ICRA 2020poster25 citations
DirtNet: Visual Dirt Detection for Autonomous Cleaning Robots
Richard Bormann, Xinjie Wang, Jiawen Xu, Joel Schmidt
Abstract
Visual dirt detection is becoming an important capability of modern professional cleaning robots both for optimizing their wet cleaning results and for facilitating demand-oriented daily vacuum cleaning. This paper presents a robust, fast, and reliable dirt and office item detection system for these tasks based on an adapted YOLOv3 framework. Its superiority over state-of-the-art dirt detection systems is demonstrated in several experiments. The paper furthermore features a dataset generator for creating any number of realistic training images from a small set of real scene, dirt, and object examples.
BibTeX
@inproceedings{icra2020_dirtnetvisualdir,
title = {DirtNet: Visual Dirt Detection for Autonomous Cleaning Robots},
author = {Richard Bormann and Xinjie Wang and Jiawen Xu and Joel Schmidt},
booktitle = {ICRA 2020},
year = {2020}
}