Effective collaboration of multiple vehicles has received much research attention, as advances in the operation of single unmanned systems have gradually matured for practical applications. Typically, task allocation is performed to minimize (or maximize) the expected cost (or utility), assuming that the cost matrix is constant. However, the quality of task allocation in terms of optimality and reliability may vary significantly, depending on the disturbances generated by the uncertainties of the nodes (positions of vehicles and tasks). This paper addresses the problem of multi-vehicle task allocation with consideration of node uncertainties. To assess the robustness of the solution, a combination of the interval Hungarian algorithm and the Gaussian approximation is employed. The performance of the proposed algorithm is demonstrated through numerical simulations of multi-objective (distance and robustness) task allocation.