###### Abstract  
As the world enters an aging and super-aged society, the application of advanced technology in assistive devices to support the daily life of the elderly is becoming a hot issue. Among them, electric wheelchairs are representative assistive devices for the walking support of the elderly, and their structural form is similar to AGV and AMR. For this reason, research is being introduced and underway to guarantee the right to voluntarily move or improve the convenience of movement for the elderly and severely disabled people who have difficulties in operating a joystick for operating an electric wheelchair. Autonomous driving of mobile robots is a technology that configures prior information on the driving environment as a map DB and operates based on it. However, active driving assistance technology is needed because wheelchairs do not move in a limited space, but can move to a place without a prior map DB or vehicle boarding depending on the passenger's intention to move. Therefore, a system for estimating the moving position and direction of the wheelchair is needed to develop a driving assistance technology in the relevant driving environment. In order to solve the above problem, this study proposes a position and direction estimation algorithm suitable for active driving of a wheelchair based on a UWB sensor. This proposal is an algorithm for estimating the position and direction of the wheelchair through the fusion of UWB, IMU, and encoder sensors. In this proposal, it is difficult to design an active driving assistance system for wheelchairs due to low accuracy, obstacles, and errors due to signal strength in the position and direction estimation with UWB sensors alone. Therefore, this study proposes a wheelchair driving position and direction estimation system that fuses the dead recording information of a wheelchair and the UWB-based position estimation technique based on sensors applied in IMU and encoders. Applying quantitative verification to the proposed technique, the direction estimation accuracy of the wheelchair of about 15.3\({}^{\circ}\) and the position estimation error average of \(\pm\)15 cm were confirmed, and it was verified that a driving guide for active driving was possible when the sensor system proposed in a mapless environment of the wheelchair was installed at a specific destination. position estimation; sensor fusion; ultra-wide band positioning; electronic wheelchair direction estimation +
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this demand, the wheelchair market size is expected to grow by 7.40% annually to reach $9.5 billion by 2032, of which the market size of electric wheelchairs accounts for more than 50% [3]. Here, 58.9% of users of electric assistive devices such as electric wheelchairs experienced accidents, of which 34.5% were involved in crashes [4]. Although it depends on the degree of disability among people with disabilities such as cognition, movement, and sensation, they generally have difficulties in fine manipulation of the joystick used for electric wheelchair operation [5]. As a result, research is being conducted to assist wheelchair convenience and collision stability by applying it to wheelchairs due to the advancement of indoor autonomous driving technology used in AGVs (Automated Guided Vehicles) and AMRs (Autonomous Mobile Robots), which have recently become a technical topic following the advent of the fourth industry [6]. Based on research on applying the autonomous driving technology of mobile robots as wheelchairs, wheelchairs capable of autonomous driving are used to help wheelchair users move only in limited spaces such as hospitals [7]. Due to the support of wheelchairs capable of autonomous driving in indoor spaces, users who complain of difficulties in wheelchair operation can use them without any manipulation. Thus, it is a hot issue because it can prevent collisions caused by inexperience in operation [8].