文献类型：期刊文献

英文题名：An EEG based dynamic shared control method for online teleoperation

作者：Zhu, Guodong[1]; Zhang, Kaiming[1]; Liu, Shuang[1]; Qian, Bo[1]; Zhang, Xiancheng[1]

机构：[1] School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, 200237, China

年份：2017

卷号：2018-January

起止页码：1

外文期刊名：2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017

收录：EI(收录号：20182905568265)

语种：英文

外文关键词：Controllers - Neural networks

摘要：Shared control is a common method for human and machine cooperation in the teleoperation. Existing methods scarcely consider the effect of the performance of operators. This paper proposes a dynamic shared control approach based on the operator's states. A new indicator named Performance of Teleoperator (PoT) is introduced. By using the BP Neural Network, a model of PoT is trained, which represents the performance of the human teleoperator from the view angle of the brain EEG signals. Meanwhile, a dynamic shared controller is designed. PoT is used to balance the control weight between instructions from the teleoperator and the autonomous controller. The experimental results demonstrate the effectiveness and advantages of the proposed method. ? 2017 IEEE.