Collision avoidance is a priority task for ensuring the safety of a maritime transportation system. However, for a ship towing system, which is characterized by multiple vessels and physical connections, the research works about collision avoidance is limited. Thus, this paper proposes a speed and heading control-based conflict resolution of a ship towing system for collision avoidance. Two systems compose the core of the proposed conflict resolution: the risk assessment system and the coordination control system. The risk assessment is to identify the conflict and determine the time of avoiding action by calculating the index of conflict and the available maneuvering margin. The coordination control is based on the model predictive control (MPC) strategy to cooperatively control two tugboats for regulating the position, heading, and speed of the manipulated ship. Simulation experiments show that according to the index of conflict, the time cost, and the fuel consumption, a selected operation of combined heading and speed can be recommended for a ship towing system to provide a safer and more efficient towage manipulation.

The regulatory endorsement of the International Maritime Organization (IMO) and the support of pivotal shipping market players in recent years motivate the investigation of the potential role that autonomous vessels play in the shipping industry. As the complexity and scale of the envisioned applications increase, research works gradually transform the focus from single-vessel systems to multi-vessel systems. Thus, autonomous multi-vessel systems applied in the shipping industry are becoming a promising research direction. One of the typical research directions is floating object manipulation by multiple tugboats. This paper offers a comprehensive literature review of the existing research on floating object manipulation by autonomous multi-vessel systems. Based on the prior knowledge of object manipulation problems in multi-robot systems, four typical ways of maritime object manipulation are summarized: attaching, caging, pushing, and towing. The advantages and disadvantages of each manipulation way are discussed, including its typical floating object and application scenarios. Moreover, the aspects of control objective, control architecture, collision avoidance operation, disturbances consideration, and role of each involved vessel are analyzed for gaining insight into the approaches for solving these problems. Finally, challenges and future directions are highlighted to give possible inspiration.

Transportation of a large offshore platform from inland waters to the open sea is a hazardous and challenging mission. With the development of the autonomous surface vessel (ASV), the problem of large floating object transportation has a chance to be solved by applying multiple physical-connected autonomous tugboats. This article proposes a distributed dynamic coordination control scheme for a multivessel autonomous towing system to transport an offshore platform under environmental disturbances. Where the dynamic coordination decision mechanism is based on the relative position of the two neighbor waypoints, the controllers are designed based on the multilayer model-predictive control (MPC) strategy with several specific cost functions, and the distributed control architecture is built based on the alternating direction method of multipliers (ADMM) with augmented Lagrangian function. The simulation experiment indicates that the proposed control scheme can achieve better consensus for the distributed control architecture accomplishment and more efficiently transport an offshore platform under environmental disturbances.

This paper proposes a distributed control scheme for autonomous tugboats to tow a ship in a restricted water traffic environment ensuring collision avoidance while being compliant with maritime regulation called COLREGS. The complex problem is cooperatively solved by addressing three sub-optimization problems. The first is to optimize the towing forces and angles for solving ship waypoint following and collision avoidance problems. The second is to optimize the tug thruster forces and moment for solving the tug online trajectory tracking and collision avoidance problems. The third is to optimize the Lagrange Multipliers for solving the consensus problem between the ship and tugs. The distributed control architecture follows the Model Predictive Control (MPC) strategy using the Altering Direction Method of Multipliers (ADMM). Simulation experiments indicate that the proposed control scheme can deal with static and dynamic obstacles in restricted waterways for a physically interconnected multi-vessel system executing the towing process, and the collision avoidance complies with COLREGS rules.

Towing operations are highly reliant on the experience of the towing operators. Safety concerns arise when towing operations are subjected to environmental disturbances and dynamic traffic conditions. However, a systematic framework and approaches to enhance the safety and automation of towing operations remain lacking. This work proposes a framework of collision prevention of ship towing operations under environmental disturbance in near port waters. The focus is to prevent internal collisions between tug and assisted ship and provide early warning of possible collisions with other surrounding ships. A cooperative multi-agent control strategy is employed to specify the direction and magnitude of the towing force of the two tugs in real-time. Therefore, in the presence of environmental disturbance, the assisted ship can sail along the planned trajectory, and the acceptable safe geometric distance between each ship pair in the towing system is guaranteed. Further, a COLREGs-compliant collision alert system is designed to promptly remind the towing operators of a collision hazard with nearby ships, and different alert levels indicate different action obligations of towing operators. This proposed framework and developed methods are applied to a tandem towing system consisting of two tugs and one assisted ship to test its feasibility.

This paper proposes a novel dynamic coordination control scheme for a physically connected multi-vessel towing system to transport an offshore platform. The transportation process is executed by four tugboats, and each of them has a leading or following role. To render the transportation faster, the roles of the tugboats can be switched in the towing process. The dynamic coordination decision mechanism is designed to allocate in real-time a combination of roles to the tugs by comparing the position and heading of the offshore platform to the next waypoint position. A control allocation strategy is developed to optimally control the position and heading of the tugboats considering multiple constraints. The reference trajectory of the tugboats is dynamically calculated based on the assigned role of each tugboat. A simulation experiment indicates that the proposed control scheme can enhance the maneuver-ability of the physically connected multi-vessel towing system and increase the efficiency of offshore platform transportation.

This paper proposes a multi-agent control scheme for multiple physically interconnected tugboats performing a ship towing process. These tugs are coordinated by two control layers. In the higher layer, the supervisory controller outputs the desired towing forces and reference trajectories for the tugs. This information is used by a tug's local controller in the lower layer to calculate the thruster forces and moment for manipulating the ship. The control strategy is based on the model predictive control concept, with the performance function designed by using the position and velocity error to make the ship follow waypoints and speed profile. A distributed control architecture is designed based on the alternating direction method of multipliers (ADMM) to reach a consensus between the predicted position generated by the tug controllers and the reference trajectory generated by the supervisory controller. Simulation experiments illustrate that the proposed method ensures the smooth and efficient maneuverability of the towing process.

This paper investigates the motion-planning problem for an unmanned surface vehicle (USV), in which the goal is to find the shortest search time, the shortest path in navigational waters, all subject to collision avoidance and USV dynamics constraints. A new motion-planning method is proposed, based on topological position relationships (TPR), to achieve this solution. Firstly, the TPR of the obstacles and the USV are constructed, based on the spatial distribution of the obstacles. This gives an overall topological navigation map, which is different from the usual grid-based map. Secondly, a numerical model of unit decomposition is built to constrain the dynamics of the USV, so that the motion of the USV better fits the exact situation. Motion planning in this study is achieved by combining the topological navigation map and a numerical model of the USV. Finally, Numerical simulations and field tests verify the effectiveness of our formulated model and proposed algorithm.

The maneuvering characteristics of the unmanned surface vehicle itself are very important to motion planning due to the limited water scale area. If the size, motion state, and maneuvering characteristics of the unmanned surface vehicle are not considered, the shortest path obtained is actually not feasible in the restricted waters. In this article, the widely used A* algorithm is improved by accounting for the maneuvering characteristics of the unmanned surface vehicle, named as the Label-A* Algorithm, which is further employed to fix the problem related to the motion planning for the unmanned surface vehicle in restricted waters. The solution to the motion planning mainly contains three stages. First, the unmanned surface vehicle trajectory unit library is established based on its maneuvering characteristics; second, an improved label-A* Algorithm is constructed, and the unmanned surface vehicle motion planning method is proposed with the trajectory unit, which is suitable for the restricted waters; Finally, numerical simulations and filed tests are designed to verify the formulated model and proposed algorithm. The motion planning method can simultaneously meet the state constraints, maneuvering characteristics constraints, and water scale constraints of unmanned surface vehicle.

The essence of the path planning problems is multi-modality constraint. However, most of the current literature has not mentioned this issue. This paper introduces the research progress of path planning based on the multi-modality constraint. The path planning of multi-modality constraint research can be classified into three stages in terms of its basic ingredients (such as shape, kinematics and dynamics et al.): Route Planning, Trajectory Planning and Motion Planning. It then reviews the research methods and classical algorithms, especially those applied to the Unmanned Surface Vehicle (USV) in every stage. Finally, the paper points out some existing problems in every stage and suggestions for future research.