A potential field-based trajectory planning and tracking approach for automatic berthing and COLREGs-compliant collision avoidance

Han, Sen; Wang, Lei; Wang, Yiting

doi:10.1016/j.oceaneng.2022.112877

Cited by 19 publications

(7 citation statements)

References 47 publications

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“…To address the issue of encountering local minima, additional methods are integrated with artificial potential fields (APFs), such as in [38]. In a study based on simulation [39], in order to achieve trajectory planning in real time for automated docking, a novel method known as the 'extended dynamic window approach' is presented. This approach utilizes potential fields and incorporates a nonuniform Theta* algorithm to explore global paths while considering potential obstacle risks, thereby avoiding the possibility of being trapped in a local minimum.…”

Section: The Artificial Potential Fieldmentioning

confidence: 99%

Route Planning Algorithms for Unmanned Surface Vehicles (USVs): A Comprehensive Analysis

Hashali,

Yang,

Xiang

2024

JMSE

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This review paper provides a structured analysis of obstacle avoidance and route planning algorithms for unmanned surface vehicles (USVs) spanning both numerical simulations and real-world applications. Our investigation encompasses the development of USV route planning from the year 2000 to date, classifying it into two main categories: global and local route planning. We emphasize the necessity for future research to embrace a dual approach incorporating both simulation-based assessments and real-world field tests to comprehensively evaluate algorithmic performance across diverse scenarios. Such evaluation systems offer valuable insights into the reliability, endurance, and adaptability of these methodologies, ultimately guiding the development of algorithms tailored to specific applications and evolving demands. Furthermore, we identify the challenges to determining optimal collision avoidance methods and recognize the effectiveness of hybrid techniques in various contexts. Remarkably, artificial potential field, reinforcement learning, and fuzzy logic algorithms emerge as standout contenders for real-world applications as consistently evaluated in simulated environments. The innovation of this paper lies in its comprehensive analysis and critical evaluation of USV route planning algorithms validated in real-world scenarios. By examining algorithms across different time periods, the paper provides valuable insights into the evolution, trends, strengths, and weaknesses of USV route planning technologies. Readers will benefit from a deep understanding of the advancements made in USV route planning. This analysis serves as a road map for researchers and practitioners by furnishing insights to advance USV route planning and collision avoidance techniques.

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Section: The Artificial Potential Fieldmentioning

confidence: 99%

Route Planning Algorithms for Unmanned Surface Vehicles (USVs): A Comprehensive Analysis

Hashali,

Yang,

Xiang

2024

JMSE

View full text Add to dashboard Cite

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“…The damping matrix, denoted as D, encompasses both linear and nonlinear damping components. Detailed expressions for these matrices can be found in either Reference [35] or [24].…”

Section: Usv Hydrodynamic Modelmentioning

confidence: 99%

“…This aligns with the characteristics of MPC, which further distinguishes between linear MPC (LMPC) and nonlinear MPC (NMPC). When exploring LMPC for underactuated USV path following, the simulation results from [24,25] revealed a modest deviation between the actual and expected paths. Conversely, in a parallel study [26,27], the authors also employed LMPC, but the simulation results contrasted with those from the previous reference, demonstrating a more accurate following effect.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Linear and Nonlinear Model Predictive Control in Path Following of Underactuated Unmanned Surface Vehicles

Li,

Zhang,

Wang

et al. 2024

JMSE

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Model predictive control (MPC), an extensively developed rolling optimization control method, is widely utilized in the industrial field. While some researchers have incorporated predictive control into underactuated unmanned surface vehicles (USVs), most of these approaches rely primarily on theoretical simulation research, emphasizing simulation outcomes. A noticeable gap exists regarding whether predictive control adequately aligns with the practical application conditions of underactuated USVs, particularly in addressing real-time challenges. This paper aims to fill this void by focusing on the application of MPC in the path following of USVs. Using the hydrodynamic model of USVs, we examine the details of both linear MPC (LMPC) and nonlinear MPC (NMPC). Several different paths are designed to compare and analyze the simulation results and time consumption. To address the real-time challenges of MPC, the calculation time under different solvers, CPUs, and programming languages is detailed through simulation. The results demonstrate that NMPC exhibits superior control accuracy and real-time control potential. Finally, we introduce an enhanced A* algorithm and use it to plan a global path. NMPC is then employed to follow that path, showing its effectiveness in tracking a common path. In contrast to some literature studies using the LMPC method to control underactuated USVs, this paper presents a different viewpoint based on a large number of simulation results, suggesting that LMPC is not fit for controlling underactuated USVs.

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“…They also developed an ensemble generation method, integrating port maps with distance sensors such as LIDAR to calculate the position of safe areas in real-time, thus addressing the issue of port maps and actual environment mismatch. Han [12] proposed a potential field-based Extended Dynamic Window Approach (EDWA) to tackle the challenge of real-time trajectory planning in automatic berthing. This approach incorporates a nonuniform Theta* (NT*) for global path search, effectively avoiding local minima while considering obstacle risk.…”

Section: Double Section Bezier Curvementioning

confidence: 99%

“…Here,  denotes the increment threshold In the ACD strategy, when the initial velocity of the vessel U 0 and the propeller rotation speed n p are constant, according to the acceleration characteristics, the time t 1 required for the vessel to accelerate to the maximum velocity U con is a fixed value. Therefore, the distance S acc during the acceleration phase can be calculated by the integral formula shown in Equation (12). Similarly, based on the deceleration characteristics, the time required for the vessel to decelerate from the maximum velocity U con to U = 0 m/s, denoted as (t 3 − t 2 ), is also a fixed value.…”

Section: Velocity Matching Algorithmmentioning

confidence: 99%

Research on Ship Automatic Berthing Algorithm Based on Flow Matching and Velocity Matching

Zhang,

Zhao,

Zhang

et al. 2024

JMSE

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Addressing the automatic berthing task for vessels, this study introduces the Flow Matching Double Section Bezier Berth Method (FM-DSB) for handling downstream and upstream berthing instructions. By considering the orientation relationship between the direction of water flow and the berth, combined with berthing modes, the algorithm determines the vessel’s entry angle into the berth and plans the berthing path using double-section Bezier curves. Effective control of vessel speed post-path determination is essential. Therefore, based on the response of vessels to propeller inputs, this study introduces the Berthing Path Velocity Matching Method (BPVM). The BPVM ensures speed matching along the berthing path through analysis of vessel acceleration and deceleration capabilities. Subsequently, simulation experiments are conducted to validate the planning algorithm for both long-distance and short-distance berthing. Furthermore, the feasibility and effectiveness of the berthing path are verified using a dual-loop path tracker based on the planned results. Experimental outcomes illustrate the adaptability of the proposed algorithm in planning berthing paths that align with vessel motion characteristics, effectively guiding vessels into berths through the designed dual-loop control system.

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A potential field-based trajectory planning and tracking approach for automatic berthing and COLREGs-compliant collision avoidance

Cited by 19 publications

References 47 publications

Route Planning Algorithms for Unmanned Surface Vehicles (USVs): A Comprehensive Analysis

Route Planning Algorithms for Unmanned Surface Vehicles (USVs): A Comprehensive Analysis

Comparison of Linear and Nonlinear Model Predictive Control in Path Following of Underactuated Unmanned Surface Vehicles

Research on Ship Automatic Berthing Algorithm Based on Flow Matching and Velocity Matching

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