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Study on the Shortest Path finding of Engine Room Patrol Robots Using the A* Algorithm

A* 알고리즘을 이용한 기관실 순찰로봇의 최단 경로 탐색에 관한 연구

  • Kim, Seon-Deok (Division of Marine Engineering, Mokpo National Maritime University)
  • 김선덕 (목포해양대학교 기관시스템공학부)
  • Received : 2022.01.27
  • Accepted : 2022.04.27
  • Published : 2022.04.30

Abstract

Smart ships related studies are being conducted in various fields owing to the development of technology, and an engine room patrol robot that can patrol the unmanned engine room is one such study. A patrol robot moves around the engine room based on the information learned through artificial intelligence and checks the machine normality and occurrence of abnormalities such as water leakage, oil leakage, and fire. Study on engine room patrol robots is mainly conducted on machine detection using artificial intelligence, however study on movement and control is insufficient. This causes a problem in that even if a patrol robot detects an object, there is no way to move to the detected object. To secure maneuverability to quickly identify the presence of abnormality in the engine room, this study experimented with whether a patrol robot can determine the shortest path by applying the A* algorithm. Data were obtained by driving a small car equipped with LiDAR in the ship engine room and creating a map by mapping the obtained data with SLAM(Simultaneous Localization And Mapping). The starting point and arrival point of the patrol robot were set on the map, and the A* algorithm was applied to determine whether the shortest path from the starting point to the arrival point was found. Simulation confirmed that the shortest route was well searched while avoiding obstacles from the starting point to the arrival point on the map. Applying this to the engine room patrol robot is believed to help improve ship safety.

기술의 발전으로 스마트 선박과 관련된 다양한 연구가 진행되고 있으며, 기관실을 무인으로 순찰할 수 있는 기관실 순찰 로봇도 이러한 연구 중의 하나이다. 순찰로봇은 인공지능을 통해 학습된 정보를 기반으로 기관실을 이동하며 기기 정상 유무 및 누수, 누유, 화재 등의 이상 유무를 파악한다. 기관실 순찰로봇에 관한 연구는 인공지능을 이용한 객체 검출에 관한 연구가 주로 진행되고 있으나, 순찰로봇의 이동 및 제어에 관한 연구는 부족한 상황이다. 이는 순찰로봇이 객체를 검출하더라도 검출한 객체까지 이동할 방법이 없다는 문제를 야기한다. 이에 본 논문에서는 기관실 이상상황 발생 시 빠르게 이상 유무를 파악할 수 있는 기동성을 확보하기 위해, A* 알고리즘을 적용하여 순찰로봇이 최단경로를 탐색할 수 있는지를 확인하였다. 라이다를 장착한 소형차를 이용하여 선박 기관실을 주행하며 데이터를 얻어, SLAM으로 매핑하여 지도를 만들었다. 매핑한 지도에서 순찰로봇의 출발 지점과 목표 지점을 설정하고, A* 알고리즘을 적용하여 출발 지점부터 목표 지점까지 최단 경로를 탐색하는지를 확인하였다. 시뮬레이션 결과 매핑된 지도에서 출발 지점부터 목표 지점까지의 장애물을 회피하며 최단 경로를 잘 탐색함을 확인 할 수 있었으며, 기관실 순찰로봇에 적용하면 선박안전에 도움이 될 것으로 사료된다.

Keywords

References

  1. Bailey, T. and H. Durrant-Whyte(2006), Simultaneous localization and mapping (SLAM): part II. IEEE Robotics & Automation Magazine, 13(3), pp. 108-117. https://doi.org/10.1109/MRA.2006.1678144
  2. Cho, M. W. and B. W. Lee(2021), Comparison of A* algorithm and reinforcement learning for finding optimal paths with dynamic change of an obstacle position in a GridWorld environment, The Institute of Electronics and Information Engineers, pp. 1592-1594.
  3. Durrant-Whyte, H. and T. Bailey(2006), Simultaneous localization and mapping: part I, IEEE Robotics & Automation Magazine, 13(2), pp. 99-110. https://doi.org/10.1109/MRA.2006.1638022
  4. Jeon, S. W., D. W. Shin, S. H. Yu, J. Y. Lee, and H. K. Jung(2021), Guide to evacuation based on A* algorithm for the shortest route search in case of fire system, The Korea Institute of Information and Communication Engineering, pp. 260-262.
  5. Kim, S. H., J. M. Sim, Y. S. Park, and D. H. Jung(2021), LiDAR-Based Smart Logistics Robot, Proceedings of Symposiuym of the Korean Institute of communications and Information Sciences, pp. 995-996.
  6. Park, K. M.(2021), Machine Classification in Ship Engine Rooms Using Transfer Learning, The Korean Society of Machine Environment & Safety, Vol. 27(2), pp. 363-368. https://doi.org/10.7837/kosomes.2021.27.2.363
  7. Pyo, Y. S.(2015), ROS Robot Programming, Ruby Paper, ISBN: 979-11-951492-7-8, pp. 311-316.
  8. Qi, J., J. Zhang, and Q. Meng(2021), Auxiliary Equipment Detection in Marine Engine Rooms Based on Deep Learing Model. Journal of Marine Science and Engineering.
  9. Qi, J., J. Zhang, Q. Meng, J. Ju, and H. Jiang(2022), Detection of Auxiliary Equipment in Engine Room Based on Improved SSD, Journal of Physics: Conference Series, Volume 2173, 3rd International Conference on Modeling, Simulation, Optimization and Algorithm (ICMSOA 2021).
  10. Seo, C. H., Y. J. Noh, and Misganaw Abebe Baye(2020), Ship Collision Avoidance with Improved A* Algorithm, pp. 1262-1263.
  11. Thrun, S., W. Burgard, and D. Fox(2006), Probabilistic Robotics, Acorn, ISBN: 979-11-6175-407-9, pp. 140-160.