This article deals with underwater gliders whether there are operated in a fleet or individually. They constitute the most affordable and energy-saving autonomous observation/data acquisition platform, making long-duration ocean exploration missions possible. In this article, theoretical researches are led to solve the path planning problem of multi-point exploration missions of this type of vehicle. We focus on the area coverage type missions i.e. all points of a given area must be visited only once. We suggest a new path planning method for area coverage i.e. the fleet of glider is sized and the optimized glider trajectories are calculated according to selected criteria (mission duration, energy consumption or travelled distance). Our proposed approach combines weighted graph theory with our underwater glider simulator whose main interest is to be capable of integrating time-varying 3D environmental data (4D). Our method is tested in simulation and then in a dynamic real-life context (Mediterranean Sea) on Alseamar’s SeaExplorer autonomous underwater gliders. Finally, a comparison with the expertise of a glider pilot and a more conventional approach, exploiting only the distance between the waypoints in the operation area, confirms the relevance and effectiveness of the suggested method. The experimental mission demonstrates the interest and benefits of the approach and the ease of operational implementation in an industrial context.