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JRM Vol.33 No.6 pp. 1315-1325
doi: 10.20965/jrm.2021.p1315
(2021)

Paper:

Spread Spectrum Sound with TDMA and INS Hybrid Navigation System for Indoor Environment

Romprakhun Tientadakul*, Hiroaki Nakanishi*, Tomoo Shiigi**, Zichen Huang***, Lok Wai Jacky Tsay***, and Naoshi Kondo***

*Graduate School of Engineering, Kyoto University
Kyoto daigaku-katsura, Nishikyo-ku, Kyoto 615-8540, Japan

**Department of Ocean Mechanical Engineering, National Fisheries University
2-7-1 Nagata-Honmachi, Shimonoseki, Yamaguchi 759-6595, Japan

***Graduate School of Agriculture, Kyoto University
Kitashirakawa-Oiwakecho, Sakyo-ku, Kyoto 606-8502, Japan

Received:
June 7, 2021
Accepted:
October 25, 2021
Published:
December 20, 2021
Keywords:
indoor navigation, inertial navigation, time of arrival, spread spectrum sound, time division multiple access
Abstract

Indoor navigation plays an essential role in agricultural robots that operate in greenhouses. One of the most effective methods for indoor navigation is the spread spectrum sound (SS-sound) system. In this system, the time of arrival (ToA) of the spread spectrum modulated sound is used for localization. However, there is a near-far problem. Transmitting the SS-sound from multiple anchors using time division multiple access (TDMA) is adequate to solve the near-far problem. However, localization is impossible because the ToA from multiple anchors cannot be simultaneously acquired. To solve this problem, a method for combining the SS-sound system with TDMA and an inertial navigation system is proposed in this study. The effectiveness of the proposed method was demonstrated through numerical simulations of a ground robot and experimentally using a crawler robot.

SS-sound and INS hybrid navigation system

SS-sound and INS hybrid navigation system

Cite this article as:
R. Tientadakul, H. Nakanishi, T. Shiigi, Z. Huang, L. Tsay, and N. Kondo, “Spread Spectrum Sound with TDMA and INS Hybrid Navigation System for Indoor Environment,” J. Robot. Mechatron., Vol.33 No.6, pp. 1315-1325, 2021.
Data files:
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