  Can we localize a robot in radiance fields only using monocular vision? This
study presents NuRF, a nudged particle filter framework for 6-DoF robot visual
localization in radiance fields. NuRF sets anchors in SE(3) to leverage visual
place recognition, which provides image comparisons to guide the sampling
process. This guidance could improve the convergence and robustness of particle
filters for robot localization. Additionally, an adaptive scheme is designed to
enhance the performance of NuRF, thus enabling both global visual localization
and local pose tracking. Real-world experiments are conducted with
comprehensive tests to demonstrate the effectiveness of NuRF. The results
showcase the advantages of NuRF in terms of accuracy and efficiency, including
comparisons with alternative approaches. Furthermore, we report our findings
for future studies and advancements in robot navigation in radiance fields.
