Indoor Semantic Map Building for Robot Navigation

Abstract

This paper proposes a method to build a semantic map for robot navigation by using a laser sensor and monocular vision. Laser data is used to construct an environmental grid map, which can guide the robot forward without collision. In this paper, we assume the indoor environment is one of the floors of the building. By using the monocular vision, the mobile robot can automatically search the doorplate of each office room and recognize the room number, which is used as an environmental semantic identifier. We assign the semantic label to the grid map so that the constructed map includes not only the spatial information but also the semantic information. The robot traverses the target floor and completes the construction of the semantic map automatically. The experimental result has shown the robot can be navigated to any given address in the target floor to complete the visit task by using our proposed semantic map.