A low cost indoor mapping robot based on TinySLAM algorithm

Zheng Gong, Jonathan Li, Wei Li

Abstract: It is important for a robot or a smart device to locate itself and create a map of its indoor environment. A number of approaches and techniques exist for indoor mapping, many of which require expensive devices and highly complex computational algorithms. In our work, we introduce a low cost robot architecture based on a cheap LiDAR system and a NVIDIA Jetson tk1 platform and perform real-time indoor mapping based on the tiny SLAM algorithm.