KFU. Card publication. Person-Following Algorithm Based on Laser Range Finder and Monocular Camera Data Fusion for a Wheeled Autonomous Mobile Robot

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PERSON-FOLLOWING ALGORITHM BASED ON LASER RANGE FINDER AND MONOCULAR CAMERA DATA FUSION FOR A WHEELED AUTONOMOUS MOBILE ROBOT

Form of presentation

Articles in international journals and collections

Year of publication

2020

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Authors, employees of KFU

Magid Evgeniy Arkadevich, author

Safin Ramil Nabiullovich, author

Chebotareva Elvira Valerevna, author

Bibliographic description in the original language

Chebotareva E. Person-Following Algorithm Based on Laser Range Finder and Monocular Camera Data Fusion for a Wheeled Autonomous Mobile Robot / Safin R., Hsia K.-H., Carballo A., Magid E. // Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2020. - �12336. - p. 21-33.

Annotation

Reliable human following is one of the key capabilities of service and personal assisting robots. This paper presents a novel person tracking and following approach for autonomous mobile robots that are equipped with a 2D laser rangefinder (LRF) and a monocular camera. The proposed method does not impose restrictions on a person's clothes, does not require a head or an upper body to be within a camera field of view and is suitable for low height indoor robots as well. The algorithm is based on a metric that takes into an account parameters obtained directly from LRF and monocular camera data. The algorithm was implemented and tested in the Gazebo simulator. Next, it was integrated into a control system of the TIAGo Base mobile robot and successfully validated in university environment experiments with real people. In addition, this paper proposes a new criterion of algorithm performance estimation, which is a function of false positives number and traveled distances by a person and by a robot. Further this criterion is used to compare performance of the proposed method with the Multiple Instance Learning (MIL) tracker in simulated and in real world environments.

Keywords

Mobile robot, Human tracking, Human following, algorithm, Laser range finder, Monocular camera, Multisensor tracking, Accuracy score, ROS, Gazebo

The name of the journal

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

URL

https://www.springerprofessional.de/en/person-following-algorithm-based-on-laser-range-finder-and-monoc/18430956

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

https://repository.kpfu.ru/eng/?p_id=240259&p_lang=2

Resource files

File name	Size (MB)	Format
F_ICR_2020_Chebotareva_PersonFollowing.pdf	1,22	pdf	show / download

Full metadata record

Field DC	Value	Language
dc.contributor.author	Magid Evgeniy Arkadevich	ru_RU
dc.contributor.author	Safin Ramil Nabiullovich	ru_RU
dc.contributor.author	Chebotareva Elvira Valerevna	ru_RU
dc.date.accessioned	2020-01-01T00:00:00Z	ru_RU
dc.date.available	2020-01-01T00:00:00Z	ru_RU
dc.date.issued	2020	ru_RU
dc.identifier.citation	Chebotareva E. Person-Following Algorithm Based on Laser Range Finder and Monocular Camera Data Fusion for a Wheeled Autonomous Mobile Robot / Safin R., Hsia K.-H., Carballo A., Magid E. // Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2020. - �12336. - p. 21-33.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=240259&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	Reliable human following is one of the key capabilities of service and personal assisting robots. This paper presents a novel person tracking and following approach for autonomous mobile robots that are equipped with a 2D laser rangefinder (LRF) and a monocular camera. The proposed method does not impose restrictions on a person's clothes, does not require a head or an upper body to be within a camera field of view and is suitable for low height indoor robots as well. The algorithm is based on a metric that takes into an account parameters obtained directly from LRF and monocular camera data. The algorithm was implemented and tested in the Gazebo simulator. Next, it was integrated into a control system of the TIAGo Base mobile robot and successfully validated in university environment experiments with real people. In addition, this paper proposes a new criterion of algorithm performance estimation, which is a function of false positives number and traveled distances by a person and by a robot. Further this criterion is used to compare performance of the proposed method with the Multiple Instance Learning (MIL) tracker in simulated and in real world environments.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	Mobile robot	ru_RU
dc.subject	Human tracking	ru_RU
dc.subject	Human following	ru_RU
dc.subject	algorithm	ru_RU
dc.subject	Laser range finder	ru_RU
dc.subject	Monocular camera	ru_RU
dc.subject	Multisensor tracking	ru_RU
dc.subject	Accuracy score	ru_RU
dc.subject	ROS	ru_RU
dc.subject	Gazebo	ru_RU
dc.title	Person-Following Algorithm Based on Laser Range Finder and Monocular Camera Data Fusion for a Wheeled Autonomous Mobile Robot	ru_RU
dc.type	Articles in international journals and collections	ru_RU