Experimental Analysis of Acoustic Field Control-Based Robot Navigation
This paper proposes novel robot navigation methods that utilize strong interaction between a designed field and a robot controller. In recent years, several studies have demonstrated the importance of interactions between different subject types (e.g., human-robot interaction, robot-environment inte...
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| Published in | Journal of robotics and mechatronics Vol. 31; no. 1; pp. 110 - 117 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Tokyo
Fuji Technology Press Co. Ltd
01.02.2019
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 0915-3942 1883-8049 1883-8049 |
| DOI | 10.20965/jrm.2019.p0110 |
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| Abstract | This paper proposes novel robot navigation methods that utilize strong interaction between a designed field and a robot controller. In recent years, several studies have demonstrated the importance of interactions between different subject types (e.g., human-robot interaction, robot-environment interaction) instead of just that between a robot controller and an isolated subject. This study explores the
robot-field interaction
design to realize autonomous robot navigation, and verifies the proposed methods experimentally. We prepare acoustic navigation trails from the start to the goal; one is generated from multiple sounds with identical frequencies, while the other is generated from multiple sounds with different frequencies. For each field controller, both the dynamic acoustic trail and the static acoustic trail, two types of
static
robot controllers are designed based only on the
present
sensor data,
namely
, gradient-following controller and sound-habituation controller. The former is a microphone-array based controller for robots equipped with multiple microphones, while the latter is designed for robots with a single microphone. Throughout the real-world demonstration, we show the validity of our proposed methods. |
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| AbstractList | This paper proposes novel robot navigation methods that utilize strong interaction between a designed field and a robot controller. In recent years, several studies have demonstrated the importance of interactions between different subject types (e.g., human-robot interaction, robot-environment interaction) instead of just that between a robot controller and an isolated subject. This study explores the robot-field interaction design to realize autonomous robot navigation, and verifies the proposed methods experimentally. We prepare acoustic navigation trails from the start to the goal; one is generated from multiple sounds with identical frequencies, while the other is generated from multiple sounds with different frequencies. For each field controller, both the dynamic acoustic trail and the static acoustic trail, two types of static robot controllers are designed based only on the present sensor data, namely, gradient-following controller and sound-habituation controller. The former is a microphone-array based controller for robots equipped with multiple microphones, while the latter is designed for robots with a single microphone. Throughout the real-world demonstration, we show the validity of our proposed methods. This paper proposes novel robot navigation methods that utilize strong interaction between a designed field and a robot controller. In recent years, several studies have demonstrated the importance of interactions between different subject types (e.g., human-robot interaction, robot-environment interaction) instead of just that between a robot controller and an isolated subject. This study explores the robot-field interaction design to realize autonomous robot navigation, and verifies the proposed methods experimentally. We prepare acoustic navigation trails from the start to the goal; one is generated from multiple sounds with identical frequencies, while the other is generated from multiple sounds with different frequencies. For each field controller, both the dynamic acoustic trail and the static acoustic trail, two types of static robot controllers are designed based only on the present sensor data, namely , gradient-following controller and sound-habituation controller. The former is a microphone-array based controller for robots equipped with multiple microphones, while the latter is designed for robots with a single microphone. Throughout the real-world demonstration, we show the validity of our proposed methods. |
| Author | Tsunoda, Yusuke Sueoka, Yuichiro Osuka, Koichi |
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| CitedBy_id | crossref_primary_10_20965_jrm_2021_p0119 crossref_primary_10_20965_jrm_2023_p0957 crossref_primary_10_1016_j_iswa_2022_200115 |
| Cites_doi | 10.1109/ROBOT.2008.4543492 10.1109/ROBOT.1997.606882 10.1109/IROS.2008.4650971 10.1109/ROBOT.1991.131810 10.1109/70.143352 10.1109/ROBOT.2008.4543409 10.1007/978-1-4613-8997-2_29 10.7210/jrsj.29.395 10.1017/S0263574704001225 10.1007/s10514-007-9035-x 10.1109/JPROC.2006.887293 10.1109/70.163777 |
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| DOI | 10.20965/jrm.2019.p0110 |
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| SubjectTerms | Acoustic navigation Acoustics Autonomous navigation Controllers Habituation (learning) Human engineering Microphones Robot control Robots Strong interactions (field theory) |
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| Title | Experimental Analysis of Acoustic Field Control-Based Robot Navigation |
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