Advanced Human-Robot Collaborative Assembly Using Electroencephalogram Signals of Human Brains
Abdullah Mohammed, Lihui Wang
Abstract
This paper introduces an intelligent system that can manipulate an industrial robot using the electroencephalogram signals of human brains to perform collaborative assembly tasks. The system is initiated by capturing the brain signals using a wearable headset, and the signals are then filtered to remove any possible artifact. Consequently, the process continues by identifying the brain signals patterns using a classifier based on pre-recorded samples. The classifier’s output determines the proper matching of the robot command that is intended by the human. To validate the results, an industrial collaborative assembly scenario of a car manifold is examined as a case study.
Topics & Concepts
HeadsetClassifier (UML)Artificial intelligenceRobotWearable computerComputer scienceHuman–robot interactionHuman–computer interactionTemplate matchingEngineeringComputer visionEmbedded systemTelecommunicationsImage (mathematics)EEG and Brain-Computer InterfacesRobot Manipulation and LearningGaze Tracking and Assistive Technology