An EEG-Based Brain-Computer Interface for Guiding Mobile Robots

The term "robot" refers to an electromechanical device that, as a result of its incorporation of electronic and computer programming, may carry out tasks either independently or in conjunction with a human operator [1]. Robots can be designed to perform functions in any order that the programmer specifies. Robots have found uses in a broad variety of disciplines, including those connected to the military, healthcare, and industry, among a number of other fields. Robots can be programmed to perform in either a mobile or stationary manner, and the choice of which mode to use is often dictated by the tasks that are intended to be carried out by the robots. It is extremely essential for a mobile robot to be able to traverse its environment in order for the robot to be capable of efficiently completing tasks, avoiding obstacles, and participating in other activities. This capability for navigation, which is dependent on sensors to supply environmental data as feedback signals, can be operator-independent or autonomous if "intelligence" is built into the computer code. Sensors are required to provide environmental data as feedback signals. Sensors are required to provide environmental data as return signals. This learning opportunity can be further used in affordable energy, agriculture, environmentally sound technologies, etc.