Dynamic response prediction of hydraulic soft robotic arms based on LSTM neural network

被引:2
作者
Xie, Qing [1 ]
Zhang, Yunce [1 ]
Wang, Tao [1 ,2 ,3 ,5 ]
Zhu, Shiqiang [1 ,4 ]
机构
[1] Zhejiang Univ, Ocean Coll, Zhoushan, Peoples R China
[2] Minist Educ, Engn Res Ctr Ocean Sensing Technol & Equipment, Zhoushan, Peoples R China
[3] Zhejiang Univ, State Key Lab Fluid Power & Mechatron Syst, Hangzhou, Peoples R China
[4] Zhejiang Lab, Hangzhou, Peoples R China
[5] Zhejiang Univ, Ocean Coll, Zhoushan 316000, Peoples R China
基金
中国国家自然科学基金;
关键词
Soft robotic arm; dynamic response prediction; neural network; long short-term memory; hydraulic power; MODEL; ACTUATORS; SYSTEM;
D O I
10.1177/09596518231153446
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Hydraulic soft robotic arms possess advantages of high flexibility and good adaptability by simulating biological organs, such as elephant trunks and octopus tentacles, and therefore have broad application prospects in unstructured environments. However, the dynamic models established by physical mechanism have some problems, such as lack of accuracy and poor real-time performance due to complex nonlinear relationships between hydraulic pressures and arm deformations. This article investigated the dynamic analysis and response prediction of a double-section hydraulic soft arm based on long short-term memory neural network. The real-time tip coordinates of the hydraulic soft arm were collected under randomly generated pressure excitations. The long short-term memory neural network was built by taking the hydraulic pressures as inputs and the tip coordinates as outputs. The experimental data were divided into training set, validation set, and test set, where the training set was used to learn the parameters of the long short-term memory network, the validation set was used to optimize the hyperparameters, and the test set was used to evaluate the performance. The results showed that the dynamic model based on the long short-term memory neural network could predict the dynamic response of the hydraulic soft arm under given inputs efficiently and accurately. This data-driven model provides a candidate for the application of dynamic response prediction and motion control of the hydraulic soft arm.
引用
收藏
页码:1251 / 1265
页数:15
相关论文
共 39 条
  • [1] A Review on IPMC Material as Actuators and Sensors: Fabrications, Characteristics and Applications
    Bhandari, Binayak
    Lee, Gil-Yong
    Ahn, Sung-Hoon
    [J]. INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, 2012, 13 (01) : 141 - 163
  • [2] A review of soft manipulator research, applications, and opportunities
    Chen, Xiaoqian
    Zhang, Xiang
    Huang, Yiyong
    Cao, Lu
    Liu, Jinguo
    [J]. JOURNAL OF FIELD ROBOTICS, 2022, 39 (03) : 281 - 311
  • [3] Bioinspired Soft Actuation System Using Shape Memory Alloys
    Cianchetti, Matteo
    Licofonte, Alessia
    Follador, Maurizio
    Rogai, Francesco
    Laschi, Cecilia
    [J]. ACTUATORS, 2014, 3 (03): : 226 - 244
  • [4] Soft Robotic Manipulators: Designs, Actuation, Stiffness Tuning, and Sensing
    Dou, Weiqiang
    Zhong, Guoliang
    Cao, Jinglin
    Shi, Zhun
    Peng, Bowen
    Jiang, Liangzhong
    [J]. ADVANCED MATERIALS TECHNOLOGIES, 2021, 6 (09)
  • [5] Model learning for robot control: a survey
    Duy Nguyen-Tuong
    Peters, Jan
    [J]. COGNITIVE PROCESSING, 2011, 12 (04) : 319 - 340
  • [6] Dielectric elastomer actuators for octopus inspired suction cups
    Follador, M.
    Tramacere, F.
    Mazzolai, B.
    [J]. BIOINSPIRATION & BIOMIMETICS, 2014, 9 (04)
  • [7] Control of pneumatic artificial muscle system through experimental modelling
    Ganguly, Shameek
    Garg, Akash
    Pasricha, Akshay
    Dwivedy, S. K.
    [J]. MECHATRONICS, 2012, 22 (08) : 1135 - 1147
  • [8] Center-of-Gravity-Based Approach for Modeling Dynamics of Multisection Continuum Arms
    Godage, Isuru S.
    Webster, Robert J., III
    Walker, Ian D.
    [J]. IEEE TRANSACTIONS ON ROBOTICS, 2019, 35 (05) : 1097 - 1108
  • [9] Dynamics for variable length multisection continuum arms
    Godage, Isuru S.
    Medrano-Cerda, Gustavo A.
    Branson, David T.
    Guglielmino, Emanuele
    Caldwell, Darwin G.
    [J]. INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2016, 35 (06) : 695 - 722
  • [10] Accurate and Efficient Dynamics for Variable-Length Continuum Arms: A Center of Gravity Approach
    Godage, Isuru S.
    Wirz, Raul
    Walker, Ian D.
    Webster, Robert J., III
    [J]. SOFT ROBOTICS, 2015, 2 (03) : 96 - 106