On-line Optimal information-aware path planning with actuation noise and intermittent noisy measurements

In this work, we describe some recent research activities over the last years regarding an online optimal perception- aware strategy. The goal is to reduce at runtime the estimation uncertainty by maximizing the amount of information provided by the onboard sensors in spite of not negligible Gaussian or Brownian actuation/process noise and intermittent noisy measurements (e.g. in case of on-board limited field-of-view sensors)