一种结合速度控制的自主船舶靠泊实用在线轨迹规划器
A Practical and Online Trajectory Planner for Autonomous Ships' Berthing, Incorporating Speed Control
AI总结：
本研究基于低速MMG模型将自主船舶靠泊轨迹规划建模为最优控制问题，采用直接多重打靶转化为非线性规划，结合速度控制与避碰约束并用SQP算法求解，仿真验证了其在多种场景下的安全性与实时可行性。
摘要：
自主船舶本质上被设计和装备为感知其内部和外部环境，随后在无人工干预的情况下根据预定目标执行适当的行动。因此，自主靠泊的轨迹规划算法必须考虑系统动力学、船舶执行器、环境扰动以及船舶、其他船舶和港口结构的安全等因素。在本研究中，基于低速MMG模型的船舶动力学，将自主船舶的轨迹规划建模为最优控制问题（OCP），并使用直接多重打靶技术将其转化为非线性规划问题（NLP）。为了提高靠泊安全性，除了考虑风扰动外，还将速度控制、执行器限制和避碰特征作为约束纳入NLP中，随后在MATLAB中使用序列二次规划（SQP）算法对其进行求解。最后，通过以下方式评估所提出规划器的性能：与两种不同模型船舶使用CMA-ES获得的解决方案进行比较；针对不同港口入口和泊位接近场景的轨迹规划；以及使用随机生成的初始条件和港口边界内位置的可行性研究。仿真结果表明，该规划器提高了靠泊安全性，并具备实用性和计算可行性，使其适用于实时应用。
英文摘要：
Autonomous ships are essentially designed and equipped to perceive their internal and external environment and subsequently perform appropriate actions depending on the predetermined objective(s) without human intervention. Consequently, trajectory planning algorithms for autonomous berthing must consider factors such as system dynamics, ship actuators, environmental disturbances, and the safety of the ship, other ships, and port structures, among others. In this study, basing the ship dynamics on the low-speed MMG model, trajectory planning for an autonomous ship is modeled as an optimal control problem (OCP) that is transcribed into a nonlinear programming problem (NLP) using the direct multiple shooting technique. To enhance berthing safety, besides considering wind disturbances, speed control, actuators' limitations, and collision avoidance features are incorporated as constraints in the NLP, which is then solved using the Sequential Quadratic Programming (SQP) algorithm in MATLAB. Finally, the performance of the proposed planner is evaluated through (i) comparison with solutions obtained using CMA-ES for two different model ships, (ii) trajectory planning for different harbor entry and berth approach scenarios, and (iii) feasibility study using stochastically generated initial conditions and positions within the port boundaries. Simulation results indicate enhanced berthing safety as well as practical and computational feasibility making the planner suitable for real-time applications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
