Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

Improved Hybrid Algorithm of Path Planning for Automated Guided Vehicle in Storage System

Authors
Jian Wang, Xinhua Zhu, Minhuan Guo, Surui Yao, Yan Su
Corresponding Author
Jian Wang
Available Online June 2017.
DOI
https://doi.org/10.2991/caai-17.2017.75How to use a DOI?
Keywords
automated guided vehicle; path planning; A* algorithm; APF algorithm; improved hybrid algorithm
Abstract
Aiming at the problem of automated guided vehicle path planning in storage system, this paper provided a new method which combines global path planning algorithm and local path planning algorithm to achieve the goal of finding the optimal path. In this paper, the improved A* algorithm is used as the global path planning algorithm, and the improved APF algorithm is used as the local path planning algorithm. The hybrid algorithm not only makes full use of the known information to generate the global optimal path, but also can effectively avoid obstacles on the path. The advantages and effectiveness of the hybrid algorithm are proved by the results of simulations and applications.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
978-94-6252-360-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/caai-17.2017.75How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jian Wang
AU  - Xinhua Zhu
AU  - Minhuan Guo
AU  - Surui Yao
AU  - Yan Su
PY  - 2017/06
DA  - 2017/06
TI  - Improved Hybrid Algorithm of Path Planning for Automated Guided Vehicle in Storage System
BT  - 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 332
EP  - 336
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.75
DO  - https://doi.org/10.2991/caai-17.2017.75
ID  - Wang2017/06
ER  -