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In this paper, a system architecture to provide end-to-end network connectivity for autonomous teams of robots is discussed. The core of the proposed system is a cyber-physical controller whose goal is to ensure network connectivity as robots move to accomplish their assigned tasks. Due to channel quality uncertainties inherent to wireless propagation, we adopt a stochastic model where achievable rates are modeled as random variables. The cyber component of the controller determines routing variables that maximize the probability of having a connected network for given positions. The physical component determines feasible robot trajectories that are restricted to safe configurations which ensure these probabilities stay above a minimum reliability level. Local trajectory planning algorithms are proposed for simple environments and leveraged to obtain global planning algorithms to handle complex surroundings. The resulting integrated controllers are robust in that end-to-end communication survives with high probability even if individual point-to-point links are likely to fail with significant probability. Experiments demonstrate that the global planning algorithm succeeds in navigating a complex environment while ensuring that end-to-end communication rates meet or exceed prescribed values within a target failure tolerance.