been illustrated with single contractor actuators and single extensor actuators, respectively. The tensile force for the contractor actuator and the compressive force for the extensor PMA are thoroughly explained and compared. Furthermore, the bending behaviour has been explained for a single extensor PMA, multi extensor actuators and multi contractor actuators. A two-section continuum arm has been implemented from both types of actuators to achieve multiple operations. Then, a novel construction is proposed to achieve efficient bending behaviour of a single contraction PMA. This novel design of a bending-actuator has been used to modify the presented continuum arm. Two different position control strategies are presented, arising from the results of the modified soft robot arm experiment. A cascaded position control is applied to control the position of the end effector of the soft arm at no load by efficiently controlling the pressure of all the actuators in the continuum arm. A new algorithm is then proposed by distributing the x, y and z-axis to the actuators and applying an effective closed-loop position control to the proposed arm at different load conditions.

Citation

Al-Ibadi, A., Nefti-Meziani, S., Davis, S., & Theodoridis, T. (2018). Novel design and position control strategy of a soft robot arm. Robotics, 7(4), https://doi.org/10.3390/robotics7040072

• Journal Article Type: Article
• Acceptance Date: Nov 10, 2018
• Online Publication Date: Nov 13, 2018
• Publication Date: Nov 13, 2018
• Deposit Date: Nov 13, 2018
• Publicly Available Date: Dec 13, 2018
• Journal: Robotics
• Publisher: MDPI
• Volume: 7
• Issue: 4
• DOI: https://doi.org/10.3390/robotics7040072
• Publisher URL: https://doi.org/10.3390/robotics7040072
• Related Public URLs: https://www.mdpi.com/journal/robotics