Multi-floor navigation of a mobile robot requires a technology that allows the robot to safely get on and off the elevator. Therefore, in this study, we propose a method of recognizing the elevator from the current position of the robot and estimating the location of the elevator locally so that the robot can safely get on the elevator regardless of the accumulated position error during autonomous navigation. The proposed method uses a deep learning-based image classifier to identify the elevator from the image information obtained from the RGB-D sensor and extract the boundary points between the elevator and the surrounding wall from the point cloud. This enables the robot to estimate the reliable position in real time and boarding direction for general elevators. Various experiments exhibit the effectiveness and accuracy of the proposed method.

Abstract
1. 서 론
2. 엘리베이터 존재 여부 판단
    2.1 Inception v3의 학습
    2.2 RGB 이미지의 전처리
3. 엘리베이터 위치
    3.1 점군 정보 전처리
    3.2 엘리베이터 문과 주변 벽면 경계점 추출
    3.3 엘리베이터 문의 위치와 진입 방향 선정
4. 실 험
    4.1 엘리베이터 인식이 가능한 센서 방향 실험
    4.2 엘리베이터 위치추정 성능
    4.3 엘리베이터 인식을 위한 센서 방향 보정 실험
5. 결 론
References

• 장민경(Mechanical Engineering, Korea University) | Min-Gyung Jang
• 조현준(Mechanical Engineering, Korea University) | Hyun-Jun Jo
• 송재복(Mechanical Engineering, Korea University) | Jae-Bok Song Corresponding author