Grasping with Your Face
Grasping with Your Face
复制标题
抓住你的脸
DOI：
10.1007/978-3-319-00065-7_30
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
P. Allen
中科院分区：
文献类型：
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作者：
Jonathan Weisz;Ben Shababo;Lixing Dong;P. Allen
脑机接口（BCI）技术在辅助机器人领域显示出巨大的潜力。特别是，严重受损的人缺乏使用他们的手和手臂将大大受益于机器人抓取系统，可以通过一个简单而直观的BCI控制。在本文中，我们描述了一个端到端的机器人抓取系统，它是由四个分类的面部肌电信号控制，从而产生强大和稳定的把握。前端视觉系统用于识别和登记要根据模型数据库抓取的对象。一旦模型对齐，它可以用于实时抓取计划模拟器，该模拟器通过离散和连续模式下的非侵入性和廉价的BCI接口进行控制。用户可以通过BCI界面控制接近方向，还可以帮助计划者选择最佳抓握方式。一旦规划了抓取，机器人手/臂系统就可以执行抓取。我们展示了使用该系统从多个不同的接近方向实时拾取各种物体的结果，仅使用面部BCI信号。我们相信这个系统是一个全自动辅助抓取系统的工作原型。
BCI (Brain Computer Interface) technology shows great promise in the field of assistive robotics. In particular, severely impaired individuals lacking the use of their hands and arms would benefit greatly from a robotic grasping system that can be controlled by a simple and intuitive BCI. In this paper we describe an end-to-end robotic grasping system that is controlled by only four classified facial EMG signals resulting in robust and stable grasps. A front end vision system is used to identify and register objects to be grasped against a database of models. Once the model is aligned, it can be used in a real-time grasp planning simulator that is controlled through a non-invasive and inexpensive BCI interface in both discrete and continuous modes. The user can control the approach direction through the BCI interface, and can also assist the planner in choosing the best grasp. Once the grasp is planned, a robotic hand/arm system can execute the grasp. We show results in using this system to pick up a variety of objects in real-time, from a number of different approach directions, using facial BCI signals exclusively. We believe this system is a working prototype for a fully automated assistive grasping system.