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

Hiroki Hayashi, Nao Sasamoto, Yoshiharu Koya, Yukihiro Kubo
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引用次数: 1

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].
基于GNSS定位的慢速机器人连续运动基线估计方法
GNSS (Global Navigation Satellite System,全球导航卫星系统)目前被广泛应用[1],其定位精度要求也越来越高。我们重点研究了一种草莓自动授粉机器人(神户城市工业大学正在开发),研究了一种连续移动基线向量估计方法[2]。在本文中,我们提出了一种基于两个连续观测时间(历元)的单个GNSS接收机观测值的差值来估计精确的连续运动基线向量的方法。此外,我们还提出了一种估计包含在移动基线向量中的偏差误差的方法。在整个实验过程中,将本文方法与相对定位方法进行了比较,误差为0.97 [cm]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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