Xiaohui Liang

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About

Xiaohui Liang is a researcher whose work bridges robotics, 3D geometry processing, and mobile systems. Her key research areas include 3D mesh compression, real-time data transmission, and autonomous navigation for mobile robots operating in unstructured environments. Liang’s major contribution lies in developing efficient methods for compressing and streaming 3D environmental data—such as mesh representations—to support accurate motion planning and situational awareness in rescue and exploration missions. Her most-cited paper, "3D Mesh Compression and Transmission for Mobile Robotic Applications" (2016), demonstrates how lightweight 3D models can enable robots to navigate complex terrains without overwhelming bandwidth or computational resources. While her citation count is modest, this work is foundational for integrating 3D perception into field robotics, where real-time performance is critical. Liang’s research addresses a key bottleneck in autonomous systems: how to transmit rich spatial information quickly enough for safe, adaptive movement. Her achievements highlight the importance of balancing geometric fidelity with transmission efficiency, a challenge that remains central to modern robotics and augmented reality applications.