DuLoc: Life-Long Dual-Layer Localization in Changing and Dynamic Expansive Scenarios

TL;DR

DuLoc is a robust LiDAR-inertial localization system that effectively handles environmental changes and long-term dynamics by integrating global maps with real-time local data, validated through extensive real-world experiments.

Contribution

This paper introduces DuLoc, a novel localization framework combining LiDAR-inertial odometry with offline maps and a motion model to improve robustness in dynamic environments.

Findings

Outperforms state-of-the-art LiDAR localization systems in large-scale outdoor scenarios.

Demonstrates robustness over 2,856 hours of real-world data across 32 vehicles.

Effective in unbounded, changing environments with environmental dynamics.

Abstract

LiDAR-based localization serves as a critical component in autonomous systems, yet existing approaches face persistent challenges in balancing repeatability, accuracy, and environmental adaptability. Traditional point cloud registration methods relying solely on offline maps often exhibit limited robustness against long-term environmental changes, leading to localization drift and reliability degradation in dynamic real-world scenarios. To address these challenges, this paper proposes DuLoc, a robust and accurate localization method that tightly couples LiDAR-inertial odometry with offline map-based localization, incorporating a constant-velocity motion model to mitigate outlier noise in real-world scenarios. Specifically, we develop a LiDAR-based localization framework that seamlessly integrates a prior global map with dynamic real-time local maps, enabling robust localization in unbounded and changing environments. Extensive real-world experiments in ultra unbounded port that involve 2,856 hours of operational data across 32 Intelligent Guided Vehicles (IGVs) are conducted and reported in this study. The results attained demonstrate that our system outperforms other state-of-the-art LiDAR localization systems in large-scale changing outdoor environments.