KFU. Card publication. Creation of a synthetic dataset for training precise movements of robots for in various industries

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

CREATION OF A SYNTHETIC DATASET FOR TRAINING PRECISE MOVEMENTS OF ROBOTS FOR IN VARIOUS INDUSTRIES

Form of presentation

Articles in international journals and collections

Year of publication

2024

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Authors, employees of KFU

Kostyuk Daniil Ivanovich, author

Kugurakova Vlada Vladimirovna, author

Authors, students KFU

Gabdullin Rafael Raynurovich, author

Iskhakov Robert Tagirovich, author

Bibliographic description in the original language

Gabdullin R.R., Kugurakova V.V., Iskhakov R.T. Creation of a synthetic dataset for training precise movements of robots for in various industries//BIO Web of Conferences. - 2024. - Vol.145. - Art. �03026.

Annotation

Creating synthetic datasets for artificial intelligence training has a crucial role in modern developments. Considering the difficulties in collecting real data, which is often a costly and time-consuming process that requires significant resources and time. Synthetic data, on the other hand, allows generating large amounts of varied and controlled data that can be customized for specific training and testing needs. This makes the process of algorithm development and improvement more efficient and affordable. This paper presents a comprehensive tool for creating synthetic motion datasets based on rigging a 3D robot model. The ability to create and edit animations through the Blender interface is described. It supports a variety of well-known 3D model formats, providing flexibility in use, and includes powerful tools to achieve high-quality visual effects and realistic scenes. In addition, the tool can automatically generate a large number of robot images needed for training neural networks. By utilizing these capabilities, the tool greatly simplifies the creation of training datasets, making the process more efficient and affordable. Possible future enhancements include automation of rigging, further optimizing the functionality and usability of the tool for robotics and machine learning.

Keywords

synthetic dataset, training precise movements, robot, virtual reality

The name of the journal

BIO Web of Conferences

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216638582&doi=10.1051%2fbioconf%2f202414503026&partnerID=40&md5=efef4a879829481203ed3c3ab391c198

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=311541&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Kostyuk Daniil Ivanovich	ru_RU
dc.contributor.author	Kugurakova Vlada Vladimirovna	ru_RU
dc.contributor.author	Gabdullin Rafael Raynurovich	ru_RU
dc.contributor.author	Iskhakov Robert Tagirovich	ru_RU
dc.date.accessioned	2024-01-01T00:00:00Z	ru_RU
dc.date.available	2024-01-01T00:00:00Z	ru_RU
dc.date.issued	2024	ru_RU
dc.identifier.citation	Gabdullin R.R., Kugurakova V.V., Iskhakov R.T. Creation of a synthetic dataset for training precise movements of robots for in various industries//BIO Web of Conferences. - 2024. - Vol.145. - Art. �03026.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=311541&p_lang=2	ru_RU
dc.description.abstract	BIO Web of Conferences	ru_RU
dc.description.abstract	Creating synthetic datasets for artificial intelligence training has a crucial role in modern developments. Considering the difficulties in collecting real data, which is often a costly and time-consuming process that requires significant resources and time. Synthetic data, on the other hand, allows generating large amounts of varied and controlled data that can be customized for specific training and testing needs. This makes the process of algorithm development and improvement more efficient and affordable. This paper presents a comprehensive tool for creating synthetic motion datasets based on rigging a 3D robot model. The ability to create and edit animations through the Blender interface is described. It supports a variety of well-known 3D model formats, providing flexibility in use, and includes powerful tools to achieve high-quality visual effects and realistic scenes. In addition, the tool can automatically generate a large number of robot images needed for training neural networks. By utilizing these capabilities, the tool greatly simplifies the creation of training datasets, making the process more efficient and affordable. Possible future enhancements include automation of rigging, further optimizing the functionality and usability of the tool for robotics and machine learning.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	synthetic dataset	ru_RU
dc.subject	training precise movements	ru_RU
dc.subject	robot	ru_RU
dc.subject	virtual reality	ru_RU
dc.title	Creation of a synthetic dataset for training precise movements of robots for in various industries	ru_RU
dc.type	Articles in international journals and collections	ru_RU