KFU. Card publication. Combining voronoi graph and spline-based approaches for a mobile robot path planning

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

COMBINING VORONOI GRAPH AND SPLINE-BASED APPROACHES FOR A MOBILE ROBOT PATH PLANNING

Form of presentation

Articles in international journals and collections

Year of publication

2017

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Authors, employees of KFU

Lavrenov Roman Olegovich, author

Magid Evgeniy Arkadevich, author

Khasyanov Ayrat Faridovich, author

Other authors

Svinin Mikhail , author

Bibliographic description in the original language

Magid E. Combining Voronoi graph and spline-based approaches for a mobile robot path planning / Lavrenov R., Svinin M., Khasianov A. // Lecture Notes in Electrical Engineering. - 2017. - � 495. - p. 475-496.

Annotation

Potential function based methods play significant role in both global and local path planning. While these methods are characterized with good reactive behaviour and implementation simplicity, they suffer from a well-known problem of getting stuck in local minima of a navigation function. In this paper we propose a modification of our original spline-based path planning algorithm for a mobile robot navigation, which succeeds to solve local minima problem and considers additional criteria of start and target points visibility to help optimizing the path selection. We apply a Voronoi graph based path as an input for iterative multi criteria optimization algorithm and present a path finding strategy within different homotopies that uses the new method. The algorithm was implemented in Matlab environment and demonstrated significantly better results than the original approach. The comparison was based on success rate, number of iterations and running time of the algorithms. In total, several thousands tests were performed in 18 different simulated environments.

Keywords

MATLAB, Mobile robot, Path planning algorithm, Potential field, Robotics, Simulated experiments, Voronoi diagram

The name of the journal

Lecture Notes in Electrical Engineering

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065493962&doi=10.1007%2f978-3-030-11292-9_24&partnerID=40&md5=346ee5837b437fdb3f42d7de62610ebd

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

https://repository.kpfu.ru/eng/?p_id=202359&p_lang=2

Resource files

File name	Size (MB)	Format
ICAR_JOURNAL_MAG_ROM.pdf	4,25	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	Khasyanov Ayrat Faridovich	ru_RU
dc.contributor.author	Svinin Mikhail	ru_RU
dc.date.accessioned	2017-01-01T00:00:00Z	ru_RU
dc.date.available	2017-01-01T00:00:00Z	ru_RU
dc.date.issued	2017	ru_RU
dc.identifier.citation	Magid E. Combining Voronoi graph and spline-based approaches for a mobile robot path planning / Lavrenov R., Svinin M., Khasianov A. // Lecture Notes in Electrical Engineering. - 2017. - � 495. - p. 475-496.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=202359&p_lang=2	ru_RU
dc.description.abstract	Lecture Notes in Electrical Engineering	ru_RU
dc.description.abstract	Potential function based methods play significant role in both global and local path planning. While these methods are characterized with good reactive behaviour and implementation simplicity, they suffer from a well-known problem of getting stuck in local minima of a navigation function. In this paper we propose a modification of our original spline-based path planning algorithm for a mobile robot navigation, which succeeds to solve local minima problem and considers additional criteria of start and target points visibility to help optimizing the path selection. We apply a Voronoi graph based path as an input for iterative multi criteria optimization algorithm and present a path finding strategy within different homotopies that uses the new method. The algorithm was implemented in Matlab environment and demonstrated significantly better results than the original approach. The comparison was based on success rate, number of iterations and running time of the algorithms. In total, several thousands tests were performed in 18 different simulated environments.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	MATLAB	ru_RU
dc.subject	Mobile robot	ru_RU
dc.subject	Path planning algorithm	ru_RU
dc.subject	Potential field	ru_RU
dc.subject	Robotics	ru_RU
dc.subject	Simulated experiments	ru_RU
dc.subject	Voronoi diagram	ru_RU
dc.title	Combining voronoi graph and spline-based approaches for a mobile robot path planning	ru_RU
dc.type	Articles in international journals and collections	ru_RU