Research on simultaneous localization and mapping of indoor mobile robot

Simultaneous localization and mapping (SLAM) is the key technology to fulfill mobile robot obstacle avoidance and autonomous navigation. As cameras such as binocular cameras or RGB-D cameras exist wide-angle limitations, the use of such sensors prone to map mismatches and localization errors. In order to solve the aforementioned problems, 2D laser radar and odometer are used as the core sensor to design an experimental system for indoor SLAM, which is configured on a mobile robot to examine the effect of indoor SLAM. Through the Rao-Blackwellized [1] particle filter algorithm, the data of laser radar and odometer are fused with real-time processing, which realizes the construction of map as well as localization and navigation of the mobile robot in the unknown environment. Experiments on simulation and physical verification were carried out with open source robot operating system (ROS). The simulation and experimental results confirm the feasibility and practicability of the platform. (paper)