Telepresence control of humanoid robot via high-frequency phase-tagged SSVEP stimuli

This paper presents a high-frequency steady-state visual evoked potential-based model for a brain-controlled humanoid robot. An advantage of this model is to reduce subjects' fatigue by using visual stimuli with a frequency of 30Hz. This study optimizes the stimulus patterns to increase the bra...

Full description

Saved in:
Bibliographic Details
Published inProceedings (International Workshop on Advanced Motion Control) pp. 214 - 219
Main Authors Hu, Hong, Zhao, Jing, Li, Hongbo, Li, Wei, Chen, Genshe
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 20.06.2016
Subjects
brain-robot interaction
Commands
Fatigue (materials)
Feedback
fuzzy feedback classification
Gratings
high-frequency steady-state visual evoked potentials
Humanoid
humanoid robot
Humanoid robots
Missions
Monitoring
Navigation
Robot control
Robots
Shape
Stimuli
Visualization
Online AccessGet full text
ISSN1943-6580
DOI10.1109/AMC.2016.7496353

Cover

More Information
Summary:This paper presents a high-frequency steady-state visual evoked potential-based model for a brain-controlled humanoid robot. An advantage of this model is to reduce subjects' fatigue by using visual stimuli with a frequency of 30Hz. This study optimizes the stimulus patterns to increase the brain signals and applies a fuzzy-based classification approach to identify human mental activities and convert them into control commands. Seven subjects successfully navigated a NAO humanoid robot to walk through a map with obstacle avoidance based on live video feedback. The on-line robot navigation experiment reached the average control success rate of 94.26% and an average collision of 1.8 times during a mission.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Conference-1
ObjectType-Feature-3
content type line 23
SourceType-Conference Papers & Proceedings-2
ISSN:1943-6580
DOI:10.1109/AMC.2016.7496353