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We consider the problem of exploring an unknown environment with a pair of mobile robots. The goal is to make the robots meet (or rendezvous) in minimum time such that there is a maximum speed gain of the exploration task. The key challenge in achieving this goal is to rendezvous with the least possible dependency on communication. This single constraint involves several sub-problems: finding unique potential rendezvous locations in the environment, ranking these locations based on their uniqueness and synchronizing with the other robot to meet at one of the locations at a scheduled time. In addition, these tasks are to be performed simultaneously while exploring and mapping the environment. We propose an approach for efficiently combining the exploration and rendezvous tasks by considering the cost of reaching a rendezvous location and the reward of its uniqueness. This cost and reward model is combined with a set of deterministic and probabilistic rendezvous strategies for the robots to meet during exploration. Experimental results suggest that the joint tasks of exploration and rendezvous are substantially improved by ranking the potential rendezvous locations based on the combined cost-reward criterion when compared to the ranking solely based on the uniqueness of the location.