This study focuses on autonomous exploration based on map expansion for an underwater robot equipped with acoustic sonars. Map expansion is applicable to large-area mapping, but it may affect localization accuracy. Thus, as the key contribution of this paper, we propose a method for underwater autonomous exploration wherein the robot determines the trade-off between map expansion ratio and position accuracy, selects which of the two has higher priority, and then moves to a mission step. An occupancy grid map is synthesized by utilizing the measurements of an acoustic range sonar that determines the probability of occupancy. This information is then used to determine a path to the frontier, which becomes the new search point. During area searching and map building, the robot revisits artificial landmarks to improve its position accuracy as based on imaging sonar-based recognition and EKF-SLAM if the position accuracy is above the predetermined threshold. Additionally, real-time experiments were conducted by using an underwater robot, yShark, to validate the proposed method, and the analysis of the results is discussed herein.

Abstract
 1. 서 론
 2. 수중로봇 자율탐사
 3. 자율탐사 요소기술
  3.1 환경 인지
  3.2 확장형 칼만 필터 기반 SLAM
  3.3 지도 확장
  3.4 경로 생성
 4. 검증 실험
  4.1 수중로봇의 지도 확장 실험
   4.1.1 실험 환경 및 내용
   4.1.2 실험 결과
  4.2 수중로봇의 지도 확장 및 위치 보정 실험
   4.2.1 실험 환경 및 내용
   4.2.2 실험 결과
 5. 결 론
 References

• 이영준(KRISO, Daejeon, Korea) | Yeongjun Lee
• 최진우(KRISO, Daejeon, Korea) | Jinwoo Choi
• 이윤건(KRISO, Daejeon, Korea) | Yoongeon Lee
• 최현택(Marine Robotics Research Division, KRISO) | Hyun-Taek Choi Corresponding author