Real-time loop closure in 2D LIDAR SLAM

TLDR

Portable LIDAR SLAM efficiently acquires as‑built floor plans, and real‑time visualization helps operators assess data quality, but portable platforms must operate under limited computational resources. The study presents a backpack mapping platform that achieves real‑time 5 cm resolution mapping and loop closure. The method employs a branch‑and‑bound strategy to compute scan‑to‑submap matches as constraints for real‑time loop closure. Experimental results demonstrate that the approach is competitive with established techniques in terms of quality.

Abstract

Portable laser range-finders, further referred to as LIDAR, and simultaneous localization and mapping (SLAM) are an efficient method of acquiring as-built floor plans. Generating and visualizing floor plans in real-time helps the operator assess the quality and coverage of capture data. Building a portable capture platform necessitates operating under limited computational resources. We present the approach used in our backpack mapping platform which achieves real-time mapping and loop closure at a 5 cm resolution. To achieve realtime loop closure, we use a branch-and-bound approach for computing scan-to-submap matches as constraints. We provide experimental results and comparisons to other well known approaches which show that, in terms of quality, our approach is competitive with established techniques.