Material Mapping in Unknown Environments using Tapping Sound
Shyam Sundar Kannan, Wonse Jo, Ramviyas Parasuraman, Byung-Cheol Min
Abstract
In this paper, we propose an autonomous exploration and a tapping mechanism-based material mapping system for a mobile robot in unknown environments. The goal of the proposed system is to integrate simultaneous localization and mapping (SLAM) modules and sound-based material classification to enable a mobile robot to explore an unknown environment autonomously and at the same time identify the various objects and materials in the environment. This creates a material map that localizes the various materials in the environment which has potential applications for search and rescue scenarios. A tapping mechanism and tapping audio signal processing based on machine learning techniques are exploited for a robot to identify the objects and materials. We demonstrate the proposed system through experiments using a mobile robot platform installed with Velodyne LiDAR, a linear solenoid, and microphones in an exploration-like scenario with various materials. Experiment results demonstrate that the proposed system can create useful material maps in unknown environments.
BibTeX
@inproceedings{iros2020_materialmappingi,
title = {Material Mapping in Unknown Environments using Tapping Sound},
author = {Shyam Sundar Kannan and Wonse Jo and Ramviyas Parasuraman and Byung-Cheol Min},
booktitle = {IROS 2020},
year = {2020}
}