基于强化学习的变刚度软抓手在高速运动中的鲁棒抓取。

IF 6.4 2区 计算机科学 Q1 ROBOTICS
Soft Robotics Pub Date : 2024-02-01 Epub Date: 2023-07-21 DOI:10.1089/soro.2022.0246
Mingzhu Zhu, Junyue Dai, Yu Feng
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引用次数: 0

摘要

工业机器人被广泛应用于高速执行拾放任务,以最大限度地缩短生产时间并提高生产率。在处理精密或易碎物品时,软质机器人抓手因其柔软性和安全交互性,比刚性抓手更适合作为终端执行器。然而,高速运动会导致软机械手振动,从而导致物体损坏或抓取失败。具有可变刚度的软机械手被认为可以通过添加阻尼装置来有效抑制振动,但要在刚度和顺应性之间取得折衷是相当具有挑战性的。本文提出了一种基于深度强化学习的控制器来控制软机械手的刚度,它可以精确地抑制振动,而对其顺应性和柔软度的影响很小。所提出的控制器是一种实时振动控制策略,可根据当前的运行环境估计控制器的输出。为了证明所提控制器的有效性,我们使用 UR5 机械臂进行了实验。实验结果表明,对于不同的情况,所提出的控制器都能快速响应,并大幅降低振荡幅度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Grasping of a Variable Stiffness Soft Gripper in High-Speed Motion Based on Reinforcement Learning.

Industrial robots are widely deployed to perform pick-and-place tasks at high speeds to minimize manufacturing time and boost productivity. When dealing with delicate or fragile goods, soft robotic grippers are better end effectors than rigid grippers due to their softness and safe interaction. However, high-speed motion causes the soft robotic gripper to vibrate, leading to damage of the objects or failed grasping. Soft grippers with variable stiffness are considered to be effective in suppressing vibrations by adding damping devices, but it is quite challenging to compromise between stiffness and compliance. In this article, a controller based on deep reinforcement learning is proposed to control the stiffness of the soft robotic gripper, which can accurately suppress the vibration with only a minor influence on its compliance and softness. The proposed controller is a real-time vibration control strategy, which estimates the output of the controller based on the current operating environment. To demonstrate the effectiveness of the proposed controller, experiments were done with a UR5 robotic arm. For different situations, experimental results show that the proposed controller responds quickly and reduces the amplitude of the oscillation substantially.

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来源期刊
Soft Robotics
Soft Robotics ROBOTICS-
CiteScore
15.50
自引率
5.10%
发文量
128
期刊介绍: Soft Robotics (SoRo) stands as a premier robotics journal, showcasing top-tier, peer-reviewed research on the forefront of soft and deformable robotics. Encompassing flexible electronics, materials science, computer science, and biomechanics, it pioneers breakthroughs in robotic technology capable of safe interaction with living systems and navigating complex environments, natural or human-made. With a multidisciplinary approach, SoRo integrates advancements in biomedical engineering, biomechanics, mathematical modeling, biopolymer chemistry, computer science, and tissue engineering, offering comprehensive insights into constructing adaptable devices that can undergo significant changes in shape and size. This transformative technology finds critical applications in surgery, assistive healthcare devices, emergency search and rescue, space instrument repair, mine detection, and beyond.
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