  Unmanned aerial vehicles (UAVs) visual localization in planetary aims to
estimate the absolute pose of the UAV in the world coordinate system through
satellite maps and images captured by on-board cameras. However, since
planetary scenes often lack significant landmarks and there are modal
differences between satellite maps and UAV images, the accuracy and real-time
performance of UAV positioning will be reduced. In order to accurately
determine the position of the UAV in a planetary scene in the absence of the
global navigation satellite system (GNSS), this paper proposes JointLoc, which
estimates the real-time UAV position in the world coordinate system by
adaptively fusing the absolute 2-degree-of-freedom (2-DoF) pose and the
relative 6-degree-of-freedom (6-DoF) pose. Extensive comparative experiments
were conducted on a proposed planetary UAV image cross-modal localization
dataset, which contains three types of typical Martian topography generated via
a simulation engine as well as real Martian UAV images from the Ingenuity
helicopter. JointLoc achieved a root-mean-square error of 0.237m in the
trajectories of up to 1,000m, compared to 0.594m and 0.557m for ORB-SLAM2 and
ORB-SLAM3 respectively. The source code will be available at
https://github.com/LuoXubo/JointLoc.
