KFU. Card publication. Automatic mapping and filtering tool: From a sensor-based occupancy grid to a 3D Gazebo octomap

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

AUTOMATIC MAPPING AND FILTERING TOOL: FROM A SENSOR-BASED OCCUPANCY GRID TO A 3D GAZEBO OCTOMAP

Form of presentation

Articles in international journals and collections

Year of publication

2017

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Authors, employees of KFU

Zakiev Aufar Azatovich, author

Lavrenov Roman Olegovich, author

Magid Evgeniy Arkadevich, author

Authors, postgraduates KFU

Lavrenov Roman Olegovich, postgraduate kfu

Authors, students KFU

Zakiev Aufar Azatovich, author

Bibliographic description in the original language

Lavrenov R., Zakiev A., Magid E. Automatic mapping and filtering tool: From a sensor-based occupancy grid to a 3D Gazebo octomap // ICMSC 2017 - International Conference on Mechanical, System and Control Engineering (St.Petersburg, Russia; 19-21 May 2017) - p. 190-195.

Annotation

Robot simulations nowadays provide significant support in testing new algorithms for robotic systems for a broad area of tasks, including navigation, mapping, and SLAM. Within a simulation, special attention should be paid for providing algorithms with realistic testing environments that are to be further used for robot navigation. This paper presents an automatic tool that allows creating realistic landscapes in Gazebo simulation, which are based on results of real world sensor-based exploration. The tool provides automatic filtering and importing of an occupancy grid map into Gazebo framework as a heightmap.

Keywords

Gazebo, ROS, octomap, occupancy grid, heightmap, map filtering

The name of the journal

2017 International Conference on Mechanical, System and Control Engineering, ICMSC 2017

URL

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85025825922&doi=10.1109%2fICMSC.2017.7959469&partnerID=40&md5=7eedf715f593235ca91d67f214636b8c

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

https://repository.kpfu.ru/eng/?p_id=162559&p_lang=2

Resource files

File name	Size (MB)	Format
2017_Automatic_mapping_and_filtering_tool_from_a_sensor_based_occupancy_grid_to_a_3D_Gazebo_octomap___kopiya.pdf	0,79	pdf	show / download

Full metadata record

Field DC	Value	Language
dc.contributor.author	Zakiev Aufar Azatovich	ru_RU
dc.contributor.author	Lavrenov Roman Olegovich	ru_RU
dc.contributor.author	Magid Evgeniy Arkadevich	ru_RU
dc.contributor.author	Zakiev Aufar Azatovich	ru_RU
dc.contributor.author	Lavrenov Roman Olegovich	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	Lavrenov R., Zakiev A., Magid E. Automatic mapping and filtering tool: From a sensor-based occupancy grid to a 3D Gazebo octomap // ICMSC 2017 - International Conference on Mechanical, System and Control Engineering (St.Petersburg, Russia; 19-21 May 2017) - p. 190-195.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=162559&p_lang=2	ru_RU
dc.description.abstract	2017 International Conference on Mechanical, System and Control Engineering, ICMSC 2017	ru_RU
dc.description.abstract	Robot simulations nowadays provide significant support in testing new algorithms for robotic systems for a broad area of tasks, including navigation, mapping, and SLAM. Within a simulation, special attention should be paid for providing algorithms with realistic testing environments that are to be further used for robot navigation. This paper presents an automatic tool that allows creating realistic landscapes in Gazebo simulation, which are based on results of real world sensor-based exploration. The tool provides automatic filtering and importing of an occupancy grid map into Gazebo framework as a heightmap.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	Gazebo	ru_RU
dc.subject	ROS	ru_RU
dc.subject	octomap	ru_RU
dc.subject	occupancy grid	ru_RU
dc.subject	heightmap	ru_RU
dc.subject	map filtering	ru_RU
dc.title	Automatic mapping and filtering tool: From a sensor-based occupancy grid to a 3D Gazebo octomap	ru_RU
dc.type	Articles in international journals and collections	ru_RU