Multi-stage Path Planning Strategy for Intelligent Cleaning Robot

Xingxing Cheng, Xianfeng Ding, Chia Tungom, Ji Yuan

2022

Abstract

The clearance of public garbage is a challenging case in artificial intelligence implementation. The difficulty is how to recognize the public garbage and make path planning. In comparison with Traditional Path Planning (TPP) architecture, we utilized a method of Multi-stage Path Planning for garbage clearance to improve the accuracy and speed of TPP architecture. Within this paper, the original public video frames are taken as input and the garbage is separated into several classes by Yolov5. Its location is estimated by the location of the camera. Taking the garbage class and location as input, the path planning is calculated by an improved Multi-stage Deep Deterministic Policy Gradient (MDDPG). Our novel architecture was trained and tested using videos from a real community place and achieved ideal effects.

Paper Citation

in Harvard Style

Cheng X., Ding X., Tungom C. and Yuan J. (2022). Multi-stage Path Planning Strategy for Intelligent Cleaning Robot. In Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC; ISBN 978-989-758-622-4, SciTePress, pages 757-765. DOI: 10.5220/0012046400003612

in Bibtex Style

@conference{isaic22,
author={Xingxing Cheng and Xianfeng Ding and Chia Tungom and Ji Yuan},
title={Multi-stage Path Planning Strategy for Intelligent Cleaning Robot},
booktitle={Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC},
year={2022},
pages={757-765},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012046400003612},
isbn={978-989-758-622-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC
TI - Multi-stage Path Planning Strategy for Intelligent Cleaning Robot
SN - 978-989-758-622-4
AU - Cheng X.
AU - Ding X.
AU - Tungom C.
AU - Yuan J.
PY - 2022
SP - 757
EP - 765
DO - 10.5220/0012046400003612
PB - SciTePress