Estimating the Localizability in Tunnel-like Environments using LiDAR and UWB

The application of robots in inspection tasks has been growing quickly thanks to the advancements in autonomous navigation technology, especially the robot localization techniques in GPS-denied environments. Although many methods have been proposed to localize a robot using onboard sensors such as cameras and LiDARs, achieving robust localization in geometrically degenerated environments, e.g. tunnels, remains a challenging problem. In this work, we focus on the robust localization problem in such situations. A novel degeneration characterization model is presented to estimate the localizability at a given location in the prior map. And the localizability of a LiDAR and an Ultra-Wideband (UWB) ranging radio is analyzed. Additionally, a probabilistic sensor fusion method is developed to combine IMU, LiDAR and the UWB. Experiment results show that this method allows for robust localization inside a long straight tunnel.

I. Introduction

In this work, we aim to address the robust localization problem in robot-based tunnel inspection tasks. Compared with traditional human-based approaches, robots are more flexible and efficient in that they do not require specialized tools to gain mobility, and are able to access places that are dangerous for humans. Recent advancements in robot sensing and autonomous navigation have significantly increased the usage of robots in such applications. However, as one of the most fundamental problems, localizing a robot inside long straight tunnels remains challenging even for the state-of-the-art methods. Reasons for localization failure include darkness, dust, ambiguity and so on. Here we focus on the ambiguity issue faced by most LiDAR-based systems.