Localizability-based Topological Local Object Occupancy Map for Homing Navigation

摘要

In this paper, we proposed a localizability-based topological local object occupancy map (TLO2M) for homing navigation. The proposed approach is a combination of topological and metric map representations. We utilize object detection to advance the occupancy grid map and train a structural localizability measuring network with it. As a result, the TLO2M is built based on structural localizability and feature similarity. The proposed method shows a 0.955 success rate of the homing task at the Gibson environments.