Development of an Adaptive Force Control Strategy for Soft Robotic Gripping

被引:1
|
作者
MacDonald, Ian [1 ]
Dubay, Rickey [1 ]
机构
[1] Univ New Brunswick, Dept Mech Engn, Fredericton, NB E3B 5A3, Canada
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 16期
基金
加拿大自然科学与工程研究理事会;
关键词
soft robotics; adaptive control; computer vision;
D O I
10.3390/app14167354
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Using soft materials in robotic mechanisms has become a common solution to overcome many challenges associated with the rigid bodies frequently used in robotics. Compliant mechanisms allow the robot to adapt to objects and perform a broader range of tasks, unlike rigid bodies that are generally designed for specific applications. However, soft robotics presents its own set of challenges in both design and implementation, particularly in sensing and control. These challenges are abundant when dealing with the force control problem of a compliant gripping mechanism. The ability to effectively regulate the applied force of a gripper is a critical task in many control operations, as it allows the precise manipulation of objects, which drives the need for enhanced force control strategies for soft or flexible grippers. Standard sensing techniques, such as motor current monitoring and strain-based sensors, add complexities and uncertainties when establishing mathematical models of soft grippers to the required gripping forces. In addition, the soft gripper creates a complex non-linear system, compounded by adding an adhesive-type sensor. This work develops a unique visual force sensor trained on synthetic data generated using finite element analysis (FEA) and implemented by integrating a non-linear model reference adaptive controller (MRAC) to control gripping force on a fixed 6-DOF robot. The robot can be placed on a mobile platform to perform various tasks. The virtual FEA sensor and controller, combined, are termed virtual reference adaptive control (VRAC). The VRAC was compared to other methods and achieved comparable control sensing and control performance while reducing the complexity of the sensor requirements and its integration. The VRAC strategy effectively controlled the gripping force by driving the dynamics to match the desired performance after a limited amount of training cycles. The controller proposed in this work was designed to be generally applicable to most objects that the gripper will interact with and easily adaptable to a wide variety of soft grippers.
引用
收藏
页数:19
相关论文
共 50 条
  • [41] Experiences in the development of a robotic application with force control for bone drilling
    Fraile, J. C.
    Perez-Turiel, J.
    Gonzalez-Sanchez, J. L.
    Lopez-Cruzado, J.
    Rodriguez, J. L.
    REVISTA IBEROAMERICANA DE AUTOMATICA E INFORMATICA INDUSTRIAL, 2008, 5 (02): : 93 - +
  • [42] Soft touch control strategy of remote teaching based on force sensing
    Liu, L. J.
    Gao, H. M.
    Zhang, G. J.
    Wu, L.
    ROBOTIC WELDING, INTELLIGENCE AND AUTOMATION, 2007, 362 : 31 - +
  • [43] Development of an Intention-Based Adaptive Neural Cooperative Control Strategy for Upper-Limb Robotic Rehabilitation
    Wu, Qingcong
    Chen, Ying
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2021, 6 (02) : 335 - 342
  • [44] Bionic soft robotic gripper with feedback control for adaptive grasping and capturing applications
    Wu, Tingke
    Liu, Zhuyong
    Ma, Ziqi
    Wang, Boyang
    Ma, Daolin
    Yu, Hexi
    FRONTIERS OF MECHANICAL ENGINEERING, 2024, 19 (01)
  • [45] Towards Adaptive Continuous Control of Soft Robotic Manipulator using Reinforcement Learning
    Li, Yingqi
    Wang, Xiaomei
    Kwok, Ka-Wai
    2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, : 7074 - 7081
  • [46] Adaptive robust control for a soft robotic snake: A smooth-zone approach
    Yin, Hui
    Chen, Ye-Hwa
    Yu, Dejie
    Lu, Hui
    Shangguan, Wenbin
    APPLIED MATHEMATICAL MODELLING, 2020, 80 : 454 - 471
  • [47] Mechanics of a pressure-controlled adhesive membrane for soft robotic gripping on curved surfaces
    Song, Sukho
    Drotlef, Dirk-M
    PaIk, Jamie
    Majidi, Carmel
    Sitti, Metin
    EXTREME MECHANICS LETTERS, 2019, 30
  • [48] Cascade Motion/Force Control Strategy of nonholonomic Wheeled Mobile Robotic Systems
    Dao Phuong Nam
    Nguyen Hong Quang
    Dinh Nhat Anh
    Tran Quang Huy
    PROCEEDINGS OF 2019 5TH INTERNATIONAL CONFERENCE ON MECHATRONICS AND ROBOTICS ENGINEERING (ICMRE 2019), 2019, : 118 - 122
  • [49] Adaptive Trajectory Control to Achieve Smooth Interaction Force in Robotic Rehabilitation Device
    Anwar, Tanvir
    Al Juamily, Adel
    MEDICAL AND REHABILITATION ROBOTICS AND INSTRUMENTATION (MRRI2013), 2014, 42 : 160 - 167
  • [50] A Bi-Criteria Kinematic Strategy for Motion/Force Control of Robotic Manipulator
    Xie, Zhengtai
    Li, Shuai
    Jin, Long
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2024, 21 (04) : 5570 - 5582