Optimizing Inspection Planning Under Localization Uncertainty for Autonomous Robots

The core message of this article is to present IRIS-U2, the first algorithm for offline inspection planning that systematically accounts for execution uncertainty, combining the capabilities of the efficient IRIS algorithm for deterministic inspection planning with Monte Carlo sampling to reason about uncertainty via POI inspection probabilities.