When Geometry is not Enough: Using Reflector Markers in Lidar SLAM

TL;DR

This paper introduces a method to enhance lidar SLAM in environments lacking geometric features by using reflector markers, with algorithms for detection and fusion demonstrated on real industrial datasets.

Contribution

It proposes a novel approach to incorporate reflector markers into lidar SLAM, improving performance in featureless environments.

Findings

Reflector markers improve SLAM accuracy in structureless areas.

The proposed detection algorithm reliably identifies markers in real-world data.

Fusion methods enhance robustness of lidar-based localization.

Abstract

Lidar-based SLAM systems perform well in a wide range of circumstances by relying on the geometry of the environment. However, even mature and reliable approaches struggle when the environment contains structureless areas such as long hallways. To allow the use of lidar-based SLAM in such environments, we propose to add reflector markers in specific locations that would otherwise be difficult. We present an algorithm to reliably detect these markers and two approaches to fuse the detected markers with geometry-based scan matching. The performance of the proposed methods is demonstrated on real-world datasets from several industrial environments.