Mind Control of a Service Robot with Visual Servoing
Lina Zhang, Zhe Sun, Feng Duan, Chi Zhu, Hiroshi Yokoi
Abstract
In the growing elderly population globally, patients with severe movement disorders account for a large proportion. Moreover, the development of intelligent service equipment can better assist them in their daily. This paper proposes a new service robot control system. The brain-computer interface (BCI) based on Steady-State Visual Evoked Potentials (SSVEP) is used to acquire and process electroencephalogram(EEG) signals and output various control commands accordingly. Then, considering the visual fatigue of SSVEP-BCI, we added an object detection method based on Yolov3-tiny and saliency prediction to identify the patient’s selection intention intelligently. The results show that the subject can successfully complete the object delivery task with an average accuracy of 90.3%. The proposed control system can help the patients control a service robot in a more intelligent and friendly way to realize some daily tasks.
BibTeX
@inproceedings{iros2021_mindcontrolofase,
title = {Mind Control of a Service Robot with Visual Servoing},
author = {Lina Zhang and Zhe Sun and Feng Duan and Chi Zhu and Hiroshi Yokoi},
booktitle = {IROS 2021},
year = {2021}
}