一种可负担的人机交互抓取训练和物体抓取遥机器人系统架构

Sudip Hazra, Abdul Hafiz Abdul Rahaman, P. Shiakolas
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引用次数: 0

摘要

由于行动障碍,一个人可能依赖轮椅、手杖和拐杖来帮助,但在执行诸如抓握和操纵物体等任务时,由于接触和能力的限制,可能会面临挑战。为了克服这些挑战,可以使用具有拟人化机械手(ARH)的多自由度机械臂。在这项研究中,我们提出了一个架构,然后将其实现到辅助系统的开发中,以帮助人们抓取物体。该体系结构将三个功能模块连接起来,提供三种操作模式来校准系统,训练用户如何执行抓握、综合抓握和执行抓握。开发的系统包括一个用户输入和反馈手套,能够捕获用户输入并提供与抓取相关的振动触觉反馈,一个基于coppeliasim的虚拟环境模拟ARH的运动,以及一个能够在感知抓取接触位置时执行抓取的欠驱动ARH。对所开发的系统的操作进行评估,以确定一个人操作它的能力,并使用两种控制方法执行抓握;采用综合抓取或实时连续控制。成功的评估验证了体系结构和开发的系统,以提供执行把握的能力。评估结果为扩展系统功能提供了信心,并将其用于开发具有不同几何形状的物体抓取轨迹数据库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Affordable Telerobotic System Architecture for Grasp Training and Object Grasping for Human-machine Interaction
Due to mobility impairment, a person might rely on wheelchairs, canes, and crutches for assistance but could face challenges when performing tasks such as grasping and manipulating objects due to limitations in reach and capability. To overcome these challenges, a multi-degree-of-freedom robotic arm with an anthropomorphic robotic hand (ARH) could be used. In this research, we propose an architecture and then implement it towards the development of an assistive system to assist a person with object grasping. The architecture interlinks three functional modules to provide three operation modes to calibrate the system, train a user on how to execute a grasp, synthesize grasps, and execute a grasp. The developed system consists of a user input and feedback glove capable of capturing user inputs and providing grasp-related vibrotactile feedback, a CoppeliaSim-based virtual environment emulating the motions of the ARH, and an underactuated ARH capable of executing grasps while sensing grasp contact locations. The operation of the developed system is evaluated to determine the ability of a person to operate it and perform a grasp using two control methods; using a synthesized grasp or under real-time continuous control. The successful evaluation validates the architecture and the developed system to provide the ability to perform a grasp. The results of the evaluation provide confidence in expanding the system capabilities and use it to develop a database of grasp trajectories of objects with different geometries.
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