dc.contributor.author |
Denisov E. |
|
dc.contributor.author |
Sagitov A. |
|
dc.contributor.author |
Yakovlev K. |
|
dc.contributor.author |
Su K. |
|
dc.contributor.author |
Svinin M. |
|
dc.contributor.author |
Magid E. |
|
dc.date.accessioned |
2020-01-15T22:06:57Z |
|
dc.date.available |
2020-01-15T22:06:57Z |
|
dc.date.issued |
2019 |
|
dc.identifier.uri |
https://dspace.kpfu.ru/xmlui/handle/net/156646 |
|
dc.description.abstract |
Copyright © 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved Recent developments in 3D reconstruction systems enable to capture an environment in great detail. Several studies have provided algorithms that deal with a path-planning problem of total coverage of observable space in time-efficient manner. However, not much work was done in the area of globally optimal solutions in dense clutter environments. This paper presents a novel solution for autonomous exploration of a cluttered 2.5D environment using an unmanned ground mobile vehicle, where robot locomotion is limited to a 2D plane, while obstacles have a 3D shape. Our exploration algorithm increases coverage of 3D environment mapping comparatively to other currently available algorithms. The algorithm was implemented and tested in randomly generated dense clutter environments in MATLAB. |
|
dc.subject |
Autonomous Exploration and Coverage Algorithm |
|
dc.subject |
Dense Clutter Environment |
|
dc.subject |
Environment Reconstruction |
|
dc.subject |
Mobile Robot |
|
dc.subject |
Next-best-view |
|
dc.subject |
Path Planning |
|
dc.title |
Towards total coverage in autonomous exploration for UGV in 2.5D dense clutter environment |
|
dc.type |
Conference Paper |
|
dc.relation.ispartofseries-volume |
2 |
|
dc.collection |
Публикации сотрудников КФУ |
|
dc.relation.startpage |
409 |
|
dc.source.id |
SCOPUS-2019-2-SID85073031408 |
|