# RLI-SLAM: Fast Robust Ranging-LiDAR-Inertial Tightly-Coupled Localization and Mapping

## TL;DR

RLI-SLAM is a new system that combines LiDAR, inertial sensors, and ranging to enable accurate and fast robot navigation in challenging environments.

## Contribution

A novel tightly-coupled ranging-LiDAR-inertial SLAM framework with real-time distortion compensation and efficient loop closure detection.

## Key findings

- Tightly coupling UWB ranging and inertial sensors reduces drift and compensates for LiDAR distortion in real-time.
- The incremental smoothing factor graph approach improves loop closure detection and mapping precision.
- RLI-SLAM outperforms existing systems in accuracy and computational efficiency in challenging environments.

## Abstract

Simultaneous localization and mapping (SLAM) is an essential component for smart robot operations in unknown confined spaces such as indoors, tunnels and underground. This paper proposes a novel tightly-coupled ranging-LiDAR-inertial simultaneous localization and mapping framework, namely RLI-SLAM, which is designed to be high-accuracy, fast and robust in the long-term fast-motion scenario, and features two key innovations. The first one is tightly fusing the ultra-wideband (UWB) ranging and the inertial sensor to prevent the initial bias and long-term drift of the inertial sensor so that the point cloud distortion of the fast-moving LiDAR can be effectively compensated in real-time. This enables high-accuracy and robust state estimation in the long-term fast-motion scenario, even with a single ranging measurement. The second one is deploying an efficient loop closure detection module by using an incremental smoothing factor graph approach, which seamlessly integrates into the RLI-SLAM system, and enables high-precision mapping in a challenging environment. Extensive benchmark comparisons validate the superior accuracy of the proposed new state estimation and mapping framework over other state-of-the-art systems at a low computational complexity, even with a single ranging measurement and/or in a challenging environment.