## 1 Introduction  
While a powered wheelchair is an important assistive product for a person who is physically handicapped, a person with a disability of the upper body cannot use a joystick. To this end, there has been the recent development of Human-Computer Interfaces (HCIs) that have replaced joysticks. Examples of these HCIs include voice control [1], brain-machine interfaces (BMI) [2], facial muscles [3], and eye blinks [4]. In this study, movement of the eyes is used as an HCI. It is known that the muscle around the eyes has a long-lasting functionality, so this HCI has a high likelihood of being available even if a person cannot move his or her mouth, face, or neck. There are several conventional methods that use the movement of eyes as an HCI. [PERSON] et al. proposed an electrooculography (EOG) based control algorithm for target navigation [5; 6; 7]; however, their technique necessitated attachment of surface electrodes around the eyes of the operator,and two modes of wheelchair control were proposed--manual and automatic. In the manual mode, the passenger inputs a turn right or turn left signal by looking towards the right or left. Likewise, one may move forward or stop by looking up or down, respectively. In the automatic mode of operation, the user looks towards a desired destination and blinks (right to start and left to stop) to starts navigating the wheelchair to the target position. However, the operation in this mode is constrained by a well-defined and known environment. [PERSON] and colleagues proposed a method that inputs a turn right and turn left signal by moving the gaze direction to the right and left and moves forward and stops by moving the gaze direction up and down using the head gear with EOG electrodes [8]. [PERSON] proposed a method in which the gaze direction is detected by processing images, using two charge coupled device cameras [9]. The self-position and the environment are recognized using a laser range finder (LRF) and a map that is created in advance. Consequently, the gaze position of the passenger in the environment is estimated. However, it is difficult for the wheelchair to move in the unknown environment because the map created in advance is needed. Conventional methods of controlling wheelchair systems in unknown environments also exist. A wheelchair exploring an unknown environment requires real-time map generation and path planning to ensure accurate obstacle-avoiding navigation. This is accomplished by recognizing the surrounding environment through use of electronic sensors. Examples of these systems include those described in [10; 11], NavChair developed by [PERSON] et al. [12], SENARIO (Sensor-Aided Intelligent Wheelchair Navigation) developed by [PERSON] et al. [13], and the Robchair developed by [PERSON] et al. [14]. This paper proposes an eye-gaze controlled wheelchair system for navigating through unknown environments. [PERSON] and his colleagues proposed a system for controlling wheelchairs by eye gaze in unknown environments [15]. Their system comprised eye-tracking glasses, depth camera to capture the geometry of the ambient space, and a set of ultrasound and infrared sensors to detect obstacles. The passenger provides inputs to the wheelchair system to move forward, stop, and turn left or right by looking up, down, left, or right, respectively, along arrows displayed on a laptop placed in front of the passenger. However, this method was found to be ineffective when dealing with complicated environments, because of the constraints associated with input directions. This paper refers to complicated environments as those wherein some passages exist on the same side (either left or right) as shown in Figure 1. This renders the navigation operation difficult and complicated. In view of the above difficulties, the wheelchair control system proposed in this study aims to achieve an operation wherein the passenger actually gazes towards the direction in which he or she wishes to move in an unknown environment.