KFU. Card publication. DCEGen: Dense clutter environment generation tool for autonomous 3D exploration and coverage algorithms testing

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

DCEGEN: DENSE CLUTTER ENVIRONMENT GENERATION TOOL FOR AUTONOMOUS 3D EXPLORATION AND COVERAGE ALGORITHMS TESTING

Form of presentation

Articles in international journals and collections

Year of publication

2019

��

��

Authors, employees of KFU

Lavrenov Roman Olegovich, author

Magid Evgeniy Arkadevich, author

Sagitov Artur Gazizovich, author

Other authors

Su Kuo-Lan , author

Svinin Mikhail , author

Authors, students KFU

Denisov Evgeniy Valerevich, author

Bibliographic description in the original language

Denisov E. DCEGen: Dense Clutter Environment Generation Tool for Autonomous 3D Exploration and Coverage Algorithms Testing / Sagitov A., Lavrenov R., Su K.-L., Svinin M., Magid E. // Lecture Notes in Computer Science. - 2019. - Vol. 11659. - p. 216-225.

Annotation

Autonomous exploration and coverage in 3D environments recently has became a rapidly developing research field. Emerging 3D reconstruction methods, designed specifically for exploration and coverage, allows capturing an environment in a greater details. However, not much work addresses certain difficulties inherent to dense clutter environments. We observed those difficulties and made an attempt that seeks to expand the applicability of such methods to more demanding scenarios. Automating the process of testing and evaluation by designing a dense clutter environment generation algorithm (DCEGen) allows us to measure comparative performance of available algorithms. We focus on path-planning algorithms used in an unmanned ground vehicles. The algorithm was implemented and verified using Gazebo simulator.

Keywords

Mobile robot, Gazebo simulation, ROS, Dense clutter environment, 3D environment, reconstruction, Autonomous exploration and coverage algorithm, Next-best-view,

The name of the journal

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

URL

https://link.springer.com/chapter/10.1007/978-3-030-26118-4_21

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

https://repository.kpfu.ru/eng/?p_id=209119&p_lang=2

Resource files

File name	Size (MB)	Format
Denisov_PaperFromBook.pdf	2,95	pdf	show / download

Full metadata record

Field DC	Value	Language
dc.contributor.author	Lavrenov Roman Olegovich	ru_RU
dc.contributor.author	Magid Evgeniy Arkadevich	ru_RU
dc.contributor.author	Sagitov Artur Gazizovich	ru_RU
dc.contributor.author	Su Kuo-Lan	ru_RU
dc.contributor.author	Svinin Mikhail	ru_RU
dc.contributor.author	Denisov Evgeniy Valerevich	ru_RU
dc.date.accessioned	2019-01-01T00:00:00Z	ru_RU
dc.date.available	2019-01-01T00:00:00Z	ru_RU
dc.date.issued	2019	ru_RU
dc.identifier.citation	Denisov E. DCEGen: Dense Clutter Environment Generation Tool for Autonomous 3D Exploration and Coverage Algorithms Testing / Sagitov A., Lavrenov R., Su K.-L., Svinin M., Magid E. // Lecture Notes in Computer Science. - 2019. - Vol. 11659. - p. 216-225.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=209119&p_lang=2	ru_RU
dc.description.abstract	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	ru_RU
dc.description.abstract	Autonomous exploration and coverage in 3D environments recently has became a rapidly developing research field. Emerging 3D reconstruction methods, designed specifically for exploration and coverage, allows capturing an environment in a greater details. However, not much work addresses certain difficulties inherent to dense clutter environments. We observed those difficulties and made an attempt that seeks to expand the applicability of such methods to more demanding scenarios. Automating the process of testing and evaluation by designing a dense clutter environment generation algorithm (DCEGen) allows us to measure comparative performance of available algorithms. We focus on path-planning algorithms used in an unmanned ground vehicles. The algorithm was implemented and verified using Gazebo simulator.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	Mobile robot	ru_RU
dc.subject	Gazebo simulation	ru_RU
dc.subject	ROS	ru_RU
dc.subject	Dense clutter environment	ru_RU
dc.subject	3D environment	ru_RU
dc.subject	reconstruction	ru_RU
dc.subject	Autonomous exploration and coverage algorithm	ru_RU
dc.subject	Next-best-view	ru_RU
dc.subject		ru_RU
dc.title	DCEGen: Dense clutter environment generation tool for autonomous 3D exploration and coverage algorithms testing	ru_RU
dc.type	Articles in international journals and collections	ru_RU