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<p>This study addresses the challenge of enabling multiple robots to share precise location information in environments where no positioning infrastructure is initially available. To overcome this challenge, we propose a method in which users deploy small Wi-Wi wireless modules on both robots and in the environment, allowing the construction of a flexible localization network without relying on preexisting infrastructure. Wi-Wi measures the propagation delay phase of a carrier wave, enabling high-precision distance measurements and time synchronization. However, due to <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(2\pi \)</EquationSource> </InlineEquation> phase ambiguity, absolute distances cannot be directly obtained. In this study, we employ a graph optimization framework that uses phase information collected by mobile robots to simultaneously estimate the trajectories of the robots and the positions of the fixed modules. Experiments demonstrated that the estimation error converges to less than 1&#xa0;m and remains robust even when the initial values contain an error of <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\pm 3\,\textrm{m}\)</EquationSource> </InlineEquation>. Furthermore, incorporating measurements between robots reduced the variance of localization errors. This method is effective for rapid robot deployment in environments where infrastructure setup is difficult, such as disaster response scenarios.</p>

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Using wireless two-way interferometry (Wi-Wi) in simultaneous localization of fixed bases and mobile robots by graph optimization

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月21日

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  • Takaaki Nara,
  • Yoshito Okada,
  • Shotaro Kojima,
  • Ranulfo Bezerra,
  • Kazunori Ohno,
  • Nobuyasu Shiga,
  • Satoshi Yasuda,
  • Kenichi Takizawa,
  • Satoshi Tadokoro

摘要

This study addresses the challenge of enabling multiple robots to share precise location information in environments where no positioning infrastructure is initially available. To overcome this challenge, we propose a method in which users deploy small Wi-Wi wireless modules on both robots and in the environment, allowing the construction of a flexible localization network without relying on preexisting infrastructure. Wi-Wi measures the propagation delay phase of a carrier wave, enabling high-precision distance measurements and time synchronization. However, due to \(2\pi \) phase ambiguity, absolute distances cannot be directly obtained. In this study, we employ a graph optimization framework that uses phase information collected by mobile robots to simultaneously estimate the trajectories of the robots and the positions of the fixed modules. Experiments demonstrated that the estimation error converges to less than 1 m and remains robust even when the initial values contain an error of \(\pm 3\,\textrm{m}\) . Furthermore, incorporating measurements between robots reduced the variance of localization errors. This method is effective for rapid robot deployment in environments where infrastructure setup is difficult, such as disaster response scenarios.