An effective approach for indoor mobile robot SLAM with multi-sensor fusion

Abstract

With the rapid development of mobile service robot industry, its application scenarios have become more complex and diverse. SLAM (Simultaneous Localization and Mapping) with a single sensor is difficult to meet the application requirements. Multisensor fusion for accurate positioning and mapping navigation has become one of the research hotspots in this field. In order to solve the problem of single sensor simultaneous localization and map construction in indoor small environment, the contour is fuzzy and the effect is not ideal. Based on ORB-SLAM2 fusion and improved Gmapping algorithm, this paper proposes a multi-sensor real-time localization mapping scheme based on laser radar and vision fusion. This algorithm combines the visual information provided by the depth camera and the scanning frame provided by the laser radar to make up for the shortcomings of a single sensor and form a real-time positioning and map building system with higher robustness. The experimental results show that the integrated SLAM scheme can obtain a more comprehensive and accurate map, which meets the expected design requirements.