A Triangle Feature Based Map-to-map Matching and Loop Closure for 2D Graph SLAM

Abstract

The loop closure problem in 2D LiDAR simultaneous localization and mapping (SLAM) is interesting yet to be solved efficiently, as it suffers from a lack of information in 2D laser rangefinder readings. For this reason, we compare two grid submaps, where features and constraints are enriched, to find loops. We propose a geometric environment descriptor called a Triangle Feature (TF). It exploits the Euclidean distance constraint any three feature points in a submap can form. A 2D graph SLAM system using TF to close loops is also developed. The global maps we build outperform some popular open-source SLAM solutions, and the system can run up to 2.4 times of real-time in our experiments.