# Material Identification of Scanned Objects Based on the Classification of the Laser Reflection Intensity Profile

## TL;DR

This paper introduces a new way to identify materials like glass using laser scanner data in robot navigation.

## Contribution

The novel approach uses laser reflection intensity profiles and gradients for material classification without needing multiple scans or sensors.

## Key findings

- The method successfully classifies materials including transparent glass using single-frame LiDAR data.
- Using intensity gradients improves classification accuracy in overlapping material regions.
- Experimental results show reliable performance in indoor environments.

## Abstract

This paper presents a method for material classification of objects detected by a laser scanner (LiDAR) used in autonomous mobile robot navigation. The proposed approach operates on a single-frame LiDAR scan composed of single-beam echoes and addresses materials with different reflective properties, including transparent glass surfaces. Material classification is performed by comparing measured reflection intensity profiles, defined as functions of distance and beam incidence angle, with reference profiles constructed for selected material classes. In addition to normalized reflection intensity, the gradient of the intensity profile is used to support discrimination in regions where material-dependent characteristics overlap. Experimental results obtained in indoor environments containing glass surfaces demonstrate that the proposed method enables reliable material type classification without multi-scan data accumulation or multi-sensor fusion.