Research on Laser Radar Indoor Positioning

Abstract

Single-line laser radar has been widely used in indoor positioning. The existing SLAM is restricted by algorithm complexity, scene and other factors. In view of this, this paper studies the comparative study of hardware and power consumption of the four existing SLAM algorithms, namely, Gmapping, Hector, Karto and Cartographer. A smart car based on Cortex-A53 raspberry board is built to realize the composition and positioning function of SLAM algorithm. Using Gmapping, Hector, Karto, Cartographer four algorithms for indoor environment lobby, corridor, classroom, laboratory monocular radar SLAM scanning mapping, monitoring its voltage, current changes, composition speed three parameters. The results show that in the case of corridor, Gmapping algorithm is the optimal choice; in the case of hall composition, Gmapping algorithm is the optimal choice; in the case of classroom composition, Cartographer algorithm is the best choice; in conventional laboratory conditions, Gmapping algorithm is the best choice.