Due to the declining birthrate and aging population, the shortage of labor in the construction industry has become a serious problem, and increasing attention has been paid to automation of construction equipment. We focus on the automatic operation of articulated six-wheel dump trucks at construction sites. For the automatic operation of the dump trucks, it is important to estimate the position and the articulated angle of the dump trucks with high accuracy. In this study, we propose a method for estimating the state of a dump truck by using four global navigation satellite systems (GNSSs) installed on an articulated dump truck and a graph optimization method that utilizes the redundancy of multiple GNSSs. By adding real-time kinematic (RTK)-GNSS constraints and geometric constraints between the four antennas, the proposed method can robustly estimate the position and articulation angle even in environments where GNSS satellites are partially blocked. As a result of evaluating the accuracy of the proposed method through field tests, it was confirmed that the articulated angle could be estimated with an accuracy of 0.1$^\circ$ in an open-sky environment and 0.7$^\circ$ in a mountainous area simulating an elevation angle of 45$^\circ$ where GNSS satellites are blocked.

翻译：针对少子老龄化导致建筑行业劳动力短缺问题，施工设备自动化日益受到关注。本研究聚焦于建筑工地中六轮铰接式自卸车的自动操控。实现自卸车自动操控的关键在于高精度估计车辆位姿与铰接角。本文提出一种基于图优化方法的自卸车状态估计技术，通过安装在铰接式自卸车上的四个全球导航卫星系统(GNSS)接收机，利用多GNSS冗余信息实现状态估计。该方法通过引入实时动态差分(RTK)-GNSS约束与四天线间的几何约束，即使在地形遮挡导致部分GNSS卫星信号受阻的环境中，仍能鲁棒地估计车辆位姿与铰接角。现场测试结果表明：在开阔天空环境下，铰接角估计精度可达0.1°；在模拟45°遮挡角度的山区环境中，铰接角估计精度为0.7°。