With the wide application of vision-based autonomous driving and mobile
robots, the impact of frequent sand-dust weather on computer vision
applications in landlocked countries during spring and autumn has also
attracted more and more attention. Although there has been a lot of
research on sand-dust image enhancement, no research has been conducted
on how to improve the positioning accuracy of vision-based autonomous
driving or mobile robots in sand-dust environments, especially because
there is currently a lack of data sets to evaluate visual positioning in
sand-dust weather. Therefore, we propose a complete set of visual
positioning data set construction methods in sand-dust weather to fill
the gap in the evaluation data set of application fields such as
autonomous driving or mobile robot attitude estimation in sand-dust
weather. At the same time, this method is also suitable for the
construction of visual positioning data sets under haze and other
similar weather. In addition, this paper further demonstrates to readers
how to use the converted dust visual positioning data set to conduct
positioning evaluation experiment of automatic driving in sand-dust
weather.