A teleoperation robot system and method driven by mixed bioelectrical signals

Abstract

The invention discloses a remote operation robot system driven by mixed bioelectrical signals, which includes an EEG signal acquisition module, an oculoelectric signal acquisition module, a signal processing module, a wireless network transmission module, a robot control module, a force-tactile detection module, a vision Detection module, tactile feedback module and visual feedback module. The invention also discloses a control method of a remote-operated robot system driven by mixed bioelectrical signals. The invention controls the tele-operated robot through the combination of the operator's motor imagery EEG signal and oculoelectric signal, and simultaneously uses visual feedback and force Haptic feedback provides real-time feedback of control status, improving control efficiency and precision.

Description

technical field [0001] The invention relates to the field of brain-computer interface, in particular to a teleoperated robot system and method driven by mixed bioelectrical signals. Background technique [0002] With the continuous development of science and technology, a new type of control system called brain control has developed rapidly. This is a human-computer integrated control system based on a brain-computer interface (BCI). A communication control system that does not depend on the normal output channels of peripheral nerves and muscles in the brain, the brain-computer interface system has been successfully applied to life assistance for the disabled, rehabilitation training for stroke patients and injured limbs, real-time monitoring of operator status, and game entertainment. And smart home, control engineering, aerospace and other fields. [0003] At present, the existing robot control system based on motor imagery EEG signals is a one-dimensional discrete contr...

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Problems solved by technology

[0003] At present, the existing robot control system based on motor imagery EEG signals is a one-dimensional discrete control system. Each motor imagery task corresponds to a control command, and each time a motor imagery task is executed, a control command is sent to control the robot to do a corresponding Action, man-machine efficiency is poor, and it is difficult to meet the needs of the operator to control the robot by using EEG. In order to realize the natural communication between the user and the environment, it is very important to realize the two-dimensional continuous control system of the robot based on EEG signals.

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