Xukang Zhu

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About

Xukang Zhu is a rising researcher in the field of robotics perception and autonomous navigation, with a core focus on multi-sensor fusion SLAM (Simultaneous Localization and Mapping) and 3D point cloud processing. His most notable contribution is the development of VILO SLAM, a tightly coupled binocular visual-inertial SLAM system integrated with LiDAR. This work directly addresses critical failure modes in traditional visual-inertial odometry—specifically, the loss of accuracy and robustness during constant-speed motion, pure rotations, or in visually sparse environments. By fusing visual, inertial, and LiDAR data, Zhu’s approach significantly enhances state estimation reliability under challenging conditions. In a complementary line of work, he has advanced 3D perception through a novel point cloud segmentation method that combines ground removal with a multi-scale twin range image construction, improving the geometric understanding of complex environments. While his most cited paper has garnered 12 citations, his research is positioned at the cutting edge of robust, real-time perception for mobile robots. Zhu’s work is particularly relevant for researchers developing autonomous systems that must operate reliably in unstructured or feature-poor settings.