대한조선학회논문집 (Journal of the Society of Naval Architects of Korea)

  • 제58권2호
  • /
  • Pages.121-128
  • /
  • 2021
  • /
  • 1225-1143(pISSN)
  • /
  • 2287-7355(eISSN)
대한조선학회 (The Society of Naval Architects of Korea)
권호 표지
DOI QR코드

DOI QR Code

로봇운영체제를 이용한 보트의 자율운항 알고리즘 개발

Development of Autonomous Algorithm for Boat Using Robot Operating System

  • 조현재 (부경대학교 마린융합디자인공학과) ;
  • 김정현 (부경대학교 마린융합디자인공학과) ;
  • 김수림 (부경대학교 마린융합디자인공학과) ;
  • 우주현 (한국해양대학교 조선해양시스템공학부) ;
  • 박종용 (부경대학교 조선해양시스템공학과)
  • Jo, Hyun-Jae (Department of Marine Design Convergence Engineering, Pukyong National University) ;
  • Kim, Jung-Hyeon (Department of Marine Design Convergence Engineering, Pukyong National University) ;
  • Kim, Su-Rim (Department of Marine Design Convergence Engineering, Pukyong National University) ;
  • Woo, Ju-Hyun (Naval Architecture and Ocean Systems Engineering, Korea Maritime and Ocean University) ;
  • Park, Jong-Yong (Department of Naval Architecture and Marine System Engineering, Pukyong National University)
  • 투고 : 2020.11.16
  • 심사 : 2021.02.10
  • 발행 : 2021.04.20
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

According to the increasing interest and demand for the Autonomous Surface Vessels (ASV), the autonomous navigation system is being developed such as obstacle detection, avoidance, and path planning. In general, autonomous navigation algorithm controls the ship by detecting the obstacles with various sensors and planning path for collision avoidance. This study aims to construct and prove autonomous algorithm with integrated various sensor using the Robot Operating System (ROS). In this study, the safety zone technique was used to avoid obstacles. The safety zone was selected by an algorithm to determine an obstacle-free area using 2D LiDAR. Then, drift angle of the ship was controlled by the propulsion difference of the port and starboard side that based on PID control. The algorithm performance was verified by participating in the 2020 Korea Autonomous BOAT (KABOAT).

키워드

참고문헌

  1. Casalino, G., Turetta, A. & Simetti, E., 2009. A Three-layered architecture for real time path planning and obstacle avoidance for surveillance USVs operating in harbour fields. Oceans 2009, Bremen, Germany, pp.1-8.
  2. Fossen, T.I., 2002. Marine control systems: guidance, navigation and control of ships. Rigs and Underwater Vehicles, Marine Cybernetics.
  3. Hong, S.C., Park, I.S., Heo, J., & Choi, H.S., 2012. Indoor 3D modeling approach based on terrestrial LiDAR. Journal of the Korean Society of Civil Engineers, 32(5D), pp.527-532. https://doi.org/10.12652/Ksce.2012.32.5D.527
  4. Kuwata, Y., Wolf, M.T., Zarzhitsky, D. & Huntsberger, T.L., 2014. Safe maritime autonomous navigation with COLREGS, using velocity obstacles. IEEE Journal of Oceanic Engineering, 39, pp.110-119. https://doi.org/10.1109/JOE.2013.2254214
  5. Larson, J. et al., 2007. Autonomous navigation and obstacle avoidance for unmanned surface vehicles. Society of PhotoOptical Instrumentation Engineers (SPIE) Conference Series, pp.17-20.
  6. Polvara, R., et al., 2018. Obstacle avoidance approaches for autonomous navigation of unmanned surface vehicles. The Journal of Navigation, 71(1), pp.241-256. https://doi.org/10.1017/S0373463317000753
  7. Statheros, T., Howells, G., & McDonald-Maier, K. 2008. Autonomous ship collision avoidance navigation concepts, technologies and techniques. The Journal of Navigation, 61, pp.129-142. https://doi.org/10.1017/S037346330700447X
  8. Simmons, R. & Henriksen, L. 1996. Obstacle avoidance and safeguarding for a lunar rover. AIAAForum on Advanced Developments in Space Robotics, Madison, WI.
  9. Song, H.W., Lee, K.K., & Kim, D.H., 2019. Implementation of an obstacle avoidance system based on a low-cost LiDAR sensor for autonomous navigation of an unmanned ship. The transactions of The Korean Institute of Electrical Engineers, 68(3), pp.480-488. https://doi.org/10.5370/KIEE.2019.68.3.480