Exploiting inaccurate a priori knowledge in robot exploration

Exploration is a task in which autonomous mobile robots incrementally discover features of interest in initially unknown environments. Most of the current exploration approaches ignore prior knowledge about the environments that have to be explored. However, in some practical cases, such knowledge could be available. In this paper, we present a method that includes a priori knowledge in an exploration strategy that selects the next best locations the robot should reach in partially explored indoor environments by exploiting the (possibly inaccurate) knowledge of theirfl oor plans.