In this paper, we introduce a target position reasoning system based on Bayesian network that selects destinations of robots on a map to explore compound disaster environments. Compound disaster accidents have hazardous conditions because of a low visibility and a high temperature. Before firefighters enter the environment, the robots notify information in advance, such as victim’s positions, number of victims, and status of debris of building. The problem of the previous system is that the system requires a target position to operate the robots and the firefighter need to learn how to use the robot. However, selecting the target position is not easy because of the information gap between eyewitness accounts and map coordinates. In addition, learning the technique how to use the robots needs a lot of time and money. The proposed system infers the target area using Bayesian network and selects proper x, y coordinates on the map based on image processing methods of the map. To verify the proposed system, we designed three example scenarios based on eyewetinees testimonies and compared time consumption between human and the system. In addition, we evaluate the system usability by 40 subjects.

Abstract
 1. 서 론
 2. 관련 연구
  2.1 재난 대응 로봇
  2.2 베이지안 네트워크
 3. 목표 지점 추론 시스템
  3.1 전체 시스템 구성
  3.2 목표지점 추론 베이지안 네트워크 설계
  3.3 지도 정보의 지식표현
 4. 실험 및 결과
  4.1 네트워크 추론 및 좌표 설정 소요 시간 비교
  4.2 시스템 유용성 평가
 5. 결론 및 향후 연구
 References

• 양견모(KIRO, Pohang) | Kyon-Mo Yang
• 서갑호(KIRO, Pohang) | Kap-Ho Seo
• 이종일(KIRO, Pohang) | Jongil Lee
• 이석재(KIRO, Pohang) | Seokjae Lee
• 서진호(Dept. of Mechanical System Eng., Pukyong National University) | Jinho Suh Corresponding author