Control method of robot detour obstacle based on EEG

• Published in: Neural computing & applications Vol. 34; no. 9; pp. 6745 - 6752
• Main Authors: Wang, Qingjun, Mu, Zhendong, Jin, Ling
• Format: Journal Article
• Language: English
• Published: London Springer London 01.05.2022; Springer Nature B.V
• Subjects: Artificial Intelligence; Barriers; Brain; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Control methods; Data Mining and Knowledge Discovery; Electroencephalography; Feature extraction; Image Processing and Computer Vision; Probability and Statistics in Computer Science; Recognition; Robot control; Robots; S.I on NC for Industry 4.0; Special Issue on Neural Computing Challenges and Applications for Industry 4.0; Sports; Training; Four dimensions; Sample entropy; Path optimization; Electroencephalogram (EEG); Robot control; Comprehensive learning
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-021-06155-8

With the development of science and technology and the progress of the times, robots have slowly entered people's lives and work. However, how to control robots to bypass obstacles has become the focus of current research. Different from other related researches, the main research purpose of this paper is to use electroencephalogram (EEG) to control robots and achieve obstacles. In this paper, sample entropy is used to extract features of EEG, and then integrated learning is used to classify the extracted features. In the research process, this paper analyses the changes in the accuracy of the subjects before and after training, respectively, analyses the results of the two kinds of sports recognition, and then analyses the distribution of brain regions for motor control. Through the experiment on 12 subjects, the results show that through training, the four sports can achieve the highest recognition result of 85.4%. The experimental results show that, for the specific analysis of the distribution of brain regions, it can be seen that there are obvious differences in the characteristics of the left and right brains that control the movement of the robot, but there are differences in the control of the movement of the robot.