## 1 Introduction
In their work, the authors consider the moving dock to be in the mid-water column (i.e., in the free space). However, if the dock is close to the seafloor, the terrain may not be smooth. As the vehicle approaches for docking in such scenarios, it could have unwanted collisions with the seafloor while attempting the docking maneuver. The work in [33] discusses the docking of ASVs into a large mother ship by placing a virtual target to a point positioned at the projection of the ASV position onto a safety circle surrounding the mother ship. This virtual target point can move along the safety circle until its bearing matches up with that of the desired docking point. Once the ASV matches its position and velocity with this virtual target point, the target point starts reducing its distance from the dock by translating, until it becomes equal to that of the docking point. However, the fully translation maneuver presented in the homing and docking stages will be difficult to achieve due to the drag, presence of water currents, and high energy requirements. Coming further, a robust guidance system can be identified as a core and crucial component for ensuring successful autonomous operations. For executing certain maneuvers close to the seafloor or near structures, underwater vehicles would require sophisticated control systems to guide the vehicle around obstacles, maintain a certain altitude or depth, all in the possible presence of ocean currents. Another interesting fact is that the previously discussed techniques take only a specific type of behavior into account. Those techniques do not incorporate diverse behaviors, ranging from the execution of the main tasks of the mission (e.g., surveying an area, structure, etc. ), to homing and docking at the end of the mission. For systems such as industrial and residential applications where the automatic procedures are important, it will be desirable to have a fully fledged control framework to solve all different control problems. Due to this increase in the capabilities assigned to the vehicle, there is a transition observed with the use of a unified guidance and control framework. The task priority framework [34; 35; 36; 37; 38] is flexible and can accommodate various tasks and operations that are required, favoring a priority-based systematic execution of tasks. Not only does it provide a unified approach, but also a systematic control that will, if required, take into account additional features such as physical/operational constraints of the vehicle (e.g., vehicle under-actuation), safety limits (e.g., maintaining a safe distance from dock to avoid collision), constraints in approach (e.g., docking from stern), and energy expenditure (e.g., minimize drag by exploiting translation only when necessary), to name but a few. A priority-based control to integrate inequality control objectives and task transitions is presented in [39], displaying how inequality control objectives could be well defined within the task priority framework without causing any discontinuities. This was further expanded in the MARIS, DexROV, and ROBUST projects [40; 41; 42; 43]. The work in [44] shows the capabilities of the task priority framework in the cooperative control of multiple underwater manipulators where a cooperative transportation scenario is considered (the same strategy has been demonstrated with ground mobile manipulators showing experimental results in [45]). Inspired from these literatures, a task priority control framework is used as the control framework for our research. Various tasks are defined in the framework where they are achieved in the order of priority. Thanks to the flexibility in incorporating various tasks, it is now easier to expand the capabilities of our controller. This paper contributes by focusing on a general control strategy, proposing a unified AUV guidance and control based on the task priority control framework and improving the previously discussed literature as explained further.