A pose-graph-based optimization technique is widely used to estimate robot poses using various sensor measurements from devices such as laser scanners and cameras. The global navigation satellite system (GNSS) has recently been used to estimate the absolute 3D position of outdoor mobile robots. However, since the accuracy of GNSS single-point positioning is only a few meters, the GNSS is not used for the loop closure of a pose graph. The main purpose of this study is to generate a loop closure of a pose graph using a time-relative real-time kinematic GNSS (TR-RTK-GNSS) technique. The proposed TR-RTK-GNSS technique uses time-differential carrier phase positioning, which is based on carrier-phase-based differential GNSS with a single GNSS receiver. Unlike a conventional RTK-GNSS, we can directly compute the robot's relative position using only a stand-alone GNSS receiver. The initial pose graph is generated from the accumulated velocity computed from GNSS Doppler measurements. To reduce the accumulated error of velocity, we use the TR-RTK-GNSS technique for the loop closure in the graph-based optimization framework. The kinematic positioning tests were performed using an unmanned aerial vehicle to confirm the effectiveness of the proposed technique. From the tests, we can estimate the vehicle's trajectory with approximately 3 cm accuracy using only a stand-alone GNSS receiver.

翻译：基于位姿图的优化技术被广泛应用于利用激光扫描仪和相机等设备的多类传感器测量值来估计机器人位姿。全球导航卫星系统（GNSS）近年来被用于估计户外移动机器人的绝对三维位置。然而，由于GNSS单点定位的精度仅为米级，该技术并未被用于位姿图的闭环检测。本研究的主要目的是利用时间相关实时动态GNSS（TR-RTK-GNSS）技术生成位姿图闭环。所提出的TR-RTK-GNSS技术采用基于单GNSS接收机的载波相位差分定位方法，与传统RTK-GNSS不同，我们可直接利用独立GNSS接收计算机器人的相对位置。初始位姿图由GNSS多普勒测量值计算的累积速度生成。为减小速度的累积误差，我们在基于图优化的框架中采用TR-RTK-GNSS技术进行闭环检测。通过无人机开展运动学定位测试，验证了所提技术的有效性。测试表明，仅使用独立GNSS接收机即可估计车辆轨迹，精度达到约3厘米。