A method of brain computer cooperative navigation combined with simultaneous localization and mapping

Abstract

Introducing human brain intelligence into robot system is an effective means to improve robot's cognition and decision-making ability. Aiming at the problems of human brain fatigue and the need of multi lead information in brain robot control, a brain computer cooperative navigation method combining synchronous localization and mapping (SLAM) is proposed in this paper. Through the steady-state visual evoked potential based on three leads, the image of the target area of interest of human brain is selected, and the brain computer cooperative navigation task is completed by combining SLAM and artificial potential field. The test results show that the average accuracy of the target area image selection method based on steady-state visual evoked potential is 94.17%, which proves that the three leads are effective. On this basis, the brain computer cooperative navigation method combined with SLAM is tested. The results show that the completion rate of navigation task is as high as 92.5%. This method alleviates the fatigue of human brain and reduces the hardware requirements of EEG acquisition.

Keywords

• slam
• steady-state visual evoked potential
• brain computer cooperative
• navigation
• artificial potential field