Articial Potential Field (APF)-based control strategies are widely used for the safe navigation of multiple unmanned vehicles due, in part, to their relative ease of implementation and reactive nature. However, a common drawback of these methods is the equal treatment of obstacles regardless of their motion, whether they are moving closer or away, and the general assumption of vehicles and obstacles of spherical shape, which can lead to overly conservative maneuvers and trajectories. To overcome these drawbacks, this paper presents a decentralized, cooperative APF-based control strategy for an arbitrarily large number of Unmanned Underwater Vehicles (UUVs) in cluttered environments that takes into account the relative direction of motion between vehicle and obstacle as well as the non-spherical shape and relative orientation of agents, resulting in more efficient transit through narrow spaces and shorter routes. The approach achieves this by formulating the minimum safe distance as a function of the shape and relative orientation of obstacles and by modulating the distance at which a vehicle starts avoiding an obstacle based on the collision threat, increasing the reaction forces when the obstacle is fast approaching and relaxing the forces when it is moving away. The proposed framework has the added convenience of generating closed-form, continuous control input forces and torques without the need for optimization-based techniques. The stability and safety of the overall control framework are rigorously proven through Lyapunov analysis. Simulation results demonstrate that the method enables safe, cooperative navigation with lower control efforts and shorter trajectories.