Method of controlling the movement of an anthropomorphic manipulator in the working area with dynamic obstacle

Currently, the rapidly developing direction of anthropomorphic robotics attracts great interest of developers. This is due to the need to perform routine, harmful and hazardous types of work without direct human intervention, which is the key to ensuring the safety of the tasks performed. The articl...

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Asıl Yazarlar:	Petrenko, V. I., Петренко, В. И., Tebueva, F. B., Тебуева, Ф. Б., Ryabtsev, S. S., Рябцев, С. С., Gurchinsky, M. M., Гурчинский, М. М.
Materyal Türü:	Статья
Dil:	English
Baskı/Yayın Bilgisi:	ATLANTIS PRESS 2021
Konular:	Machine learning Convolutional neural networks Anthropomorphic manipulator Dynamic environment Dynamic obstacles
Online Erişim:	https://dspace.ncfu.ru/handle/20.500.12258/18115
Etiketler:	Etiketle Etiket eklenmemiş, İlk siz ekleyin!

id	ir-20.500.12258-18115
record_format	dspace
spelling	ir-20.500.12258-181152021-09-08T07:31:17Z Method of controlling the movement of an anthropomorphic manipulator in the working area with dynamic obstacle Petrenko, V. I. Петренко, В. И. Tebueva, F. B. Тебуева, Ф. Б. Ryabtsev, S. S. Рябцев, С. С. Gurchinsky, M. M. Гурчинский, М. М. Machine learning Convolutional neural networks Anthropomorphic manipulator Dynamic environment Dynamic obstacles Currently, the rapidly developing direction of anthropomorphic robotics attracts great interest of developers. This is due to the need to perform routine, harmful and hazardous types of work without direct human intervention, which is the key to ensuring the safety of the tasks performed. The article discusses the issue of optimizing the trajectory of the manipulator when performing operations in the working area with an obstacle. To achieve this goal, an algorithm for controlling the movement of an anthropomorphic manipulator in a working area with dynamic obstacles is proposed using deep learning technology with amplification of a convolutional artificial neural network based on the DQN learning algorithm. This algorithm is more scalable than peers because it can be used for a wide variety of path planning problems in both deterministic and non-deterministic environments. The results of modeling the operation of a manipulator with seven rotational degrees of mobility in the working area with a typical obstacle in the form of a sphere are presented. The presented simulation results demonstrate the effectiveness of the proposed method and the need for its further development 2021-09-08T07:30:04Z 2021-09-08T07:30:04Z 2020 Статья Petrenko, V. I.; Tebueva, F. B.; Ryabtsev, S. S.; Gurchinsky, M. M. Method of controlling the movement of an anthropomorphic manipulator in the working area with dynamic obstacle // PROCEEDINGS OF THE 8TH SCIENTIFIC CONFERENCE ON INFORMATION TECHNOLOGIES FOR INTELLIGENT DECISION MAKING SUPPORT (ITIDS 2020). - 2020. - Book Series: Advances in Intelligent Systems Research. - Volume 174. - Page 359-364 http://hdl.handle.net/20.500.12258/18115 en PROCEEDINGS OF THE 8TH SCIENTIFIC CONFERENCE ON INFORMATION TECHNOLOGIES FOR INTELLIGENT DECISION MAKING SUPPORT (ITIDS 2020) application/pdf ATLANTIS PRESS
institution	СКФУ
collection	Репозиторий
language	English
topic	Machine learning Convolutional neural networks Anthropomorphic manipulator Dynamic environment Dynamic obstacles
spellingShingle	Machine learning Convolutional neural networks Anthropomorphic manipulator Dynamic environment Dynamic obstacles Petrenko, V. I. Петренко, В. И. Tebueva, F. B. Тебуева, Ф. Б. Ryabtsev, S. S. Рябцев, С. С. Gurchinsky, M. M. Гурчинский, М. М. Method of controlling the movement of an anthropomorphic manipulator in the working area with dynamic obstacle
description	Currently, the rapidly developing direction of anthropomorphic robotics attracts great interest of developers. This is due to the need to perform routine, harmful and hazardous types of work without direct human intervention, which is the key to ensuring the safety of the tasks performed. The article discusses the issue of optimizing the trajectory of the manipulator when performing operations in the working area with an obstacle. To achieve this goal, an algorithm for controlling the movement of an anthropomorphic manipulator in a working area with dynamic obstacles is proposed using deep learning technology with amplification of a convolutional artificial neural network based on the DQN learning algorithm. This algorithm is more scalable than peers because it can be used for a wide variety of path planning problems in both deterministic and non-deterministic environments. The results of modeling the operation of a manipulator with seven rotational degrees of mobility in the working area with a typical obstacle in the form of a sphere are presented. The presented simulation results demonstrate the effectiveness of the proposed method and the need for its further development
format	Статья
author	Petrenko, V. I. Петренко, В. И. Tebueva, F. B. Тебуева, Ф. Б. Ryabtsev, S. S. Рябцев, С. С. Gurchinsky, M. M. Гурчинский, М. М.
author_facet	Petrenko, V. I. Петренко, В. И. Tebueva, F. B. Тебуева, Ф. Б. Ryabtsev, S. S. Рябцев, С. С. Gurchinsky, M. M. Гурчинский, М. М.
author_sort	Petrenko, V. I.
title	Method of controlling the movement of an anthropomorphic manipulator in the working area with dynamic obstacle
title_short	Method of controlling the movement of an anthropomorphic manipulator in the working area with dynamic obstacle
title_full	Method of controlling the movement of an anthropomorphic manipulator in the working area with dynamic obstacle
title_fullStr	Method of controlling the movement of an anthropomorphic manipulator in the working area with dynamic obstacle
title_full_unstemmed	Method of controlling the movement of an anthropomorphic manipulator in the working area with dynamic obstacle
title_sort	method of controlling the movement of an anthropomorphic manipulator in the working area with dynamic obstacle
publisher	ATLANTIS PRESS
publishDate	2021
url	https://dspace.ncfu.ru/handle/20.500.12258/18115
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Method of controlling the movement of an anthropomorphic manipulator in the working area with dynamic obstacle

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