Short-range Lidar SLAM utilizing localization data of monocular localization

Abstract

Abstract Simultaneous localization and mapping (SLAM) is a widely used technology in autonomous mobile robots, where sensors such as Lidar or cameras are typically used. Sensor fusion using multiple sensors has been employed to compensate for the shortcomings of each sensor in SLAM. However, the sensor cost cannot be ignored when considering its practical usage. Therefore, this study aims at realizing a high-precision SLAM using a sensor switching system, combining multiple low-cost sensors. The sensor switching system consists of a low-cost Lidar SLAM and a monocular localization. Since a low-cost Lidar has a short laser range, degeneracy often occurs due to the fact that they cannot capture features while building maps. The proposed system uses localization data from monocular localization to ensure precision in regions where degeneracy occurs. The proposed system was evaluated through the simulation assuming the museum environment where the degeneracy occurred. The accuracy of the robot trajectory and the built map proved the effectiveness of the proposed system.

Keywords

• SLAM
• Sensor fusion
• Calibration