Leizheng Shu

Learning to Anchor Visual Odometry: KAN-Based Pose Regression for Planetary Landing

Accurate and real-time 6-DoF localization is mission-critical for autonomous lunar landing, yet existing approaches remain limited: visual odometry (VO) drifts unboundedly, while map-based absolute localization fails in texture-sparse or low-light terrain. We introduce KANLoc, a monocular localizati

Learning to Anchor Visual Odometry: KAN-Based Pose Regression for Planetary Landing

StepNav: Structured Trajectory Priors for Efficient and Multimodal Visual Navigation

JointLoc: A Real-time Visual Localization Framework for Planetary UAVs Based on Joint Relative and Absolute Pose Estimation

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 differenc…