Learning Optimal Fin-Ray Finger Design for Soft Grasping

Author:

Deng Zhifeng,Li Miao

Abstract

The development of soft hands is an important progress to empower robotic grasping with passive compliance while greatly decreasing the complexity of control. Despite the advances during the past decades, it is still not clear how to design optimal hands or fingers given the task requirements. In this paper, we propose a framework to learn the optimal design parameter for a fin-ray finger in order to achieve stable grasping. First, the pseudo-kinematics of the soft finger is learned in simulation. Second, the task constraints are encoded as a combination of desired grasping force and the empirical grasping quality function in terms of winding number. Finally, the effectiveness of the proposed approach is validated with experiments in simulation and using real-world examples as well.

Publisher

Frontiers Media SA

Subject

Artificial Intelligence,Computer Science Applications

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Development and Investigation of a Grasping Analysis System with Two-Axis Force Sensors at Each of the 16 Points on the Object Surface for a Hardware-Based FinRay-Type Soft Gripper;Sensors;2024-07-28

2. Versatile 3D-printed fin-ray effect soft robotic fingers: lightweight optimization and performance analysis;Journal of the Brazilian Society of Mechanical Sciences and Engineering;2024-05-23

3. Dynamic evaluation of a suction based gripper for fruit picking using a physical twin;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

4. Enhancing the Performance of Fin Ray Effect Soft Robotic Finger via Computational Design and Simulation;2024 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC);2024-05-02

5. Design and Development of Fin-Ray Finger using Topology Optimization with Multiple Load Cases;2024 International Conference on Cognitive Robotics and Intelligent Systems (ICC - ROBINS);2024-04-17

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