Abstract
Autonomous navigation algorithms for mobile robots are widely used. At present, the mainstream civil indoor mobile robot autonomous navigation algorithms are using low cost 2D LiDAR, which obtains less environmental information. In this paper, a lower-cost binocular camera and 2D LiDAR are used as sensors to obtain more environmental information. Firstly, the binocular camera is calibrated and fitted with depth error. Secondly, the 3D information of the binocular camera is intercepted and projected to obtain two-bit point cloud data. Finally, the processed 2D camera point cloud data is fitted with the LiDAR point cloud for interpolation, and the fused 2D point cloud is obtained for autonomous robot navigation. The experimental verification can determine that this algorithm has significantly improved the autonomous navigation effect compared to using 2D LiDAR alone.