传感器模式控制机器人眼头运动辅助任务的可行性分析

J. Schäfer, Marion Gebhard
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引用次数: 2

摘要

辅助机器人为有严重运动障碍(即四肢瘫痪)的人提供了一种无需帮助即可完成日常任务的方法。在这项工作中,研究了控制机器人系统的新传感器模式,以使四肢瘫痪患者在日常生活中获得更多的自主权。在这项工作中,测试和比较了几种捕获与用户相关信息的方式。五种传感器模式,眼电图、基于视频的眼动追踪、MARG传感器、基于视频的头部追踪和耳后肌肌电图,可用于控制机器人的免提。提出用头部运动作为连续控制,眼动作为离散事件控制。测试表明,MARG传感器是最可靠的跟踪头部运动和眼球追踪眼镜捕捉眼睛的运动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Feasibility analysis of sensor modalities to control a robot with eye and head movements for assistive tasks
Assistive robotics has offered a way for people with severe motor disabilities (i. e. tetraplegics) to perform every day tasks without help. New sensor modalities to control a robot system are investigated within this work to enable tetraplegics to gain more autonomy in everyday life. In this work several modalities to capture information related to the user are tested and compared. The five sensor modalities, electrooculography, video-based eye tracking, MARG sensors, video-based head tracking and electromyography of the posterior auricular muscle, can be used to control a robot hands-free. It is proposed to use movements of the head as continuous control and eye movements as discrete event control. The tests show that the MARG sensors are most reliable to track head movements and eye tracking glasses to capture movements of the eyes.
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