A Method of Successive Moving Baseline Estimation of a Slow Speed Robot based on GNSS Positioning
Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications(2023)
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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