Proceedings of the 8th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2020)

A Robotic Complex Control Method Based on Deep Reinforcement Learning of Recurrent Neural Networks for Automatic Harvesting of Greenhouse Crops

Authors
Vyacheslav Petrenko, Fariza Tebueva, Vladimir Antonov, Mikhail Gurchinsky
Corresponding Author
Fariza Tebueva
Available Online 10 November 2020.
DOI
https://doi.org/10.2991/aisr.k.201029.064How to use a DOI?
Keywords
deep reinforcement learning, recurrent neural networks, recurrent Q-networks, automation and robotics, decision-making
Abstract

The modern development of technology determines the feasibility of the transition in agriculture from manual labor to automatic production. One of the promising areas is the automation of growing vegetable crops in greenhouse complexes. Necessary factors for intensive plant growth and unfavorable for human health, such as high temperature and humidity, as well as an atmosphere saturated with chemicals, make the task of robotizing agricultural operations urgent in this area. The method for controlling a robotic complex for automatic fruit collection in greenhouse complexes is proposed. Work in greenhouse complexes is characterized as non-deterministic and with partial observability of the environment; therefore, the deep recurrent neural network DRQN was used as the basis for the method of controlling the robotic complex. Deep learning with reinforcement was used for optimizing its weights. The presented simulation results demonstrate the efficiency of the proposed method and the need for its further development.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 8th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2020)
Series
Advances in Intelligent Systems Research
Publication Date
10 November 2020
ISBN
10.2991/aisr.k.201029.064
ISSN
1951-6851
DOI
https://doi.org/10.2991/aisr.k.201029.064How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Vyacheslav Petrenko
AU  - Fariza Tebueva
AU  - Vladimir Antonov
AU  - Mikhail Gurchinsky
PY  - 2020
DA  - 2020/11/10
TI  - A Robotic Complex Control Method Based on Deep Reinforcement Learning of Recurrent Neural Networks for Automatic Harvesting of Greenhouse Crops
BT  - Proceedings of the 8th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2020)
PB  - Atlantis Press
SP  - 340
EP  - 346
SN  - 1951-6851
UR  - https://doi.org/10.2991/aisr.k.201029.064
DO  - https://doi.org/10.2991/aisr.k.201029.064
ID  - Petrenko2020
ER  -