A Consideration on High Accuracy Estimation of Successive Moving Baseline for a Slow Speed Robot Based on GNSS Positioning

GNSS (Global Navigation Satellite System) is currently used in a variety of applications, 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. 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 solution of the moving baseline vector. Throughout the experiment, the proposed method and the relative positioning method are compared, and the results show that the proposed method can provide the baseline vector with the accuracy of 1.06 cm.