返回
Robust Visual Feedback Control for Precise In-Hand Manipulation Using Parallel Soft Actuators
DOI:10.1109/TRO.2024.3410130.png)
摘要
En 中文
Soft robotic hands are reliable for grasping objects of various shapes. However, they perform poorly in the high-precision manipulation of grasped objects because the modeling and sensing of soft actuator deformation are complex. To overcome this problem, in a previous study, we proposed a robust visual feedback control method for precise in-hand manipulation using parallel soft actuators. This method enables precise in-hand manipulation without measuring the soft actuator deformations. Generally, in the feedback control of a parallel drive system, the actuator force is converted into the force/torque applied to the grasped object. The conversion matrix constantly changes depending on the position/orientation of the object and the contact points of the soft actuators with the object. Consequently, accurately measuring the conversion matrix is difficult. Therefore, we estimated it as a constant matrix in our previous studies, and its robustness was confirmed experimentally. However, its theoretical robustness was not analyzed sufficiently. Therefore, in this article, we discuss the robustness of the estimated constant matrix through a mathematical stability proof. Furthermore, we investigate the characteristics of the estimated drive matrix. Then, we perform a numerical robustness analysis. Finally, the robustness of the proposed method is studied via the above investigation and verification experiments.
Keyword:
In-hand manipulation
parallel mechanism
robust control
soft robotic hand
visual feedback control
期刊
IF:
10.5
论文数:
3.3K
被引数:
2.8W
机构
引用论文
Bending angle prediction and control of soft pneumatic actuators with embedded flex sensors - A data-driven approach
MECHATRONICS
IF3.1
Multimode Grasping Soft Gripper Achieved by Layer Jamming Structure and Tendon-Driven Mechanism通过层卡结构和腱驱动机构实现多模式抓取软夹持器
SOFT ROBOTICS
IF6.1
Flexible self-powered multifunctional sensor for stiffness-tunable soft robotic gripper by multimaterial 3D printing用于多材料3D打印的刚度可调柔性机器人手爪的柔性自供电多功能传感器
NANO ENERGY
IF17.1

