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Guidance and Transportation of a Target Vessel by a SWARM Unmanned Surface Vehicles (USVs)

Mohajer, Mohammad Mahdi | 2025

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 58291 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Sayyaadi, Hassan
  7. Abstract:
  8. This study presents the design and simulation of a system for guiding a target vessel using multiple autonomous tugboats (swarm tugboats). The main objective is to develop a coordinated control architecture and force allocation strategy capable of accurately guiding the target vessel along predefined reference trajectories while optimizing the interaction among the tugboats. In the initial phase, the dynamic model of the target vessel was developed based on the Newton–Euler equations. The model was validated through two approaches: (1) comparing the model’s outputs with analytical predictions derived from dynamic equations, and (2) verifying the model’s behavior against results reported in reputable sources such as data from Cybership I and II. The results demonstrated that the model possesses sufficient accuracy in predicting forces and accelerations, making it reliable for use in the control system. To control the vessel’s trajectory, a Proportional-Derivative (PD) controller was employed, operating in the inertial coordinate frame and providing stable responses under various conditions. Additionally, to enhance accuracy and mitigate noise-related errors, a Kalman Filter was used in certain scenarios for state estimation. At a higher level, a Consensus-based swarm Allocator was designed to appropriately distribute the controller’s output forces among the four tugboats. Locally, each tugboat solved a Quadratic Programming (QP) problem to convert its reference forces into actual thruster forces, taking into account constraints and thruster installation angles. The system’s performance was evaluated across various trajectories, including circular, sinusoidal, obstacle-laden, and multi-goal paths. An Artificial Potential Field (APF) algorithm was used for obstacle avoidance and intermediate target positioning. The results indicated that the designed system could accurately follow the reference paths while maintaining dynamic stability. Furthermore, the RMS error analysis between the model output and control force confirmed the accuracy of the dynamic estimation and the effectiveness of the control architecture. Finally, the system's performance in complex scenarios—such as navigating around multiple obstacles and adapting to dynamic goals—was also examined, showcasing the high adaptability and scalability of the proposed architecture. This research lays a foundation for the future development of real-world multi-agent maritime navigation systems
  9. Keywords:
  10. Consensus Algorithms ; Particles Swarm Optimization (PSO) ; Path Planning ; Obstacle Avoidance ; Optimal Force Allocation ; Marine Multiagent Control

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