A Method of Successive Moving Baseline Estimation of a Slow Speed Robot based on GNSS Positioning

Hiroki Hayashi, Nao Sasamoto, Yoshiharu Koya,Yukihiro Kubo

Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications(2023)

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Abstract
The GNSS (Global Navigation Satellite System) is currently used in a variety of applications [1], and its positioning accuracy requirements become more and more demanding. We focus on an automatic strawberry pollination robot (under development in Kobe City College of Technology) and study a method of successive moving baseline vector estimation [2]. In this paper, we propose a method to estimate accurate successive moving baseline vectors based on the difference of the single GNSS receiver observables obtained at two successive observation time (epoch). Furthermore, we also propose a method to estimate the bias error included in the moving baseline vector. Throughout the experiment, the proposed method and the relative positioning method are compared that the error is 0.97 [cm].
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Key words
slow speed robot,successive moving baseline estimation,gnss positioning
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