Zhiliu Yang

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About

Zhiliu Yang is a researcher advancing the frontiers of autonomous navigation and large-scale 3D scene reconstruction. His work centers on sensor fusion, simultaneous localization and mapping (SLAM), and novel view synthesis for robotics. Yang’s major contributions include the development of FPGA-accelerated LiDAR mapping systems for real-time SLAM, as demonstrated in his work on Cartographer, a system deployed in commercial applications like Google Street View. He also proposed π-Map, a tightly coupled fusion mechanism that dynamically integrates LiDAR and sonar data for reliable indoor mapping, addressing key challenges in autonomous robot navigation. Most recently, Yang introduced GaRField++, a reinforced Gaussian radiance fields framework that tackles scalability and rendering deficiencies in large-scale 3D reconstruction for embodied AI. His research has garnered attention, with papers accumulating citations from the robotics and computer vision communities. Yang’s work on π-Map, in particular, has been recognized for its innovative decision-based global optimization approach, marking him as a rising contributor to the field of autonomous systems and 3D mapping.