The concept of controlling a wheelchair using brain signals is promising. However, the continuous control of a wheelchair based on unstable and noisy electroencephalogram signals is unreliable and generates a significant mental burden for the user. A feasible solution is to integrate a brain-computer interface (BCI) with automated navigation techniques. This paper presents a brain-controlled intelligent wheelchair with the capability of automatic navigation. Using an autonomous navigation system, candidate destinations and waypoints are automatically generated based on the existing environment. The user selects a destination using a motor imagery (MI)-based or P300-based BCI. According to the determined destination, the navigation system plans a short and safe path and navigates the wheelchair to the destination. During the movement of the wheelchair, the user can issue a stop command with the BCI. Using our system, the mental burden of the user can be substantially alleviated. Furthermore, our system can adapt to changes in the environment. Two experiments based on MI and P300 were conducted to demonstrate the effectiveness of our system.

In this paper, we propose an intelligent wheelchair system that relies on a brain computer interface (BCI) and automatic navigation. When in operation, candidate destinations and waypoints are automatically generated on the basis of the current environment. Then, the user selects a destination using a P300-based BCI. Finally, the navigation system plans a path and navigates the wheelchair to the determined destination. While the wheelchair is in motion, the user can issue a stop command with the BCI. Using our system, the mental burden of the user can be alleviated to a large degree. Furthermore, our system can adapt to changes in the environment. The experimental results demonstrated the effectiveness of our system.

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