Modular Actuator for Multimodal Proprioceptive and Kinesthetic Feedback of Robotic Hands

IF 5.3 2区 计算机科学 Q2 ROBOTICS
Sungwoo Park;Myo-Taeg Lim;Donghyun Hwang
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引用次数: 0

Abstract

This study addresses the challenge of implementing proprioceptive and kinesthetic (PK) feedback in robotic hands, essential for grasping and manipulation tasks in unstructured environments. We developed a compact modular actuator featuring a low-module, high-transmission-ratio multistage gear mechanism that measures 25 × 10 × 24 mm, weighs only 10 grams, and maintains moderate backdrivability. The actuator provides multimodal PK feedback, capturing position, velocity, current, and torque data, which are critical for performing various grasping and manipulation tasks. To enable precise motion and force control, we introduced a new adaptive velocity estimator and a simplified Reaction Torque Observer (RTOB). Comprehensive experiments demonstrated the actuator's ability to accurately detect surface shape, roughness, and stiffness of target objects, eliminating the need for additional sensors or space. Experimental results confirmed the actuator's precision, achieving measurement errors of 5.8 mrad for position, 0.19 rad/s for velocity, and 0.011 N·m for torque. These findings highlight the actuator's ability to leverage proprioceptive information, significantly enhancing the functionality and adaptability of robotic hands in diverse and dynamic scenarios.
多模态机械手本体感觉和运动反馈的模块化驱动器
本研究解决了在机器人手中实现本体感觉和动觉(PK)反馈的挑战,这对于非结构化环境中的抓取和操作任务至关重要。我们开发了一种紧凑型模块化执行器,具有低模块,高传动比多级齿轮机构,尺寸为25 × 10 × 24 mm,重量仅为10克,并保持适度的反驾驶性。执行器提供多模态PK反馈,捕获位置,速度,电流和扭矩数据,这对于执行各种抓取和操作任务至关重要。为了实现精确的运动和力控制,我们引入了一种新的自适应速度估计器和简化的反作用力观测器(RTOB)。综合实验证明,该驱动器能够准确检测目标物体的表面形状、粗糙度和刚度,无需额外的传感器或空间。实验结果证实了执行器的精度,位置测量误差为5.8 mrad,速度测量误差为0.19 rad/s,扭矩测量误差为0.011 N·m。这些发现突出了驱动器利用本体感觉信息的能力,显著增强了机械手在各种动态场景中的功能和适应性。
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来源期刊
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters Computer Science-Computer Science Applications
CiteScore
9.60
自引率
15.40%
发文量
1428
期刊介绍: The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.
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