| Форма представления | Статьи в зарубежных журналах и сборниках |
| Год публикации | 2020 |
| Язык | английский |
|
Магид Евгений Аркадьевич, автор
Сафин Рамиль Набиуллович, автор
Чеботарева Эльвира Валерьевна, автор
|
| Библиографическое описание на языке оригинала |
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. |
| Аннотация |
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. |
| Ключевые слова |
Mobile robot, Human tracking, Human following, algorithm, Laser range finder, Monocular camera, Multisensor tracking, Accuracy score, ROS, Gazebo |
| Название журнала |
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 |
| Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку |
https://repository.kpfu.ru/?p_id=240259 |
| Файлы ресурса | |
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Полная запись метаданных  |
| Поле DC |
Значение |
Язык |
| dc.contributor.author |
Магид Евгений Аркадьевич |
ru_RU |
| dc.contributor.author |
Сафин Рамиль Набиуллович |
ru_RU |
| dc.contributor.author |
Чеботарева Эльвира Валерьевна |
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/?p_id=240259 |
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 |
Статьи в зарубежных журналах и сборниках |
ru_RU |
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