The Structure, Design, and Closed-Loop Motion Control of a Differential Drive Soft Robot

被引:50
作者
Pang Wu [1 ]
Wang Jiangbei [1 ]
Fei Yanqiong [1 ]
机构
[1] Shanghai Jiao Tong Univ, Inst Robot, Dongchuan Rd 800, Shanghai 200240, Peoples R China
基金
中国国家自然科学基金;
关键词
soft robot; differential movement; RBF neural networks; automatic control; NETWORKS;
D O I
10.1089/soro.2017.0042
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
This article presents the structure, design, and motion control of an inchworm inspired pneumatic soft robot, which can perform differential movement. This robot mainly consists of two columns of pneumatic multi-airbags (actuators), one sensor, one baseboard, front feet, and rear feet. According to the different inflation time of left and right actuators, the robot can perform both linear and turning movements. The actuators of this robot are composed of multiple airbags, and the design of the airbags is analyzed. To deal with the nonlinear performance of the soft robot, we use radial basis function neural networks to train the turning ability of this robot on three different surfaces and create a mathematical model among coefficient of friction, deflection angle, and inflation time. Then, we establish the closed-loop automatic control model using three-axis electronic compass sensor. Finally, the automatic control model is verified by linear and turning movement experiments. According to the experiment, the robot can finish the linear and turning movements under the closed-loop control system.
引用
收藏
页码:71 / 80
页数:10
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