In this paper, we present a novel resource-allocation problem formulation for vision-aided inertial navigation systems (VINS) for efficiently localizing micro aerial vehicles equipped with two cameras pointing at different directions. Specifically, based on the quadrotor's current speed and median distances to the features, the proposed algorithm efficiently distributes processing resources between the two cameras by maximizing the expected information gain from their observations. Experiments confirm that our resource-allocation scheme outperforms alternative naive approaches in achieving significantly higher VINS positioning accuracy when tested onboard quadrotors with severely limited processing resources.
