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 inJournal of robotics and mechatronics Vol. 31; no. 1; pp. 110 - 117
Main Authors Tsunoda, Yusuke, Sueoka, Yuichiro, Osuka, Koichi
Format Journal Article
LanguageEnglish
Published Tokyo Fuji Technology Press Co. Ltd 01.02.2019
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ISSN0915-3942
1883-8049
1883-8049
DOI10.20965/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.
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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crossref_primary_10_20965_jrm_2023_p0957
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StartPage 110
SubjectTerms Acoustic navigation
Acoustics
Autonomous navigation
Controllers
Habituation (learning)
Human engineering
Microphones
Robot control
Robots
Strong interactions (field theory)
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