Improving Gridmap with Semantic Information

Abstract

Grid-maps are often used by autonomous robots to navigate in environment. However, grid-maps have a limitation that they only contain information about free space and obstacles in the map. They do not contain semantic information about the obstacles and the place. Semantic SLAM has been proposed to solve this problem. However, sometimes, replacing the existing grid-map by a semantic map is not feasible as it requires changing the underlying localization and navigation module. To this end, in this paper, a method to embed semantic information in existing grid-map is proposed. The algorithm can use a monocular camera and embed semantic information in the grid-map. The results are evaluated in a simulation based environment.