We examine the problem of finding a single meeting location for a group of heterogeneous autonomous mobile robots, such that the total system cost of traveling to the rendezvous is minimized. We propose two algorithms that solve this problem. The first method computes an approximate globally optimal meeting point using numerical simplex minimization. The second method is a computationally cheap heuristic that computes a local heading for each robot: by iterating this method, all robots arrive at the globally optimal location. We compare the performance of both methods to a na??ve algorithm (center of mass). Finally, we show how to extend the methods with inter-robot communication to adapt to new environmental information.