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This paper presents the development of a path-planning algorithm for Unmanned Aerial Vehicles (UAVs) in order to increase the situational awareness for platooning vehicles. The scenario considers a team of cooperative UAVs, initially docked on moving Unmanned Ground Vehicles (UGVs). In particular, the goal consists in finding the best routing plan for the UAVs in order to visit some designated targets in a wide search area to augment the UGVs’ situational awareness. Taking into account the maximal endurance constraint of the UAVs, this problem becomes equivalent to a time-constrained multiple depot vehicle routing problem with moving depots. To tackle this variant of the well-known vehicle routing problem, a methodology based on a TABU search meta-heuristic is implemented. While respecting the endurance constraint, this methodology tempts to optimize multiple objectives: the number of UAVs required, the total length of the routing and the balance of the lengths of the different routes within the routing plan. The proposed approach based on a meta-heuristic gives relevant results in a relatively short period of time.