# Study on Elevator Recognition Techniques for Upper-Limb-Disabled Wheelchair Users
## 1 Introduction
The front-wheel- and mid-wheel-drive types exhibit no difficulties in a narrow environment due to their narrow turning radius [16]. However, due to the nature of the platform, driving is unstable on non-flat ground because of low shock absorption, making it unsuitable for outdoor use [16; 17]. On the other hand, the rear-wheel-drive type does not comply with the restrictions of the application environment because it allows relatively stable driving even on non-flat ground due to its high shock absorption power [16; 17]. However, unlike the front-wheel- and mid-wheel-drive types, the rear-wheel-drive type can cause collisions during the alignment to prepare for elevator boarding due to the wide turning radius and relatively difficult manipulation in front of the wheelchair. In addition, wheelchair users are located at an angle to the front or side with the elevator when pressing the elevator call switch, so the driving process for the alignment varies depending on the situation. Therefore, this study presents a LiDAR-sensor-based elevator recognition technique that can detect the elevator from the position and angle in front of the rear-wheel-drive wheelchair user considering boarding of the elevator in order to solve this problem. Existing elevator recognition studies used LiDAR sensors that measure fast and accurate distance values to solve the inconvenience of maintenance and repair, which is a limitation of elevator recognition using Marker [8; 9; 10; 11]. Since LiDAR sensors measure distances using light sources, the reliability of the measured distance data is determined by the type of surface material measured [14]. Various finishing materials for elevators are used, and elevators made of steel or of mirror-type stainless steel with high surface reflectivity should be additionally considered when performing elevator recognition based on LiDAR sensors. However, sensors that measure distances using light sources, such as LiDAR, show good performance with general materials with low reflectivity, but high-reflective materials with high reflectivity result in low recognition performance due to the diffused reflection of light. When scanning an elevator door finished with a low-reflective material with low surface reflectance, the shape of the elevator is clearly shown in the LiDAR raw data collected. For this reason, recognition techniques using the regularity of data are possible. However, in the case of elevators made of high-reflective materials with high surface reflectance, recognition techniques depending on regularity are impossible to use due to a high level of measurement errors in the collected data [18]. Therefore, this study proposes a technique for recognizing elevator doors finished with low- and high-reflective materials to enable elevator recognition in various elevator environments. The purpose of the proposed method is not to determine the existence of an elevator gate in the system using the vision sensor and AI technology described above, but to calculate the effective distance and coordinates for electric wheelchair entry according to the elevator structure. Therefore, the technique proposed in this paper uses LiDAR sensors based on distance information. However, since the LiDAR approach involves a sensor that uses a light source, it is necessary to take measurements according to the elevator surface material; thus, this method estimates the width and coordinates of the elevator door based on the structural features of the elevator boarding gate. The proposed recognition technique recognizes the elevator boarding gate based on the threshold value in points collected from LiDAR containing information on the boarding gate, using the lines created by the ABD (adaptive breakpoint detector) segmentation algorithm that actively responds according to the LiDAR's measurement distance and the split-and-merge-based IEPF (iterative end point fit) line segment extraction algorithm that can more clearly detect the boundary of the structure.