Papers
7
Total Citations
102
H-Index
4
About
Kaiwen Xue is a robotics researcher whose work spans autonomous navigation, multi-sensor fusion, and unmanned surface vehicles (USVs). His primary research areas include simultaneous localization and mapping (SLAM) for aerial robots, LiDAR-inertial odometry, and autonomous aquatic systems. Xue’s most impactful contribution is the MARS-LVIG dataset (41 citations), a multi-sensor aerial robots SLAM dataset that integrates LiDAR, visual, inertial, and GNSS data—providing a critical benchmark for advancing robust localization in challenging environments. He also developed LTA-OM (34 citations), a long-term association LiDAR-IMU odometry and mapping framework that addresses the persistent challenge of consistent map building over extended missions. In the aquatic domain, Xue designed OBoat, an agile omnidirectional USV platform, and a novel projectile-based charging mechanism for autonomous docking, demonstrating practical solutions for real-world maritime tasks. His work on SCALE, a self-correcting visual navigation system using anti-novelty estimation, pushes the boundaries of deep reinforcement learning for mobile robots. With over 100 total citations and contributions spanning from gripper design to optimization-based localization, Xue is establishing himself as a versatile innovator in field robotics.
Research Focus
Key Achievements
Top Papers
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- 2LTA‐OM: Long‐term association LiDAR–IMU odometry and mapping34 citations · 2024
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- 7Design of An Adaptive Mini Gripper for Climbing Robots2 citations · 2018