一种多源测距与视觉惯性融合的月球车定位方法

针对月球车月面探测活动任务中对高精度定位的需求，当前视觉惯性定位方法存在误差累积，并且在缺乏先验环境信息时无法消除，基于三角测量原理的无线电定位方法可以通过测量接收端到至少三个不同发射端的距离来确定目标物体位置，但需要架设三台以上基站，因此难以满足月面环境下大范围定位的需求。文章提出了一种基于基站无线测距和视觉惯性里程计融合定位方法，以解决上述定位手段存在的问题。该方法首先利用视觉惯性里程计构建的环境模型将WIFI、UHF和UWB三类无线电基站测距信息进行融合，然后将测距结果和视觉IMU信息进行位置联合解算来确定月球车位置，最后在Matlab和Gazebo软件平台上进行仿真验证，在距离基站最远行进1500米的条件下实现了0.92米定位误差。实验结果表明，该方法能够在满足月面探测任务对于精准定位的需求。

A lunar rover location method based on the fusion of multi-source ranging and visual inertia

In light of the demand for high-precision positioning in lunar surface exploration missions, the current visual inertial positioning method suffers from error accumulation that cannot be mitigated without prior environmental information. The radio positioning method based on the principle of triangulation can determine the position of target objects by measuring the distance between the receiving end and at least three different transmitting ends. However, due to the requirement for more than three base stations, it poses a challenge in meeting large-scale positioning needs in lunar environment. The paper proposes a fusion positioning method that utilizes wireless ranging from base stations and visual inertial odometers to address the limitations of existing positioning methods. The proposed approach involves fusing WIFI, UHF, and UWB radio base station ranging information with an environment model constructed using visual inertial SLAM. Subsequently, the location of the lunar rover is determined through joint calculation of the ranging results and visual IMU data. Finally, simulation and verification were conducted on the Matlab and Gazebo software platform, resulting in a positioning error of 0.92meters at a distance of 1500meters from the base station. The experimental results demonstrate that the proposed method satisfies the requirements for precise positioning in lunar surface exploration missions.