Static and dynamic evaluation of acoustic positioning system using TDMA and FDMA for robots operating in a greenhouse

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Abstract

Acoustic positioning system has great potential to be applied in a greenhouse due to its centimeter-level accuracy, low cost, and ability of extensive greenhouse coverage. Spread Spectrum Sound-based local positioning system (SSSLPS) has been proposed to be a navigation tool for multiple agricultural robots by the authors' research team. However, to increase the system capacity for positioning multiple robots in a greenhouse, the near-far problem caused by the interference between speakers needs to be overcome. The use of different access methods, Time Division Multiple Access (TDMA) or Frequency Division Multiple Access (FDMA), is essential in the SSSLPS system for solving the near-far problem. The static positioning in a greenhouse was first evaluated by setting different parameters to determine the optimal signal setting for a dynamic experiment. From that, the moving robot tests were added with a motion capture system and tested the performance of TDMA and FDMA. The results demonstrated that TDMA can be used in a stationary sound-based positioning system with 12.2 mm accuracy, but it has a time delay problem in dynamic positioning. A simulation was designed to mimic the position error increases with different moving speeds. Although FDMA has the sound damping problem in high-frequency regions creating a peak detection issue, it achieved a higher accuracy with an average position error of 62.1 mm compared to 180.3 mm of TDMA. This study shows that the TDMA method is suitable for static measurements, while the FDMA method is suitable for measuring dynamic objects and controlling mobile robots.

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APA

Tsay, L. W. J., Shiigi, T., Zhao, X., Huang, Z., Shiraga, K., Suzuki, T., … Kondo, N. (2022). Static and dynamic evaluation of acoustic positioning system using TDMA and FDMA for robots operating in a greenhouse. International Journal of Agricultural and Biological Engineering, 15(5), 28–33. https://doi.org/10.25165/j.ijabe.20221505.6796

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