An Optimum Design Method of Pneu-Net Actuators for Trajectory Matching Utilizing a Bending Model and GA

Yilin Sun, Qiuju Zhang, Xiaoyan Chen and Haiwei Chen

Mathematical Problems in Engineering, 2019, vol. 2019, 1-12

Abstract:

This study addresses the problem in designing pneu-net actuators to achieve specific target trajectories for particular applications. The finite element analysis (FEA) method is used to study the sensitivity of 9 design parameters to bending deformation of actuators, and the results of FEA demonstrate that the width of the chamber and the width of the middle layer have great influence on the bending performance. Besides, the relations between the bending angles of actuators with different width parameters and the pressure are always highly linear. Using FEA and the cubic polynomial fitting algorithm, a unified bending model of the pneu-net actuator is established with three crucial design parameters (i.e., segment length, chamber width, and middle-layer width). An optimum design method based on the bending model and genetic algorithm (GA) is put forward to automatically adjust these three crucial parameters to realise trajectory matching. The method is developed to be an effective solution for the problem in matching the target trajectory with the experimental results achieved on an actuator designed by imitating a human index finger. Furthermore, the results of the experiment also verify that the actuator can achieve stable grasping, and the proposed method has an important directive to design pneu-net actuators for their application in the fields of robotics, rescue, and detection.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6721897

DOI: 10.1155/2019/6721897

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