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상대속도를 고려한 포텐셜 필드 기반 군집 무인수상선의 대형 제어

A Formation Control of Swarm Unmanned Surface Vehicles Using Potential Field Considering Relative Velocity

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초록

With the advancement of autonomous navigation technology in maritime domain, there is an active research on swarming Unmanned Surface Vehicles (USVs) that can fulfill missions with low cost and high efficiency. In this study, we propose a formation control algorithm that maintains a certain shape when multiple unmanned surface vehicles operate in a swarm. In the case of swarming, individual USVs need to be able to accurately follow the target state and avoid collisions with obstacles or other vessels in the swarm. In order to generate guidance commands for swarm formation control, the potential field method has been a major focus of swarm control research, but the method using the potential field only uses the position information of obstacles or other ships, so it cannot effectively respond to moving targets and obstacles. In situations such as the formation change of a swarm of ships, the formation control is performed in a dense environment, so the position and velocity information of the target and nearby obstacles must be considered to effectively change the formation. In order to overcome these limitations, this paper applies a method that considers relative velocity to the potential field-based guidance law to improve target following and collision avoidance performance. Considering the relative velocity of the moving target, the potential field for nearby obstacles is newly defined by utilizing the concept of Velocity Obstacle (VO), and the effectiveness and efficiency of the proposed method is verified through swarm control simulation, and swarm control experiments using a small scaled unmanned surface vehicle platform.

Abstract

With the advancement of autonomous navigation technology in maritime domain, there is an active research on swarming Unmanned Surface Vehicles (USVs) that can fulfill missions with low cost and high efficiency. In this study, we propose a formation control algorithm that maintains a certain shape when multiple unmanned surface vehicles operate in a swarm. In the case of swarming, individual USVs need to be able to accurately follow the target state and avoid collisions with obstacles or other vessels in the swarm. In order to generate guidance commands for swarm formation control, the potential field method has been a major focus of swarm control research, but the method using the potential field only uses the position information of obstacles or other ships, so it cannot effectively respond to moving targets and obstacles. In situations such as the formation change of a swarm of ships, the formation control is performed in a dense environment, so the position and velocity information of the target and nearby obstacles must be considered to effectively change the formation. In order to overcome these limitations, this paper applies a method that considers relative velocity to the potential field-based guidance law to improve target following and collision avoidance performance. Considering the relative velocity of the moving target, the potential field for nearby obstacles is newly defined by utilizing the concept of Velocity Obstacle (VO), and the effectiveness and efficiency of the proposed method is verified through swarm control simulation, and swarm control experiments using a small scaled unmanned surface vehicle platform.

참고문헌 (30)

  1. Balch, T., "Behavior-based formation control for multirobot teams", IEEE transactions on robotics and automation, 14(6), pp.926~939 (1998)
  2. Barnes, L., "Unmanned ground vehicle swarm formation control using potential fields", 2007 Mediterranean Conference on Control andAutomation (2007), IEEE
  3. Barnes, L., "Swarm formation control with potential fields formed by bivariate normal functions", 2006 14th Mediterranean Conference on Control and Automation (2006), IEEE
  4. Bibuli, M., "Swarm-based path-following for cooperative unmanned surface vehicles", Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 228(2), pp.192~207 (2014)
  5. Borenstein, J., "Real-time obstacle avoidance for fast mobile robots", IEEE Transactions on systems, Man, and Cybernetics, 19(5), pp.1179~1187 (1989)
  6. Borenstein, J., "The vector field histogram-fast obstacle avoidance for mobile robots", IEEE transactions on robotics and automation, 7(3), pp.278~288 (1991)
  7. Chakravarthy, A., "Obstacle avoidance in a dynamic environment: A collision cone approach", IEEE Transactions on Systems, Man, and Cybernetics-Part A:Systems and Humans, 28(5), pp.562~574 (1998)
  8. Cui, R., "Leader –follower formation control of underactuated autonomous underwater vehicles", Ocean Engineering, 37(17-18), pp.1491~1502 (2010)
  9. Ge, S. S., "Dynamic motion planning for mobile robots using potential field method", Autonomous robots, 13(3), pp.207~222 (2002)
  10. Ghommam, J., "Adaptive leader–follower formation control of underactuated surface vessels under asymmetric range and bearing constraints", IEEE Transactions on Vehicular Technology, 67(2), pp.852~865 (2017)
  11. Chinese military innovation in artificial intelligence, "Kania, E. B.", Testimony to the US-China Economic and Security Review Commission, ~ (2019)
  12. Khatib, M., "An extended potential field approach for mobile robot sensor-based motions", Proc. International Conference on Intelligent Autonomous Systems (IAS’4) (1995)
  13. Kim, J. W., "Local path planning for autonomous vehicles based model predictive control using velocity obstacles potential field in emergency situation", M.S, pp.2020
  14. Ko, N. Y., "Avoidability measure in moving obstacle avoidance problem and its use for robot motion planning", Proceedings of IEEE, 1996, pp.3, ~
  15. Kuwata, Y., "Safe maritime autonomous navigation with COLREGS, using velocity obstacles", IEEE Journal of Oceanic Engineering, 39(1), pp.110~119 (2013)
  16. Leonard, N. E., "Virtual leaders, artificial potentials and coordinated control of groups", Proceedings of the 40th IEEE Conference on Decision and Control, pp.2968~2973 (2001), IEEE
  17. Lewis, M. A., "High precision formation control of mobile robots using virtual structures", Autonomous robots, 4(4), pp.387~403 (1997)
  18. Oh, Y. S., "Formation conatrol and obstacle avoidance of mobile robot for moving object tracking", Journal of Electrical Engineering and Technology(JEET), 60(4), pp.856~861 (2011)
  19. Park, J. H., "Obstacle avoidance of leader-follower robots based on potential field and flexible formation", The Transactions of the Korean Institute of Electrical Engineers, pp.1389~1390 (2015)
  20. Park, J. H., "Preliminary study of potential field based formation controlfor cooperative navigation of multiple autonomous surface vehicles", Institute of Control Robotics and Systems, pp.290~291 (2021)
  21. Rimon, E., "Exact robot navigation using artificial potential functions", IEEE Transactions on Robotics And Automation, 8(5), pp.501~518 (1992)
  22. Sadowska, A., "A virtual structure approach to formation control of unicycle mobile robots using mutual coupling", International Journal of Control, 84(11), pp.1886~1902 (2011)
  23. On the sea surveillance and illegal ship control by using unmanned surface vehicle swarm, "Son, N. S.", Society of Naval Architects of Korea, ~ (2020)
  24. Sonnenburg, C. R., "Modeling, identification, and control of an unmanned surface vehicle", Journal of Field Robotics, 30(3), pp.371~398 (2013)
  25. Sun, Z., "Leaderfollower formation control of underactuated surface vehicles based on sliding mode control and parameter estimation", ISA transactions, 72, pp.15~24 (2018)
  26. Tak, M. H., "Formation control algorithm for swarm robots using virtual force", The Transactions of the Korean Institute of Electrical Engineers, 63(10), pp.1428~1433 (2014)
  27. Tychonievich, L., "A maneuvering-board approach to path planning with moving obstacles", Proceedings of the 11th international joint conference on Artificial intelligence, 2, pp.1017~1021 (1989)
  28. Ulrich, I., "VFH+: Reliable obstacle avoidance for fast mobile robots", Proceedings of the 1998IEEE International Conference on Robotics and Automation, 2 (1998)
  29. Woo, J. H., "Collision avoidance for an unmanned surface vehicle using deep reinforcement learning", Ocean Eng ineering, 199, pp.107001~ (2020)
  30. Yu, Z., "Course keeping control of an autonomous boat using low cost sensors", Journal of System Design and Dynamics, 2(1), pp.389~400 (2008)

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