Indoor SLAM Algorithm Based on PL-ICP and Map Matching

Abstract

ICP is a common algorithm for indoor mapping of mobile robots, which completes the process of robot positioning and mapping by constantly matching adjacent scans. Pl-ICP is an optimized version of ICP, which can achieve faster convergence speed and higher accuracy than ordinary ICP. But whether it is ICP or PL-ICP, because the position of the new scan is only related to the previous scan, errors will continue to accumulate, thereby reducing the quality of the final map. This paper proposes a map-matching algorithm based on PL-ICP and TSDF. By extracting the point cloud from the TSDF grid map, the new scan of the laser can be matched with a high-quality TSDF map, so as to solve the problem of error accumulation in PL-ICP. The experiment will be divided into two parts: simulation and real environment. The experiments in these two parts prove the effectiveness of the algorithm in this paper.