Information Based Exploration with Panoramas and Angle Occupancy Grids

In this work we present a multi-robot information based exploration strategy with the goal of constructing high resolution 3D maps. We use a Cauchy-Schwarz Quadratic Mutual Information (CSQMI) based objective which operates on a novel angle enhanced occupancy grid to guide robots in the collection of RGBD panoramas, which have been shown to provide memory efficient high quality representations of space. To intelligently collect panoramas, we introduce the angle enhanced occupancy grid which emphasizes perspective in addition to coverage, a characteristic we believe results in the construction of higher quality maps than traditional occupancy grid methods. To show this, we conduct simulations and compare our approach with frontier exploration. Using our angle enhanced occupancy grid, only 11.4% of decimeter wall segments were covered by fewer than 20 pixels as compared with 33.5% for the frontier method.